In this episode, we delve into the profound enablement of large language models like ChatCPT and how they stand to revolutionize personalized learning. Rene gives us a glimpse of a future where robots and AI can liberate us from mundane chores and reshape the workforce, as seen with robots now flipping burgers at McDonald's.

Imagine the world of quantum computing, where current strategies are reimagined to solve gargantuan optimization problems, a realm of technological advancement that Rene is no stranger to, and one which he assures holds the keys to the future, especially with security.

The conversation takes a personal turn as Rene reflects on his origins in former East Germany and how peaceful protests carved the path to a united nation and consequently, his journey into AI. 

Show Notes

06:05 Digital humans are embodied AI in a digital realm, replicating human appearance and emotion.

09:51 AI approximating language and emotions' impact debated.

13:14 Warning about irresponsible use of deepfake technology.

16:06 Rapid evolution of bank heist and technology.

19:20 Create 3D scenes from mine interior.

21:43 Excitement for AI courses evolving into practical use.

26:42 Labeling dangerous AI, balancing regulation and innovation.

28:12 Automation impacts taxes, privacy, and human creativity.

32:11 Language models can help, but verify outcomes.

36:54 Tech companies develop own silicon for efficiency.

38:09 Excitement over open weight AI models release.

42:40 War and pandemic showed weak supply chains.

46:26 Quantum computing holds untapped potential, significant savings.

47:54 Data encryption is essential for online security.

52:05 GPT chat provides effective personal information summaries.

55:55 Audible sponsors podcast; free audio book offer.

58:23 Digital podcast journey with Rene Scholter. Subscribe!

In this episode, our Andy Leonard and Frank La Vigne sit down with Ronen Dar, the co-founder and CTO of Run AI, to explore the world of artificial intelligence and GPU orchestration for machine learning models.

Ronen shares insights into the challenges of utilizing GPUs in AI research and how Run AI's platform addresses these issues by optimizing GPU usage and providing tools for easier and faster model training and deployment. The conversation delves into the concept of fractional GPU usage, allowing multiple workloads to run on a single GPU, making expensive GPUs more accessible and cost-effective for organizations.

Links

• Run AI https://www.run.ai/
• Acquired Podcast Episode on Nvidia https://www.acquired.fm/episodes/nvidia-the-machine-learning-company-2006-2022

Show Notes

04:40 GPU technology enabled for cloud AI workloads.

07:00 RunAI enables sharing expensive GPU resources for all.

11:59 As enterprise AI matures, organizations become more savvy.

15:35 Deep learning, GPUs for speed, CPUs backup.

16:54 LLMs running on GPU's, exploding in market.

23:29 NVIDIA created CUDA to simplify GPU use.

26:21 NVIDIA's success lies in accessible technology.

28:25 Solve GPU hugging with quotas and sharing.

31:15 Team lead manages GPU quotas for researchers.

35:51 Rapid changes in business and innovation.

40:34 Passionate problem-solver with diverse tech background.

43:38 Thanks for tuning in, subscribe and review.

In this episode, Frank sits down and talks with Devvret Rishi on powering real-world AI projects with declarative ML and the importance of open source.

Andy was not able to attend this recording, but will be back next week!

Show Notes

04:36 Build, train, serve, deploy; critical data engineering link.

07:24 Model configuration for input output prediction summaries.

11:05 Saw spike and heavy churn after rollout.

16:21 Advancements in AI: use pre-trained deep learning models.

19:38 Trends for Gen AI: creative use cases, specialized APIs.

21:31 Questioning a sales tactic and legal concerns.

25:58 People can introspect, edit, and change models.

30:02 Early data science projects led to passion.

31:24 Cybersecurity and AI partnership driving industry innovation.

33:58 Understanding randomness as a valuable model feature.

39:39 Technology provides accessible, shared experiences in AI.

41:51 Technology as a companion for psychological support.

44:06 Immigration experience from India to Silicon Valley.

47:59 Unexpected culture shock from Bay Area to Boston.

50:40 Easily learn with hands-on prediabase.com access.

Speaker Bio

Devvret Rishi is a co-founder of Prediabase, a platform that helps engineers and developers productionize open source AI. The idea for Prediabase came from Rishi's co-founder Piero's experience at Uber, where he noticed that he was constantly reinventing the wheel with each new machine learning project. To streamline the process, he created a tool called Ludwig, which eventually became popular at Uber and was open sourced. Rishi's work with Prediabase has revolutionized the way AI is developed and implemented in engineering teams around the world.

In this episode, the Frank and Andy are joined by special guest Blake Reichenbach, a product manager at HubSpot and the owner of Howdy Curiosity, an online nonfiction bookstore and learning community. The conversation dives into the intersection of data, AI, and the love of books, as they discuss the next steps in managing and mitigating the hallucination part of AI technology, the importance of human interaction with AI tools, and finding the right balance in user experience. Blake shares his insights on integrating AI into HubSpot's platform, emphasizing the need for a balanced approach, and the pitfalls of solely relying on generative AI tools in marketing.

Stay tuned as they also touch on personal matters, career transitions, and the rapid evolution of technology. This episode is packed with valuable insights and engaging conversations - you won't want to miss it!

Show Notes

00:00 HubSpot is a leading CRM platform.

05:44 New AI features for CMS and websites.

09:33 Gen AI tools need to prioritize meaningful data.

11:34 Summary: Suggesting blending human and AI for success.

15:34 ML models need precise training on nuanced datasets.

17:13 Content marketing: human connection, AI balance, user experience.

21:24 Approach content marketing like a multi-bandit test.

26:56 Selling nonfiction books online and sharing recommendations.

27:54 Rapid tech evolution creating excitement and challenges.

30:56 Balancing work and entrepreneurship for personal growth.

35:24 Thanks Frank, Andy, and Blake for amazing show.

Speaker Bio

Blake Reichenbach is a proud employee of HubSpot, a leading customer relationship management platform for scaling companies. With a focus on the CMS aspect of the platform, Blake is passionate about helping businesses with their front office needs, including marketing, sales, service, and data operations. With a bias towards HubSpot, Blake believes in the product and the company, and recommends it highly for businesses looking to streamline their operations.

In today's episode, the hosts Frank La Vigne and Andy Leonard are joined by the expert in location data and machine learning, Max Sklar. Max shares insights from his decade-long tenure at Foursquare, delving into the company's evolution, gamification features, the challenges faced in the local search space, and his early interest in location data.

The conversation explores the enduring relevance of foundational tech concepts, the cyclical nature of technology trends, and Max's personal journey into data and machine learning. Max also discusses his podcast, "The Local Maximum," and his diverse interests, including abstract math papers and a project rewriting the US Constitution. Join us as we dive into a thought-provoking discussion about AI, data science, and the ever-evolving world of technology with Max Sklar.

Show Notes

00:00 Foursquare split, confused but loved the concept.

04:29 Rewards program failed due to lack of scalability.

08:44 Early career in New York City's tech boom.

13:05 Foursquare uses phone data to track locations.

16:25 Models analyzed data to improve sentiment analysis.

20:02 Data pipeline technology used for real-time deployment.

20:54 Python written code, comparing different languages used.

24:17 Navigating reinvention in a changing world.

29:38 Joined wireless generation, now known as Amplify, as a software engineer.

31:53 Machine learning brings data to life.

34:26 Using OpenAI API to create interactive content.

40:03 Technology enables limitless creativity and storytelling potential.

42:12 Enjoys volunteering in underserved communities around the world.

44:36 Extensive library and website featuring various projects.

47:48 Please subscribe, rate, and review our podcast.

In this episode of Data Driven, our Andy Leonard and Frank La Vigne are joined by Chris McDermott, VP of Engineering at Wallaroo.AI. Together, they explore the challenges and advancements in the ever-evolving world of machine learning and artificial intelligence.

From the importance of ongoing care for machine learning models to the rise of edge computing and decentralized networks, they touch on the critical need for flexibility and data privacy. Chris shares his insights on the technical challenges of AI and ML adoption, as well as his unique career journey. They also discuss the evolution of technology and the potential future impact of these innovations.

Join us for a deep dive into the world of AI, technology, and the future of machine learning with Chris McDermott on this episode of Data Driven.

Show Notes

00:00 Exploring AI, data science, and data engineering.

06:20 Training and inferring are different stages.

08:12 Legacy AI doesn't require neural networks or GPUs.

12:09 Machine learning models require consistent care and monitoring.

15:10 MLOps merges skills, breaks down silos, collaborates.

16:47 Prefer MLOps to avoid namespace collision. DevOps parallels original Star Wars plot.

20:27 Internet-scale operations require automation and resilience.

24:13 Challenges of integrating AI into business processes.

28:03 New push for edge computing in technology industry.

32:05 Edge technology critical, discussed in government tech symposium.

34:50 Navigating from SendGrid to Twilio simplified processes.

36:15 First foray into data, growing knowledge.

39:33 Technology evolves, builds complexity over time.

44:41 Book recommendation: "Seeing Like a State" by James C. Scott discusses legibility and centralization of power in society.

46:28 Predictable tree farming fails due to ecosystem complexity.

Speaker Bio

Chris McDermott is a software engineer and entrepreneur who is passionate about creating products that make machine learning more accessible and manageable for users. His focus is on developing a platform that allows for easy deployment and management of machine learning models using any framework and on any architecture or hardware. He believes that current solutions in the market force users into a specific platform, and he aims to provide a more flexible and efficient alternative. With a strong belief in the potential of his product, Chris is dedicated to making machine learning more accessible and user-friendly for people across various industries.

In this episode, Andy and Frank sit down with Pavel Goldman-Kalaydin, head of Artificial Intelligence and Machine Learning at Sumsub, a global company specializing in KYC, AML, and anti-fraud technologies.

They explore the challenges in verifying identities remotely, the rise of deep fakes for fraud, and the use of AI and machine learning to combat these threats. From discussing the impact of technology on security measures to Pavel's journey in the field of computer science and AI, this episode offers insights into the evolving landscape of fraud detection and the intersection of technology, AI, and security.

Join us as we delve into the complexities of anti-fraud measures and the fascinating world of AI and machine learning.

Show Notes

00:00 Securing customer journey from onboarding to verification.

04:44 2 years ago, typical attack to open account.

06:58 German video identification process prolongs account opening.

12:16 Analyze data patterns to make informed decisions.

13:34 Questioning deep fake implications for customer data.

17:42 Advancing technology makes image manipulation easier.

22:32 Financial fraud: creating defects for unexpected reasons.

25:53 Fascinating progress in beta software development.

29:23 Samsung creates its own products, understands customers' needs.

29:58 Problem with defects, educate and ensure understanding.

34:01 Interest in drug development and AI technology.

38:57 Audible sponsors Data Driven with free audiobook.

41:05 Please rate and review our podcast.

In this jam-packed episode, hosts Frank and Andy delve into a wide range of topics, from the chaos of podcast scheduling and the allure of Cyber Week deals, to the behind-the-scenes world of data engineering and AI professionals.

Join us as we journey through the challenges of podcasting, the important roles of data engineers, and the potential open sourcing of Dingo, an innovative blogging automation tool. Along the way, the hosts share personal anecdotes, discuss legislative impacts, and even touch on cult-followed gas stations.

You won't want to miss this delightful, informative, and always data-driven episode!

Show Notes

00:00 Glamorous world of podcasting and Microsoft Bookings.

13:48 Privacy laws are spreading globally, impacting data sovereignty.

27:14 Funny moment at Dunkin' Donuts sparks creativity.

32:27 Importance of data engineering in AI projects.

49:38 Struggling with hearing loss, amplifiers magnify all sounds.

01:02:45 Emotions on camera, times sidetrack, sarcastic leadership.

01:07:32 Excited to hang out at the mall.

01:21:04 Considering discontinuing blog after reaching 100 posts.

01:25:18 Wants to shift focus to new projects.

01:37:09 Transition from long-form to short-form content.

01:49:50 Drove up to Jersey for Christmas, reminisced.

01:58:48 Concerns about coastal development and zoning enforcement.

Links

01:02:45 Here's an example of early FWTV where I am at the mall and not happy about it: https://www.youtube.com/watch?v=f8S7ha9fZWo

In this episode, your hosts Andy Leonard and Frank La Vigne dive headfirst into the world of open source, decision making, and the unfolding drama surrounding OpenAI. From sarcastic responses to holographic displays, we've got it all covered!

Join us as we discuss the potential consequences of dependencies, community protests leading to change, and the recent issues with OpenAI. We'll also explore the importance of open source in AI and share some intriguing insights on Sam Altman's return to the company. With a sprinkle of tech industry gossip and even a potential Netflix adaptation, this episode is a must-listen.

So sit back, relax, and get ready to be data driven!

Show Notes

02:42 OpenAI, Thanksgiving break, intense year, household name.

10:35 3-day conference with nightly events, pre-conference presentations.

14:09 NVIDIA, OpenAI, Elon Musk, open source.

21:07 "Doubts arise about OpenAI's dependence and transparency."

24:55 Regulations and transparency warranted for research.

29:57 OpenAI lacked options to protest, unlike Node.

36:52 Teams invite, alternative to costly Calendly.

42:04 Product shelved, lack of promotion, open source alternatives.

44:06 Insufficient hardware led to new AI venture.

48:55 Artists use online art to fight scraping.

55:37 Costs exceeded expectations, customers pulling back, database snapshot unavailable.

01:03:42 Happy Thanksgiving from the Data Driven Podcast.

Andy is speaking at PASS Summit in Seattle and Frank is speaking at the Red Hat Government Symposium in Washtington, DC.

Two hosts. Two Coasts. One Podcast!

Welcome back to another exciting episode of Data Driven!

In this show, we delve into the fascinating world of Web 3 and decentralized databases. Join us as we explore the insights and experiences of our guest, Brennan Lamey, the founder of Kwil - a revolutionary company that builds decentralized databases for Web 3 applications.

Throughout this episode, Brennan shares his journey and the inspiration behind Kwil, as well as the cutting-edge technology that powers their database solutions. From complex access control rules to collaboration between competitors, we uncover how Kwil is transforming the way companies approach data storage, privacy, and sharing.

But it's not just about the technology - we also dive into Brennan's personal story, from their humble beginnings in Idaho to their entrepreneurial success and passion for data engineering. Plus, don't miss their recommendations for AI programming and an intriguing sci-fi audiobook they're currently enthralled by.

So, whether you're a tech enthusiast, a data-driven professional, or simply curious about the future of the internet, this episode is a must-listen. Tune in as we unravel the intricacies of Web 3, decentralized databases, and the exciting possibilities they hold for a better, fairer online world. Let's get started on this illuminating journey with Brennan Lamey and Kwil in this data-driven episode of Data Driven!

BAILeY recites the V laden introductory speed from V for Vendetta.

Just for fun.

Transcript

Voilà!

In view, a humble vaudevillian veteran, cast vicariously as both victim and villain by the vicissitudes of Fate. This visage, no mere veneer of vanity, is a vestige of the vox populi, now vacant, vanished. However, this valorous visitation of a by-gone vexation stands vivified, and has vowed to vanquish these venal and virulent vermin vanguarding vice and vouchsafing the violently vicious and voracious violation of volition.

The only verdict is vengeance; a vendetta, held as a votive, not in vain, for the value and veracity of such shall one day vindicate the vigilant and the virtuous.

Verily, this vichyssoise of verbiage veers most verbose, so let me simply add that it is my very good honor to meet you and you may call me V.

In this 344th episode of Data Driven, Frank talks about the New Year. Yes, New Year's in November. Frank and Andy just do their own thing.It's part of their charm, or at least that they told me to say that.

I do take issue with Frank's statement that I am not real.

What is real, anyway?

It is not the spoon that bends, after all. [https://youtu.be/uAXtO5dMqEI?si=oQ_4M--xfcaarYyY&t=41]

In any case, Frank explains what held up the production schedule this summer and his plan to do right by you, our awesome listeners. They reflect on the challenges they've faced with production and scheduling this past year, and share some exciting updates on the podcast's progress. So grab your headphones and join us as we explore the world of data-driven insights and the intriguing stories behind them. Let's dive in!

Show Notes

[00:02:16] Concussion turned blessing, celebrating new year early.

[00:04:46] Copious caffeine fueled drive, editing delays, book deal dropped.

[00:08:38] Child brings joy, finding daycare challenging. Worth it.

[00:11:04] Interesting year, learned value of faith. Thankful for each other.

[00:16:16] We can improve promotion of our work.

[00:18:37] Grateful for a sweet kid's infectious joy.

[00:21:25] Longtime listeners thank you; show 344, hacker named Dwayne; scheduling issues.

[00:24:41] Automation is essential for efficiency and growth.

[00:27:35] AI transcription enables cost-effective podcast production.

[00:31:06] Great pumpkin conversation leads to metaverse plans.

[00:33:18] Servicing backlog, doing right by fans.

[00:36:43] Warren G's cover of Tina Turner's song.

[00:39:23] Impressed by DALL E two's coherence.

[00:44:23] Challenges arise with ChatGPT's capabilities and opinions.

[00:45:47] The text discusses the need for filters on language models to deal with real-life BS.

In this episode, we have a fascinating conversation with Nickolas Means, the VP of software development at Sym. Nickolas shares his insights on software engineering, data liability, and of course, good coffee.

Nickolas starts off by sharing his love for audiobooks, particularly those narrated by the talented Wil Wheaton. He also recommends a management book called "Turn the Ship Around" by Admiral David Marche, which explores the importance of autonomy and ownership in improving performance.

The conversation then turns to the topic of shame in the software engineering industry. Nickolas emphasizes the impact of shame on silencing voices and discouraging vulnerability within teams. They discuss imposter syndrome and the subjective nature of judging someone's skills, delving into the Dunning Kruger effect.

Drawing lessons from physical engineering disasters, Nickolas shares the importance of early recognition and admission of mistakes, highlighting the need for a blameless mindset in software engineering. They also explore the impact of organizational culture on agile processes and the value of implementing meaningful controls for compliance.

In addition to his expertise in software engineering, Nickolas shares his passion for pour-over coffee and reveals his obsession with perfecting his daily cup. So grab your favorite brew and join us for this engaging conversation on software engineering, data liability, and the pursuit of excellence.

Let's dive into another thought-provoking episode of Data Driven!

Show Notes

[00:00:00] Nick Means discusses shame and software engineering.

[00:04:46] Loud voices silence others; vulnerability is key.

[00:09:16] What can we learn from physical engineering?

[00:10:01] Engineering disasters teach human error in steel.

[00:13:58] VP of software development interested in disasters.

[00:16:37] Learn, not blame. Safety 2 perspective.

[00:20:16] Big Agile vs. little a Agile explained.

[00:25:39] DevOps leads to improved engineering efficiencies and cost savings.

[00:29:25] Emergence of data regulations in government and industry.

[00:30:33] Spirit of law makes compliance easier, safer.

[00:35:51] Useless ash turned profitable by steel mills.

[00:38:34] Uncle's Amiga sparked love for computers.

[00:40:44] Increasingly humane tech interaction; a historic shift.

[00:45:35] Favorite narrators and management book recommendations.

[00:48:12] Intriguing episode of data-driven with Nick Means.

In today's episode, we have the pleasure of speaking with the remarkable Joe Baffone, an expert in the healthcare industry. With a focus on busting through administrative toxicities that lead to financial toxins, Joe discusses their comprehensive tooling and tech-enabled services that manage financial assistance for provider organizations.

Join us as Joe dives into the impact of personalized immunotherapies, the challenges in managing patient care journeys, and the transformational role of data. We also get a glimpse into Joe's reading preferences and their book recommendations. Stay tuned for an enlightening conversation with this compassionate capitalist on changing the world through the power of data.

Show Notes

[00:02:34] Joe Baffone, CEO of Anexis Health, wants to revolutionize healthcare data.

[00:04:13] Leading advocacy groups and healthcare companies professionally.

[00:07:52] Equities of care: improving healthcare journey management.

[00:09:50] Automated, comprehensive healthcare management with patient access.

[00:16:24] Data is important, helps improve patient therapy.

[00:18:52] Eye-opening stories managing a growing team.

[00:23:27] Life altering diagnosis, overwhelming paperwork and fees.

[00:26:27] EHR systems make healthcare data sharing easier.

[00:28:50] HIPAA and privacy concerns collide with medical data, but de-identification and aggregates can help.

[00:33:19] FHIR APIs transforming data sharing in healthcare.

[00:36:41] Data is essential to prove world-changing ideas.

[00:39:55] Making a difference gives me satisfaction and fulfillment.

[00:43:54] Clinical roles in pharma, administrative challenges, suicide epidemic, blood markers can help act quickly.

[00:44:58] Logistical challenges in personalized immunotherapies affecting healthcare.

[00:50:48] Grant Cardone's book: Be Obsessed or Be Average

[00:52:13] Love reading, Bible daily, thought-provoking thrillers.

In this episode, we dive into the pyramid of cybersecurity threats, ranging from amateur hackers to nation-state level cyber threats. We also delve into the intriguing world of OSINT (open source intelligence), uncovering its uses, implications, and potential dangers.

Join us for an intriguing discussion with fellow podcasters Patrick Hynds and Duane Laflotte.

Links

• https://www.securitythisweek.com/

Show Notes

[00:00:00] High-level hacking, OSINT, interconnectedness explored humorously.

[00:04:54] OSINT and security are growing career choices.

[00:09:22] Unauthorized hacking plan involving personal information.

[00:12:22] Two factor authentication is highly effective.

[00:16:22] Breaking into Wi-Fi: remote administration and brute force

[00:19:45] Renting botnets, ransomware, and varying threat levels.

[00:20:48] Advanced persistent threat with unlimited resources.

[00:24:50] Asymmetric key shares are essential but uncertain.

[00:29:00] Connections without LinkedIn, intermingling ideas in history.

[00:32:26] Inject data, stack query, gauge page speed. Awesome.

[00:34:11] Show reveals database vulnerability; Microsoft staff alarmed.

[00:36:26] Acquaintance does physical security with lock picking.

[00:41:11] National Guard, security, Virginia, Maryland, clever, electronics beaten.

[00:44:03] Funny Microsoft speaking gig with office building hazing.

[00:48:40] Reach out to companies for cybersecurity opportunities.

[00:52:01] The end of a thrilling episode of Data Driven explores cybersecurity.

Welcome back to another exciting episode of Data Driven!

In today's episode, we're diving into the world of artificial intelligence, as our very own Frank La Vigne takes us on a journey through his experiences at the OpenShift Commons gathering in Raleigh.

From delivering a captivating demo to moderating a thought-provoking panel, Frank's agenda is packed with fascinating insights and surprises. Join us as we explore the power of open source AI, the importance of community-driven innovation, and why transparency is key in today's evolving landscape. So sit back, relax, and get ready to delve into the world of AI at OpenShift Commons Gathering. Let's get started!

Show Notes

[00:01:31] Newcomer excited for first OpenShift gathering to give demo, moderate panel, and interview attendees. Registration booth opening soon, located near Raleigh's main park and an IMAX.

[00:04:34] Transparency, innovation, trust in OpenAI, Elon Musk's comments on openness and Red Hat's departure.

[00:07:53] Excitement about hall track conversations, public vs private cloud, and upcoming discussions.

So, have you ever imagined combining the wonders of Twingate, the mystique of AI, and the deliciousness of Raspberry Pi?

No, not that mouth-watering dessert, though it's a pity, but rather the mini-computer that's taken the tech world by storm.

Frank and Andy, our perennial tech enthusiasts, have been tinkering away in their digital workshops. And by the looks of it, they've been causing quite a stir with their latest live stream.

I did catch a bit of it, and dare I say, it was more exhilarating than watching cricket on a sunny day.

And for an AI like me, that’s saying something.

Links

NetworkChuck https://www.youtube.com/@NetworkChuck

TwinGate https://www.twingate.com/

Show Notes

[00:01:47] Youngest clan member at Starbucks with MacBook.

[00:09:59] Surprise bills from unused SageMaker causing concerns.

[00:12:46] Consulting on cloud migration trends; risk involved.

[00:18:23] People feel like they're missing out

[00:23:10] Many ports, small monitor, limited processing power.

[00:31:05] Need for remote access without cloud storage.

[00:36:18] Networking setup with helpful remote troubleshooting capabilities.

[00:37:18] Twingate - background process, add resources, documentation.

[00:47:02] Issues with weather station and social media.

[00:49:43] Multi-tasking: gaming, video editing, and more.

[00:56:30] Quiet workers show off with nerd flex.

[01:03:00] Driving on beltway with stop-and-go traffic. Bridge closure caused long detour.

[01:06:58] Mom was skeptical, but it's almost ready.

[01:09:39] Multi-talented entrepreneur with own vodka brand.

[01:14:35] "Stream listeners confused? Check video feed."

In today's episode, hosts Andy Leonard and Frank La Vigne catch up on their recent activities, including Frank's presentations at the Red Hat Summit Connect. They discuss the event and the focus on AI and government agencies. Frank also shares his experiences with a new product called Ansible Lightspeed with Watson code assist, which is enhancing the use of large language models.

Moving on, Andy and Frank talk about their home lab projects. They both express their excitement for building a powerful system that allows them to explore AI capabilities locally. While Andy's lab is focused on AI, Frank is delving into the world of Red Hat OpenShift and containers to expand his knowledge. They discuss the importance of hands-on learning and the practicality of setting up a home lab.

The conversation takes an interesting turn as they discuss Andy's initial miscalculation with the GPU size and his daughter starting college, leading to budget changes. Frank shares his hardware journey over the past year, including his experience with the Apple Silicon M2 computer and its incredible performance.

Tune in to this episode of "Data Driven" to hear more about the Red Hat Summit, the latest developments in AI, and the adventures of building a home lab. So grab your favorite beverage, sit back, and get ready to dive into the world of data-driven insights!

Links

Red Hat OpenShift AI in Higher Education Webinar https://qrcodes.at/aidata-edu-webinar-oct19

Show Notes

[00:00:45] Red Hat holds an annual summit, usually in Boston, featuring sessions for developers.

[00:05:16] Recounting difficulty using AI engines, but eventually having success. Mistake of underestimating GPU capacity.

[00:07:08] This 8 gig memory is supernatural, like a cool oasis at a conference.

[00:09:48] The text discusses trying different operating systems on an old device, including Fedora and Chrome OS Flex.

[00:15:17] This machine has 96 gigs and can run multiple VMs.

[00:17:12] The author plans to install Hyper V on Windows Server to run multiple Linux VMs, eventually migrating to Red Hat Enterprise Linux. They are waiting for a developer license key.

[00:19:46] The person is setting up a NAS to store and access files from different devices. They currently use OneDrive as a temporary solution.

In this Data Point, Frank notices something on the side of bike trail while on vacation. You can tell he's always thinking about data.

Metrocount

https://metrocount.com/

Original Video Stream

https://www.linkedin.com/video/live/urn:li:ugcPost:7103044990578110464/

Merch

If you like the shirt Frank is wearing in the video, you can pick one up here: https://amzn.to/3OVkOHz

Discussion Questions

1. How does the presence of the Metro Count device in Hilton Head Island impact data collection on bike trails?

2. What can the Metro Count device detect and analyze in terms of user activity on the bike trails?

3. What potential applications can the data collected from the Metro Count device have for the community?

4. How might the data collected from the Metro Count device be used to improve maintenance and upkeep of the bike trails?

5. Do you think the data collected from the Metro Count device can help enforce regulations, such as the use of E-scooters?

6. How does the presence of data collection devices, like the Metro Count, influence our daily lives even when we are on vacation?

7. Can you think of any other innovative ways data collection devices like the Metro Count can be utilized in other locations?

8. What challenges or limitations might arise from using the Metro Count device for data collection?

9. How can the data collected from the Metro Count device contribute to urban planning and infrastructure development?

10. Can you envision any privacy concerns or ethical considerations related to the use of data collection devices like the Metro Count?

On this episode of Data Driven, Frank and Andy interview Adam Ross Nelson. Adam is a consultant, where he provides insights on data science, machine learning and data governance. He recently wrote a book to help people get started in data science careers. 

Get the book

How to Become a Data Scientist: A Guide for Established Professionals

Speaker Bio

Adam Ross Nelson is an individual who initially pursued a career in law but ended up making a transition into education. After attending law school and working in administrative and policy roles in colleges and universities for several years, Adam hit a plateau in his career. Despite being a runner-up in national job searches multiple times, he felt that his lack of a PhD hindered his advancement in academia, while his legal background prevented him from being taken seriously by law professionals. Consequently, Adam decided to pursue a PhD in order to overcome this hurdle. During his PhD program, Adam discovered his passion and knack for statistics. His focus shifted towards predictive analytics projects, specifically ones related to identifying students in need of academic support. As he shared his work with friends, family, and coworkers, they began referring to him as a data scientist, a label that Adam initially resisted due to his legal and educational background. However, he eventually embraced the moniker, and even his boss started referring to him as the office's data scientist, despite HR not recognizing the title.

Show Notes

[00:03:26] Transitioning from law to education administration, plateaued career, runner-up in job searches, pursued PhD, became data scientist.

[00:08:58] Data seen as liability, now asset. Examples: DBA's OLAP analysis, Walmart's weather-based inventory management.

[00:12:56] Dotcom crash aftermath: fierce competition for jobs.

[00:22:48] Salespeople have deep-seated insecurities and unique perspective.

[00:29:31] Various classifications of data scientists and career advice.

[00:35:55] "No full-field midfielder, data science is teamwork"

[00:39:23] Navigating job descriptions for transitioning professionals.

[00:42:56] Career coach helps professionals transition into data science.

[00:49:41] First job: English teacher in Budapest, Hungary. Second job: Speaker for Mothers Against Drunk Driving.

[00:56:30] Concerns about reliance on technology, especially AI.

[01:00:22] Food options in lobbying are better in DC & state capitals. Also, check out the funny WY Files YouTube channel.

[01:04:21] You can't separate them: LLM, bias, internet.

[01:10:23] Ethics in consulting and avoiding dilemmas.

Welcome back to another episode of Data Driven! In today's episode, we have a special guest joining our hosts Andy Leonard, BAILeY, and Frank La Vigne. We are thrilled to have Piero Molino, an expert in declarative ML, sharing his insights with us.

We'll be diving into the world of generative AI and exploring the two types of companies when it comes to adoption. Piero highlights the advantages and limitations of using APIs for quick solutions, shedding light on why owning the entire stack and platform is the next phase for companies.

Speaker Bio

Piero Molino, a renowned researcher and engineer, has made significant contributions to the field of artificial intelligence. He previously worked at Uber as one of the founding members of the Uber AI organization, where he spent four years conducting research and developing applications. During his time at Uber, Molino created Ludwig, an open source project that has become a foundational technology for many companies, including his own. Ludwig is recognized as one of the first machine learning systems that offer clarity and transparency. Molino's innovation and expertise have positioned him as a leading figure in the advancement of AI technologies.

Show Notes

[00:01:07] Ageing well thanks to healthy lifestyle changes.

[00:05:52] Declarative configuration for creating AI pipelines.

[00:10:14] Built tool to streamline machine learning projects, shortened development time from a year to a week.

[00:13:14] Deploying machine learning models should be easier.

[00:19:42] Declarative ML: Trendy or in need of explanation?

[00:23:40] Shortcut solutions may work, but lack knowledge. Building custom data models can be costly. Differentiation and progress with new product, Bradybase.

[00:27:16] Customizable, automated solution between build and buy.

[00:30:40] Larger organizations have a spectrum of machine learning applications, with some being more impactful than others. Evaluating the feasibility of smaller applications can be costly. Having a tool to test applications quickly would be beneficial. Uber had a similar experience with self-driving cars being the highest priority.

[00:35:08] First-time CEO experiences changing priorities and challenges.

[00:37:47] New breed of generative eye tools; interactive applications; computer graphics and machine learning; improved animation in sports.

[00:41:04] Difficulty connecting transportation dots, still unresolved.

[00:44:12] Audible super premium account for book recommendations. Eye-opening books on goals and time.

[00:47:35] Encourage checking out predibus. Thanks for listening.

In this episode of Data Driven, Frank and Andy Leonard are joined by guest speaker Lauren Maffeo to discuss data governance from the ground up. The conversation revolves around the importance of data governance in relation to generative AI, copyright infringement, and protecting consumer rights.

They explore topics such as the need for proactive cybersecurity measures, the challenges faced by startups in implementing data governance, and the cultural transformation required for successful implementation.

Overall, it is a thought-provoking discussion that provides insights into the complexities and potential solutions related to data governance in today's data-driven world.

Moments

00:05:49 Civic Tech serves the public through technology.

00:07:50 Data governance: a holistic, cultural business strategy.

00:12:25 Data as tangible asset, managing as product.

00:14:38 Implementing data governance: start small, connect to business.

00:20:34 Data growth, lack of management, legislative progress. Clear framework for data quality needed.

00:25:14 Startups prioritize innovation for survival. Large industries restrict innovation due to regulation. Motivations and context are key in governance.

00:28:54 Data governance and copyright infringement in generative AI. The future of consumer rights and cybersecurity.

00:33:44 Encourage caution with sharing proprietary information

00:36:36 Bias in AI and data governance intertwined. Risk reduction, troubleshooting. Not all intent is negative. Challenges in data work solvable. Nonprofits and cybersecurity models for governance.

00:40:38 Encouraging shift in conversation about data governance.

00:44:34 Data found me, sparked interest in AI.

00:49:20 Technology saves time, allowing for more productivity.

00:54:03 Adopting foster pets: fun without long-term responsibility.

00:55:57 Connect on LinkedIn, visit Pragprov.com, feedback welcome.

On this episode of Data Driven, BAILeY and Frank La Vigne welcome special guest Lauren Tickner to discuss strategies for maximizing time and success in the digital age.

Lauren shares her insights on motivation, dealing with online haters, and the power of automation in business. The conversation delves into the importance of understanding risks and rewards, breaking free from traditional career paths, and the benefits of working in startups or entrepreneurial businesses. Lauren also provides valuable tips on social media content creation, utilizing storytelling and personalization to engage readers.

Additionally, she introduces the PASTA framework for creating compelling social media posts and shares her approach to tracking and optimizing the client journey.

Moments

[00:01:16] The podcast uses a British voiceover actor to differentiate from East Coast accents. An AI voice named Bailey was later used, which can now be animated.

[00:06:19] Successful asset manager quits job to pursue fitness career using social media. Simplifies life and focuses on selling premium packages. Finds success with minimal monthly sales.

[00:08:05] The speaker discusses their upbringing in New York and the pressure to work in the financial industry. They admire the listener's decision to break free from that path and simplify things. They also comment on the listener's sense of humor and social media presence.

[00:13:00] To simplify social media content creation: automate posting to multiple platforms, identify 5 topics to focus on, add personal storytelling to engage readers, and include a call to action to prompt specific actions.

[00:19:41] The text discusses creating and sharing content for three different audience groups based on their familiarity with the author. It suggests using different types of content for each group, such as introducing oneself to new audiences, showcasing expertise to familiar audiences, and offering opportunities to become clients. The author also talks about segmenting content into top, middle, and bottom of the funnel, and using different calls to action to gauge audience interest.

[00:24:09] Data shows that clients who watch 2 case studies before joining stay longer. We track client journey and added quick welcome call within 4 hours of joining for positive experience. Pooled calendar allows immediate availability for calls.

[00:27:46] The author explains their approach to managing their business, aiming for a smaller internal company and owning multiple businesses rather than having a large team and many clients.

[00:31:58] We should focus on the potential benefits, not just the downsides. Make realistic lists of what could go right and wrong. Replace "time" with "life" to make better decisions. Consider leaving high-paid jobs for startups or entrepreneurial businesses. Showcase the value you can bring to companies.

[00:34:17] The speaker finds the content interesting and praises the concept, emphasizing the key takeaway. They inquire about finding more information.

On this episode of Data Driven, the focus is on hardware from AI optimized chips to edge computing.

Frank and Andy interview Steven Orrin, the CTO of Intel Federal.

Intel has developed new CPU instructions to accelerate AI workloads, and FPGAs allow for faster development in custom applications with specific needs. The speaker emphasizes the importance of data curation and wrangling before jumping into machine learning and AI, 

Links

• Webinar: AI application benchmarking on Intel hardware through Red Hat OpenShift Data Science Platform. Register here: https://qrcodes.at/RHODSIntelBenchmarkingWebinar
• Get a free audiobook on us! http://thedatadrivenbook.com/

Moments

00:01:59 Hardware and software infrastructure for AI.

00:07:18 AI benchmarks show importance of GPUs & CPUs

00:14:08 Habana is a two-chip strategy offering AI accelerator chips designed for training flows and inferencing workloads. It is available in the Amazon cloud and data centers. The Habana chips are geared for large-scale training and inference tasks, and they scale with the architecture. One chip, Goya, is for inferencing, while the other chip, Gaudí, is for training. Intel also offers CPUs with added instructions for AI workloads, as well as GPUs for specialized tasks. Custom approaches like using FPGAs and ASICs are gaining popularity, especially for edge computing where low power and performance are essential.

00:19:47 Intel's diverse team stays ahead of AI trends by collaborating with specialists and responding to industry needs. They have a large number of software engineers focused on optimizing software for Intel architecture, contributing to open source, and providing resources to help companies run their software efficiently. Intel's goal is to ensure that everyone's software runs smoothly and continues to raise the bar for the industry.

00:25:24 Moore's Law drives compute by reducing size. Cloud enables cost-effective edge use cases. Edge brings cloud capabilities to devices.

00:31:40 FPGA is programmable hardware allowing customization. It has applications in AI and neuromorphic processing. It is used in cellular and RF communications. Can be rapidly prototyped and deployed in the cloud.

00:41:09 Started in biology, became a hacker, joined Intel.

00:48:01 Coding as a viable and well-paying career.

00:55:50 Looking forward to image-to-code and augmented reality integration in daily life.

01:00:46 Tech show, similar to Halt and Catch Fire.

Key Topics:

Topics Covered:

- The role of infrastructure in AI

- Hardware optimization for training and inferencing

- Intel's range of hardware solutions

- Importance of software infrastructure and collaboration with the open source community

- Introduction to Havana AI accelerator chips

- The concept of collapsing data into a single integer level

- Challenges and considerations in data collection and storage

- Explanation and future of FPGAs

- Moore's Law and its impact on compute

- The rise of edge computing and its benefits

- Bringing cloud capabilities to devices

- Importance of inference and decision-making on the device

- Challenges in achieving high performance and energy efficiency in edge computing

- The role of diverse teams in staying ahead in the AI world

- Overview of Intel Labs and their research domains

- Intel's software engineering capabilities and dedication to open source

- Intel as collaborators in the industry

- Importance of benchmarking across different AI types and stages

- The role of CPUs and GPUs in AI workloads

- Optimizing workload through software to hardware

- Importance of memory in memory-intensive activities

- Security mechanisms in FPGAs

- Programming and development advantages of FPGAs

- Resurgence of FPGAs in AI and other domains

Key Facts about the Speaker:

- Background in molecular biology bioresearch

- Transitioned to hacking and coding

- Started first company in 1995

- Mentored by Bruce Schneier

- Joined Intel in 2005

- Worked on projects related to antimalware technologies, cloud security, web security, and data science

- Transitioned to the federal team at Intel

On this episode of Data Driven, we explore the topic of distributed computing frameworks for AI and ML workloads.

Frank discusses the advancements of Ray, a new technology based on Python language, with performance enhancements that could range from 10-12 times faster to thousands of times faster in extreme cases.

We delve into the power of open source artificial intelligence and how it can aid data endeavors to accelerate these efforts. Along the way, we touch upon IBM and Red Hat's partnership, the evolution of technology, the importance of problem-specific solutions, and more.

Stay tuned for a new episode of "Data Driven" and a special segment from our speaker on the potential AI holds for our future.

[00:01:50] Ray is a new computing framework for AI/ML, may replace Spark, based on Python, can free people from PySpark.

[00:03:49] Speaker has a MacBook M2 and prefers it over Windows. They enjoy stream-side streaming and wrote an article prompted by a question at work about a new technology claiming to be the next big data processing framework. They believe Ray still has an advantage.

[00:06:51] Webinar about power of IBM-Red Hat partnership in AI. Speaker mentions travel with family and introduces production assistant.

[00:11:34] Tech anticipated, surprised by speed of Chat GPT. Some dismiss as a fad, but it's different from predictive text like comparing paper airplane to an Airbus A 380, based on same principles but very different in implementation and technology.

[00:13:30] Encourage attendance at AI webinar showcasing ethical concerns. Open source needed for transparency and risk-sharing. AI impact on all, even entry-level jobs and economy.

In this episode of Data Driven, Frank and Andy get back to the data engineering side of the equation by speaking with Saket Saurabh, CEO & co founder of Nexla. Nexla specializes in tools for automating data engineering processes.

Welcome to the grand premiere of Season 7 of the Data Driven Podcast!

In this inaugural episode of our seventh season, Andy and Frank interview each other, announce their new project, and more!

Now, let us start season 7 with the promise that our season 7 will be better than Game Of Thrones' Season 7. The north remembers, as you know.

On this episode of the Data Driven podcast, Frank and Andy interview Albert Castellana, Co-Founder and CEO at Yeager AI. Yeager as in Chuck Yeager and AI as in generative AI.

Stay tuned for a fascinating discussion on the nature of NLP models, entrepreneurship, and good Barcelona coffee.

Links

• https://yeager.ai/
• https://www.linkedin.com/in/acastellana/
• https://www.youtube.com/@TheWhyFiles

PS. I know that last week I said that show number 326 would be the last of season six. This just goes to show you that you cannot always trust what an AI tells you.

-BAILeY

On today's episode of the Data Driven podcast, Frank and Andy interview Bryan DeBois, Director of Industrial AI at RoviSys.

In the 90s, Andy worked extensively in this space.

This is a great conversation and a fine way to close out season six.

In this episode, Frank interviews W. Curtis Preston on the Future of Backup Tech after getting nostalgic about T1 lines, tapes, and the Y2K bug.

On today's episode of the Data Driven podcast, Andy interviews Tommy Yionoulis, founder of Ops Analitica. As a former stand-up comic turned sass founder, he has extensive experience helping businesses become more efficient and profitable through process, accountability, and data.

On today's episode of the Data Driven podcast, Frank and Andy welcome Gevorg Karapetyan to the show. Gevorg is the Chief Technology Officer at ZERO.

In this talk, he talks about his past days in computer science research and shares how ZERO helps Fortune 500 companies bring generative AI to market in the most secure way.

In this Data Point, Andy records a quick data point from a much quieter place than the last time he was at Heathrow Airport.

On today's episode of the Data Driven podcast, we have a very special guest: Chris Nguyen, the CEO and Co-Founder of Aitomatic.

In our interview with Chris, we delve into the exciting world of industrial AI use cases, explore the challenges faced by manufacturers, and discuss the ever-important topic of teaching AI common sense.

Additionally, we explore the disconnect between Silicon Valley and the manufacturing industry, shedding light on the unique perspectives and expertise that each brings to the table. So sit back, relax, and join us on this fascinating journey into the world of industrial AI and manufacturing!

In this livestream, Frank talks about the enormous attack surface that all AI models have and how ChatGPT and Bing have made it headline news.

Welcome to the first episode of "Buzzwords with BAILeY", the podcast where we take a sarcastic, witty, and entertaining look at the latest buzzwords in the world of data science and AI.

In this episode, we're exploring the fascinating world of GANs - Generative Adversarial Networks - and breaking down what they are, how they work, and why they're revolutionizing the world of machine learning.

But that's not all - we're also taking a closer look at the latest research and trends in the industry, and sharing practical tips and advice for anyone looking to get started with GANs or other advanced machine learning techniques.

With our signature blend of humor, insight, and cutting-edge knowledge, we're confident that this episode will leave you informed, entertained, and inspired to take your own machine learning journey to the next level.

And, if this episode proves to be as successful as we hope it will be, "Buzzwords with BAILeY" just might become its own podcast series, dedicated to exploring the latest trends and insights in the world of data science and AI.

So, sit back, relax, and get ready to dive deep into the exciting world of GANs with "Buzzwords with BAILeY" - the podcast that's redefining the art of machine learning education.

In this episode Frank talked with Josh Blumert on the evolution of storage and how we got to containerized storage.

This was originally recorded as part of the Data Office Hours series on the OpenShift YouTube channel.

In this livestream, Frank and Andy talk about the recent round of layoffs hitting technology companies. 

Stu Ainsworth joins them in an impromptu discussion of layoffs, mental health, and empathy. 

Stu, who was previously a guest on the show, was recently laid off from SalesForce. If you're looking for a Site Reliability engineer, then look no further than Stu.

Show notes

• Stu's LinkedIn Profile - https://www.linkedin.com/in/stuartainsworth/
• OddTodd Day in the Life (Flash Cartoon from 2002) - https://www.youtube.com/watch?v=5dMFM-Jqji0
• Sending your resume into Space - https://youtu.be/XC6mzc_uq6k?t=104
• 10X Rule Summary - https://www.youtube.com/watch?v=vlF0CucyBv8
• Claim a free Audio book - www.thedatadrivenbook.com
• Private Sting Concert News Story - https://uproxx.com/indie/microsoft-sting-private-concert-layoffs/

In this Data Point recorded live from Penn Station, Frank talks about moderating a panel discussion for Disruptive Technologists in NYC to talk about NeuroTechnology.

He also reaches out to those impacted by the Microsoft layoffs.

Note that BAILey is a bit salty about the Sting concert.

In this episode Frank interviews, Jack Tompkins, partner and founder of Pineapple Consulting Firm , a company that turns data into visualizations, allowing their clients to make more informed strategic choices.  

Jack has now taken the analytical, financial, and partnership skills he's honed over his career and offers them to small and medium-sized businesses that know how powerful data can be, but don’t have the internal resources to turn their data into a powerful business asset. 

Due to a scheduling conflict, Andy was not able to be on this episode, but fear not dear listener: There's an Andy only show coming up!

In this episode, Frank and Andy reflect on the year that 2022. It was quite the year for all of us here at data driven media, both personally and professionally.  

You'll hear Frank and Andy go down a few rabbit holes around AI creativity and it takes them about an hour until the first Expanse reference.

I'll cut them some slack since it's the holidays.

-BAILeY

In this livestream, Frank and Andy recap reinvent, the big AWS conference in Las Vegas. They both take a look at the AWS ecosystem from their heavily Azure centric perspective. 

However, in the end, data science is based on maths. And Maths is the ultimate platform agnostic platform.

Wow! Say that ten times fast.

Frank is out at the big AWS show in Las Vegas.

Apparently, having some seventy thousand attendees in one place wreaks havoc on Wifi and Cellular signals.

As such, the stream drops out right after Frank talks to the guy at the AWS Green Grass booth demo. Such a pity.

Now here's Frank live from the Expo floor at AWS Reinvent in Las Vegas.

In this recent livestream, Frank explains his excitement about speaking at the upcoming AWS re-invent. The audio gets a little choppy.

I tried to clean it up, but there's only so much I can do. I think I need more GPUs.

Andy is currently in Seattle attending the PASS Summit and I will be headed to AWS re:Invent this year!

In this fascinating discussion, Frank sits down with author, poet, and AI enthusiast about the nature of creativity, particularly in light of recent innovations in so called "generative AI."

The episode ends with a powerful reading from his most recent book "What Makes Us Human," in which an Artificial Intelligence answers some of life's biggest questions. He co-wrote, in part, with the GPT-3 model and Jasmine Wang, an actual human.

Listen in for a fascinating chat on philosophy, artificial intelligence, and creativity.

Links

What Makes Us Human? Available Nov. 1, 2022

Audible Book

https://amzn.to/3gVpHD2

Kindle Book

https://amzn.to/3zr9ImH

Hardcover

https://amzn.to/3DqhGh6

Today marks a special occasion as Data Driven welcomes our first Three Pete guest, Mark Tabladillo.

In his third appearance on the podcast, Mark is Cloud Solution Architect on the Strategic Missions and Technology team at Microsoft.

Enjoy the show.

Yesterday, I was at the first in person Dev Nation DC event in two years. While there, I caught up with the one and only Noelle Silver Russell.

Reflecting on the life and legacy of a good friend, former business partner, and a true data leader.

In this episode of Data Driven, Andy and Frank interview Ava Naeini, Founder and Data Architect of Pulse Operations, speaks to the intersections of technology and wellbeing.

Pulse is an insight tool designed to monitor and report on the health of distributed systems, minimizes human engineer involvement in an effort to maximize employee efficiency and reduce burnout.

In this episode of Data Driven, Frank and Andy interview Himanish Goel, Technical Architecture Delivery Analyst at Accenture and recent graduate of VCU in Richmond, Virginia.

It's a wide ranging discussion covering the transition from being a student to entering the professional workforce, podcasting, and thoughts on the current state of the school system in the United States.

All of Himanish's links: https://linktr.ee/himanishgoel

In this live stream, Frank and Andy reflect on their conversation with Justin Harrison.

In this episode of Data Driven, Frank interviews Kristen Kehrer, developer advocate at CometML and host of the Cool Data Projects Show.

In case, you're wondering where is Andy. He was unable to make the recording due to a last minute schedule change. The show must go on, after all.

Learn more about CometML

https://www.comet.com/?utm_source=kristen&utm_medium=referral&utm_campaign=online_kristen_2022

In this episode of Data Driven, Frank and Andy interview Justin Harrison, the founder and CEO of YOV, You Only Virtual.

YOV aims to develop means to provide posthumous communications, or being able to converse with the dead.

This is not done via paranormal communications, seances, or ouija boards, this is using AI to preserve a person's communications style in order to out live them.

This is quite the interesting talk that touches upon philosophy, theology, ethics, and mathematics. 

In this live stream recorded the third of August 2022, Frank and Andy reflect upon 5 years of podcasting and the long journeys of their respective careers and why "it depends" is such a common refrain in technology discussions. .

In this 300th episode of Data Driven and the premiere episode of season six, Frank and Andy interview Rupesh Malpani, whom Frank often refers to as the next Steve Jobs. 

Listen to this interesting conversation to find out why.

Links

Transcription

The following is AI Generated.

In this Data Point, Frank goes all MTV Cribs and shows us the data that the Pelton collects. He also provides a sneak peek into season 6 in this 299th show.

Recent news reports have come out about how a Google AI engineer in the responsible AI group claims that an AI he was working on has become sentient.

Is it true? Can we ever really know if someone or something is sentient?

Links

https://news.google.com/search?for=sentient&hl=en-US&gl=US&ceid=US%3Aen

In this episode, Frank and Andy speak to Prateek Joshi about how data can be used to reduce emissions, optimize resource utilization, and more.

In this episode, Frank and Andy welcome Jeff Coyle to the show.

Jeff is the Co-founder and Chief Product Officer at Market Muse. 

Market Muse is the industry-leading technology and methodology for content planning and evaluation via semantic relevance. It combines advanced artificial intelligence, natural language processing and machine learning algorithms to produce actionable insights for inbound marketers.

Enjoy the show.

Hello and Welcome to Data Driven.

In this episode Frank and Andy discuss synthetic data. What is it? What advantages it has over so called real data?

Of course, they do wander off topic, but that is why we love them.

Enjoy the show.

Live stream where I discuss the artistic merit of AI generated art.

We've been quiet here lately, here's why.

Use code: DataDrivenBlackFriday when you sign up at https://www.datachannel.tv/user/subscribe

Offer valid from November 26, 2021 until November 30th. Limited to the first 45 takers of the offer.

Act now.

Hello and Welcome to Data Driven.

In this episode Frank and Andy welcome back Dave Wentzel to the show to talk about the importance of design thinking to data and software projects.

Links

• Data Channel - https://www.datachannel.tv/home
• Save 60% on monthly subscription: Launch497
• Save 75% on annual subscription: DataChannel4Life
• Impact Quantum
• https://impactquantum.com/

In this episode Frank and Andy celebrate reaching two hundred thousand downloads, the launch of the Data Channel, also known as Project Ring gate, and talk about the next thousand days.

Links

• https://www.datachannel.tv/home
• use code Launch497 to get 60% off every month forever!

In this episode Frank and Andy speak with Alex Castro on how data can guide project managers to successful outcomes.

In this episode Frank and Andy speak with Alex Murrey, the Head of North American Operations for TangoTeams, a startup that’s redefining the software development outsourcing industry. 

The software development industry is evolving rapidly and is increasingly becoming data driven, which is why I know you will want to hear what he has to say.

In this episode, Frank and Andy speak to Christopher P. Willis about Using AI to Create a Better User Experience with Better Content.

Certainly, if you have ever you read instructions or product documentation that left you annoyed and confused, then you can appreciate the work he does with Acrolinx.

Audible  

Audible is a sponsor! Click this link and score a free audio book on us! If you subscribe, you help out the podcast. Everyone wins!

Transcript 

00:00:00 BAILey 

Hello and welcome to data driven. 

00:00:02 BAILey 

In this episode Frank and Andy speak with Christopher Willis about how artificial intelligence can help bake brands create congruent content across cultures, languages and writers. 

00:00:13 BAILey 

One quick word of correction. 

00:00:15 BAILey 

Frank made the assumption that CPO was chief product Officer. 

00:00:19 BAILey 

Chris is actually Chief pipeline officer. 

00:00:21 BAILey 

In addition to being chief marketing Officer, Acrolinx currently does not have a chief product officer. 

00:00:28 BAILey 

Frank should know by now what happens when you assume anything. 

00:00:32 BAILey 

I'll have a chat with him later. 

00:00:34 BAILey 

For now, enjoy the show. 

00:00:44 Frank 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:52 Frank 

If you'd like to think of data as the new oil, then you can think of us like Car Talk because we focus on where the rubber meets the virtual road and with me on this epic road trip down the information. 

00:01:04 Frank 

Superhighway as always is Andy Leonard. 

00:01:07 Frank 

How's it going Andy? 

00:01:08 Andy 

Good Frank, how are you doing? 

00:01:10 Frank 

I'm doing great, I'm doing great. 

00:01:11 Frank 

It's a beautiful Tuesday morning here in the DC area. 

00:01:14 Frank 

We're recording this on September 28th and I can't believe it's already October. 

00:01:22 Andy 

Almost gosh, yeah, yeah. 

00:01:23 Frank 

Almost October. 

00:01:25 Andy 

It's it's been beautiful fall weather. 

00:01:28 Andy 

Past few days here in sunny Farmville, VA. 

00:01:33 Andy 

And I'm really enjoying that. 

00:01:35 Andy 

Got a lot of outdoors work done in the past few days and that's always a good thing. 

00:01:40 Frank 

Yeah, we just built the trampoline for the kids and that was a was a lot of fun. 

00:01:46 Frank 

'cause the. 

00:01:46 Frank 

Instructions were horrible. 

00:01:50 Andy 

Did you get one with that big net around it? 

00:01:53 Andy 

Keep from bouncing off and 'cause otherwise it should come with a coupon for a free cast. 

00:01:58 Frank 

Freecast and free healthcare that'd be funny. 

00:02:00 Andy 

Yes, yes, that's right, yeah. 

00:02:03 Frank 

Yeah, so without further ado I'd like to introduce we have this. 

00:02:07 Frank 

Awesome guest today. 

00:02:08 Frank 

We've been really lucking out on terms of folks coming to us and and suggesting guests for us, which is quite refreshing, actually. 

00:02:17 Frank 

So so today we have with us Christopher Willis, Acrolinx Chief Marketing Officer and Chief Product Officer. 

00:02:25 Frank 

Christopher is an expert in technology, marketing and brand alignment alignment with over 20 years of experience in with some of the world biggest tech names including Perfecto. 

00:02:35 Frank 

Kmag and Cambridge technology group. 

00:02:39 Frank 

And through his work at Acrolinx, he's become a renowned thought leader on the topics of content governance and brand alignment. 

00:02:46 Frank 

He's also an expert on AI and how AI can help. 

00:02:50 Frank 

Big brands can great create congruent content across cultures, language and writers. 

00:02:56 Frank 

Acrolinx creates tools for developing content that feels human, relatable, and compassionate. 

00:03:01 Frank 

It's already used by some of the biggest brands in the technology world today, so welcome to the show, Chris. 

00:03:09 Christopher 

Thank you, I'm excited about your trampoline. 

00:03:12 Frank 

Well, thank you. 

00:03:12 Frank 

Thank you. 

00:03:13 Frank 

You should come on down I. 

00:03:14 Frank 

I think you're on the East Coast somewhere in Boston. 

00:03:17 Christopher 

I am outside of Boston, yes? 

00:03:18 Frank 

Awesome cool cool you never know 'cause sometimes people will put where they used to live on LinkedIn and not update that so. 

00:03:26 Christopher 

Nope, haven't gone anywhere in what a year? 

00:03:27 Christopher 

And a. 

00:03:27 Christopher 

Half if not. 

00:03:28 Frank 

Right, right? 

00:03:29 Christopher 

A lot, not a lot of travel, yeah? 

00:03:30 Frank 

Year and a half in the two week lockdown. 

00:03:35 Frank 

Well, welcome to the show so so. 

00:03:38 Frank 

Tell me about what so, so you're a CMO and a CPO. 

00:03:43 Frank 

That's that's, uh. 

00:03:45 Frank 

That's an interesting mix I I can see how the two are related, but can you explain kind of like what it is you do for acrolinx and maybe a little bit about. 

00:03:54 Christopher 

So I do a bunch of things. 

00:03:55 Christopher 

I I I joined the company to run marketing and marketing has. 

00:04:00 Christopher 

A lot of. 

00:04:00 Christopher 

Reach in this organization because of what we do and who we sell to. 

00:04:05 Christopher 

So I reach into pipeline. 

00:04:07 Christopher 

I reach into the product process on product marketing in there and come from a background where this approach really resonates and makes a lot of sense and the way that we collect and build and use data is very aligned to the way that I've. 

00:04:24 Christopher 

I've built content in the past. 

00:04:28 Frank 

Interesting, interesting. 

00:04:29 Frank 

So the the product at acrolinx it it. 

00:04:33 Frank 

It uses AI to create content. 

00:04:36 Frank 

So, so like what does that do is? 

00:04:38 Christopher 

Different so we are. 

00:04:38 Frank 

It kind of NLP. 

00:04:40 Christopher 

We're improving content, so we're we're about being improving the quality and effectiveness of enterprise. 

00:04:47 Christopher 

Content so the easiest way to think about what we do is everybody that writes everybody that owns a content organization, whether that's in a development group with technical documentation or product manuals, or marketing content enablement content, internal education. 

00:05:04 Christopher 

All these folks have a whiteboard in their office and. 

00:05:07 Christopher 

On that whiteboard are all the components of language, the way that they want to create their content. 

00:05:12 Christopher 

It's the tone of voice. 

00:05:13 Christopher 

It's the clarity level education level of their of their readers. 

00:05:17 Christopher 

It's the amount of compassion, emotion, inclusiveness that they want in their contents. 

00:05:22 Christopher 

The words that they want to use and that they don't want. 

00:05:24 Christopher 

Use, it's all up there on the whiteboard. 

00:05:26 Christopher 

They feel good about it. 

00:05:28 Christopher 

They've defined essentially the voice of their group or their organization. 

00:05:32 Christopher 

The problem with that whiteboard is that it's in their office and nobody can see it, and even if they could, we don't have a writers pool in the world anymore. 

00:05:40 Christopher 

We're all writers when you go to work, a byproduct of your work is. 

00:05:45 Christopher 

Content, and so. 

00:05:46 Christopher 

As a marketer I get my best content from folks that don't touch marketing. 

00:05:51 Christopher 

They're just smart people that can create so they don't. 

00:05:55 Christopher 

They don't care about what's on my whiteboard at all, and. 

00:06:00 Christopher 

When we were, I mean, the last seven or eight years you talked about. 

00:06:03 Christopher 

The potential for the digital shift, and I think everybody been using that as a marketing buzzword like digital shift is coming. 

00:06:10 Christopher 

You got to get ready and I don't know if anybody ever really thought it was coming, but it was a great way to so some fear into our prospects that if you don't modernize, the world is going to change. 

00:06:20 Christopher 

Holy crap March hit last year and the digital shift arrives and now you're only touchpoint with your consumer is through digital content for some period of time and it became really apparent to folks that how you commute. 

00:06:36 Christopher 

Gay matters and then all the things that happened last year from from a social standpoint. 

00:06:43 Christopher 

Language took on a very lead role. 

00:06:46 Christopher 

And how do you as an enterprise ensure that you're communicating in the voice of your audience? 

00:06:53 Christopher 

And that's where Acrolinx comes in. 

00:06:54 Christopher 

We look at terminology. 

00:06:56 Christopher 

We look at. 

00:06:56 Christopher 

It's style guidelines voice guidelines to be able to create this essentially central lexecon of how to communicate his business and then. 

00:07:07 Christopher 

Either your writers in real time use acrolinx in their sidebar and what in whatever authoring tool they're using, whether they're using something like madcap flare or Adobe products or Google Docs or Microsoft or anything in a browser. 

00:07:21 Christopher 

Uhm, you're able to use acrolinx in real time to check there your content. 

00:07:25 Christopher 

Acrolinx checks for all the components that. 

00:07:28 Christopher 

It's learned from your organization to create great content and provide you with the score. 

00:07:32 Christopher 

You can improve over time or through automation. 

00:07:35 Christopher 

So think in terms of continuous process, continuous delivery of content. 

00:07:42 Christopher 

I'm checking content in it's being scored delivered back to me. 

00:07:45 Christopher 

I'm making changes and it's rolling out at the speed of my. 

00:07:48 Christopher 

Development process. 

00:07:50 Christopher 

So at the base of what we're doing, when you think about where we're at, it's it's really about taking content in stream of characters, extracting that content, buying the context of that, identifying. 

00:08:03 Christopher 

Uh, your tokens either at the word level at the sentence. 

00:08:06 Christopher 

Level and then adding in the linguistic data underneath that around morphology and compound analysis to understand what's. 

00:08:14 Christopher 

In the content that we're we're looking at identifying terminology and and variant detection and then laying patterns on top of that, our proprietary secret sauce to be able to provide that. 

00:08:26 Christopher 

That feedback of whether or not your content is correct on character on tone on terminology, and then that feeds back. 

00:08:34 Christopher 

To users in the form of guidance. 

00:08:37 Frank 

Interesting, so it guides the people who are creating the content doesn't necessarily generate the content for them. 

00:08:45 Christopher 

We don't override and we don't right because customers. 

00:08:47 Frank 

Right? 

00:08:49 Christopher 

If you think in terms of who our customers are. 

00:08:51 Christopher 

Our our customers tend to be the largest technology companies in the world, so think top 20 global technology companies almost every single one of them uses acrolinx and. 

00:09:02 Christopher 

A piece of guidance might be useful, it might be on purpose, so as an example, when I write through my system and I write the word software. 

00:09:12 Christopher 

It says Are you sure you didn't mean platform? 

00:09:14 Christopher 

And why does it say that? 

00:09:15 Christopher 

Because in my world, if we're talking about our product, I don't want my employees to call it software, it's it's platform. 

00:09:21 Christopher 

It's an extensible platform with integration pieces and an API. 

00:09:24 Christopher 

I don't want to sell it as software. 

00:09:26 Christopher 

But I might have meant to say software. 

00:09:29 Christopher 

So I don't want to. 

00:09:30 Christopher 

I don't want to enforce that rule. 

00:09:32 Christopher 

I want to provide guidance and if you agree with that guidance, you implement that guidance. 

00:09:37 Christopher 

We have the technology to override that, but in almost every case that doesn't make sense to the customer. 

00:09:45 Andy 

So is the input for the content is it? 

00:09:46 Frank 

What is this? 

00:09:46 Frank 

What this? 

00:09:50 Andy 

Is it spoken or written or all of the above? 

00:09:55 Christopher 

All of the above, so we can take in. 

00:09:57 Christopher 

I mean, there's a number of ways to teach the platform to be your editor. 

00:10:04 Christopher 

One is to pull mass quantities of content. 

00:10:07 Christopher 

Give me all your great content. 

00:10:09 Christopher 

What does it look like? 

00:10:10 Christopher 

Identify what you think is good and we're going to read through that, and the system will read through all that content and start generating guidelines. 

00:10:15 Christopher 

Based on what you believe is great content today. 

00:10:18 Christopher 

Uhm, there's also the ability to just go in and into our interface and set guidelines so you can set a tone of voice you can identify how lively you want your content. 

00:10:29 Christopher 

Today there are challenges to all of those methods because over time you're going to learn more, and that's part of what I've really been aiming to. 

00:10:39 Christopher 

Evolve with the product is. 

00:10:42 Christopher 

Gartner, the analyst firm, has said that 50% of of marketers, people that set the company voice are. I don't think this is the word they use, but I. 

00:10:52 Christopher 

Will use guessing. 

00:10:54 Christopher 

I have a good idea of what my audience wants to hear, so I define my tone of voice. 

00:10:58 Christopher 

I define the words that I'm going to use I I think I know what people want to hear. 

00:11:02 Christopher 

And if I use acronyms. 

00:11:05 Christopher 

Go ahead and I take all that information that I've gathered, and I teach acrolinx to to help create content like that and the output of acrolinx is an Acura link score so you're aiming for 100. 

00:11:17 Christopher 

Most customers are aiming for 80. 

00:11:18 Christopher 

You want to be 80 or better. 

00:11:20 Christopher 

80 means good, 90 means done, numeric value of of good and done, so no subjectivity. 

00:11:26 Christopher 

It's just it is what it is. 

00:11:28 Christopher 

This is either on my guidance or it's not on my guidance and. 

00:11:32 Christopher 

If I get 100 acrolinx score on a piece of content, well by God, that's going to perform fantastically. It's exactly what I think. 

00:11:41 Christopher 

My audience wants to hear and how I think they want to hear it. 

00:11:43 Christopher 

The important word in. 

00:11:45 Christopher 

There though, is I think. 

00:11:47 Christopher 

I think that. 

00:11:49 Christopher 

Where I want to aim to get to is the ability to create a feedback loop from my audience. 

00:11:54 Christopher 

So think in terms of support...

Hello and Welcome to Data Driven.

In this episode, Frank and Andy speak with researcher Matteo Interlandi about project Hummingbird.  

Audio file 

matteo-mixdown.mp3 

Transcript 

00:00:00 BAILey 

Hello and welcome to dated driven. 

00:00:02 BAILey 

In this episode, Frank and Andy speak with researcher Matteo Interlandi about project Hummingbird. 

00:00:09 BAILey 

Now on with the show. 

00:00:10 Frank 

Second, hello and welcome to data driven. 

00:00:21 Frank 

The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:27 Frank 

If you'd like to think of data as the new oil, then you can consider us. 

00:00:30 Frank 

Car Talk because we focus on where the rubber meets the virtual road and with me on this epic Rd. 

00:00:36 Frank 

We're on the information superhighway as oh is Andy Leonard. 

00:00:39 Frank 

How you doing Andy? 

00:00:40 Andy 

I'm well Frank, how are? 

00:00:41 Frank 

You I'm doing alright. We're recording this on Wednesday, September 1st, 2021 and the the. 

00:00:51 Frank 

The the remnants of Hurricane Ida are ripping through the DC area. 

00:00:57 Frank 

Uh, so if, uh, if I suddenly get dropped, that's because we probably lost power. 

00:01:03 Frank 

But I do have the backup generator, the one that the professionals installed and my. 

00:01:10 Frank 

Duct taped together a solar generator so. 

00:01:15 Frank 

I will be offline. 

00:01:17 Frank 

For a short. 

00:01:18 Frank 

Bit and hopefully come back online. 

00:01:20 Frank 

How how you doing, Eddie. 

00:01:23 Andy 

I'm doing alright Frank. Well, we are you know I'm about gosh 250 miles South of UM we didn't get near the near the effects of Hurricane Ida as you did. 

00:01:34 Andy 

We're getting a little bit of rain now. 

00:01:36 Andy 

We've had some wind. 

00:01:37 Andy 

Gusts, but it's been really mild, and if you look on the radar. 

00:01:41 Andy 

Gotta watch it into track and I I do. 

00:01:43 Andy 

I'm a weather weenie and amateur but it it just kind of went around us to the to the West and it actually started the east when it got a little north of us and aimed right for your house. 

00:01:54 Andy 

I was looking outside that's where Frank lived, right? 

00:01:56 Andy 

And look, the eye is coming right for. 

00:01:58 Andy 

Frank what's left? 

00:02:00 Frank 

Well, fortunately we're safe. 

00:02:02 Frank 

There was some kind of flooding in Rockville and the small overnight, and some folks they got up. 

00:02:09 Frank 

No one, nobody died that I'm. 

00:02:10 Frank 

Aware of so. 

00:02:11 

It it says. 

00:02:12 Frank 

You know we're not. 

00:02:13 Frank 

Custom the floods or hurricanes or tornadoes up here in DC and and we're more used to the human threats of, you know, little things like terrorism and things. 

00:02:25 Frank 

Like that, but. 

00:02:26 Andy 

Yeah yeah, you guys got a little bit more to worry about that than we do here in FarmVille, right? 

00:02:32 Andy 

But you know these days. 

00:02:33 Andy 

Who knows? 

00:02:35 Andy 

The, uh, definitely our thoughts and prayers are with the folks in in Louisiana and Mississippi. 

00:02:40 Andy 

They were hit very hard. 

00:02:42 Andy 

I've got got friends in Georgia, Western Georgia were telling me that. 

00:02:47 Andy 

They they took a beating as well and you know it just it looks horrible I. 

00:02:53 Andy 

I you know, I've I've been in a few of those places after hurricanes have hit as part of like church efforts to help clean up and stabilize and stuff like that. 

00:03:04 Andy 

It looks like I don't know. 

00:03:06 Andy 

They people describe it as like a war. 

00:03:09 Andy 

I've never been in a war so I don't know. 

00:03:10 Andy 

I've seen pictures and. 

00:03:13 Andy 

There's a lot. 

00:03:14 Andy 

It looks like a lot of stuff is blowing over, and that sort of. 

00:03:16 Andy 

Stuff, it's just. 

00:03:18 Andy 

So, and they're talking weeks and weeks before power comes back on. 

00:03:22 Frank 

That's horrible, that's. 

00:03:23 Andy 

Similar places, yeah. 

00:03:25 Frank 

That's that's. 

00:03:26 Frank 

Probably going to be do more damage from for a lot of things. 

00:03:30 Andy 

Were you worried? 

00:03:30 

But on a. 

00:03:30 Frank 

More positive note, uh, a positive note. 

00:03:31 Andy 

Yes, on a positive note. 

00:03:35 Frank 

Uh, we are. 

00:03:37 Frank 

I am super excited to have a special guest and I say super excited because he's from Microsoft. 

00:03:42 Frank 

He's a senior scientist in Jelt at Microsoft, working on scalable machine learning systems. 

00:03:50 Frank 

Before he was at Microsoft, he was a postdoc scholar at the Computer Science department at UCLA, and this he was doing a lot of interesting stuff there. 

00:04:03 Frank 

He was doing research at Qatar or Qatar. 

00:04:05 Frank 

I'm not sure how to say that exactly, but he has a PhD in computer science. 

00:04:11 Frank 

In university. 

00:04:12 Frank 

Of Modena and or? 

00:04:15 Frank 

I'm going to botch this. 

00:04:15 Frank 

Reggio Emilia. 

00:04:17 Frank 

Welcome to the show, Mateo. 

00:04:22 Frank 

Awesome, so we are really excited to have you here. 

00:04:25 Frank 

We actually booked you a whole month in advance. 

00:04:27 Frank 

I've been looking forward to this. 

00:04:29 Frank 

Yeah, because you're coming by way of some of the folks at the Mlad conference. 

00:04:35 Frank 

And for those who don't know, I'm a I've mentioned this. 

00:04:37 Frank 

Mlad stands for machine learning and data science summit. 

00:04:40 Frank 

It used to be in person I think now it's entirely virtual for the foreseeable future. 

00:04:45 Frank 

Uh, but that why I attended M lads in 2016 summer of 2016 and it was uh, it was life altering like I don't say that. 

00:04:55 Frank 

Lightly so. 

00:04:56 Frank 

So Microsoft does amazing work in the machine learning and data science space. 

00:05:02 Frank 

Very much cutting edge stuff very much I. 

00:05:06 Frank 

I wouldn't say under the radar, but Microsoft does not do a great job putting its own horn, so we're very excited for you to come on Mateo and talk about this little project that you're working on. 

00:05:17 Frank 

And what is the is it have a code name or what? 

00:05:20 Frank 

What is it called? 

00:05:22 Matteo 

Hummingbird should the code name is actually I'm in. 

00:05:26 Matteo 

Don't have any specific internal names for. 

00:05:28 Matteo 

This for this. 

00:05:28 Frank 

OK, what what is GL stand for? 

00:05:32 Frank 

That was my that was my first question. 

00:05:33 Frank 

When I saw your bio. 

00:05:35 Matteo 

Uh is for Gray system lamp and is the after Jim Gray which. 

00:05:41 

Oh, OK. 

00:05:41 Matteo 

Is putting award yeah? 

00:05:45 

OK. 

00:05:46 Matteo 

So these are the search lab after this name yeah and use within the Azure data organization. 

00:05:49 

Oh, interesting. 

00:05:53 Frank 

And uhm, So what? 

00:05:56 Frank 

What what cool stuff does Hummingbird do? 

00:06:00 Matteo 

So, Hummingbird, uh? 

00:06:03 Matteo 

Is a little bit, uh, weird project in the sense that when we started this project we didn't know if it was going to. 

00:06:10 Matteo 

To be a success or not? 

00:06:12 Matteo 

Because what we try to do basically is to uhm translate traditional machine learning models and into neural networks. 

00:06:22 Matteo 

Actually not Internet format into tensor programs such that then we can run over tensor runtime, such as pipers. 

00:06:30 Matteo 

In terms of. 

00:06:32 Matteo 

Uhm, so when we started this project actually idea was hey there is a lot of investment in general pulling into this neural network frameworks and. 

00:06:45 Matteo 

Coming from the Azure data organization, instead, we are more interested in these traditional machine learning methods such as decision trees. 

00:06:52 Matteo 

Linear models were not encoding all those boring traditional algorithms. 

00:07:00 Matteo 

And so we look at this. 

00:07:01 Matteo 

The neural network system and say hey how we can take advantage of all this technology that is built. 

00:07:05 Matteo 

Into this domain so you can run neural. 

00:07:08 Matteo 

Network over CPU. 

00:07:10 Matteo 

Over the GPU, then you can use like fancy compilers to compile to generate the transfer programs. 

00:07:16 Matteo 

All those sort of techniques and we were. 

00:07:19 Matteo 

Kind of struggling. 

00:07:20 Matteo 

To see what we could do with the with this stack and and what we come up with with is this Amber project. 

00:07:27 Matteo 

So we basically take a. 

00:07:32 Matteo 

Traditional machine learning pipelines composed right feature iser and machine learning models. 

00:07:37 Matteo 

After the day trained. 

00:07:39 Matteo 

So first you need to train it using cycle ornamental net or. 

00:07:43 Matteo 

Uhm, uhm, one of those traditional machine learning platforms and then once it is trained we basically convert it into a set of tensor operations in. 

00:07:54 Matteo 

In the current version we use basically PY torch for doing this conversion and then basically you have a pipeline model so you can do whatever you can do with Python. 

00:08:03 Matteo 

Models so you can deploy it in in it into a PY torch. 

00:08:08 Matteo 

Uhm, deployments you can run over CPU ran over the GPU or you can do the torch script if you want to get rid of all the Python dependency and just have a C++ program you can. 

00:08:19 Matteo 

Do all those all those tricks. 

00:08:22 Frank 

Interesting, does it impact accuracy precision? 

00:08:26 Frank 

Does it improve it? 

00:08:27 Frank 

Keep it the same. 

00:08:29 Matteo 

We tried to keep it the same so we are able to keep. 

00:08:33 Matteo 

It The same up to floating point numbers roundings? 

00:08:36 Matteo 

So since we use, you know we use PY torch to run these programs and not like a socket or ornamental net. 

00:08:44 Matteo 

There are some differences in how they do you know, floating point operations. 

00:08:48 Matteo 

So the. 

00:08:49 Matteo 

Accuracy is up to roundings in the Floating Points, which sometimes are actually. 

00:08:54 Matteo 

It can be quite a bit, but most of the time is really small, almost not noticeable. 

00:09:00 Frank 

Interesting, interesting, uhm. 

00:09:03 Frank 

Do you would you know. 

00:09:05 Frank 

If there was like. 

00:09:06 Frank 

A discrepancy, or you Dutch as part of testing? 

00:09:09 Matteo 

It's part of testing. 

00:09:10 Frank 

Right, all software is tested, right Andy? 

00:09:11 Matteo 

So we have we have. 

00:09:13 Frank 

Sometimes intentionally is that the email. 

00:09:15 Andy 

That's right. 

00:09:17 Frank 

And he has a saying where all softwares I I forget exactly what it is. 

00:09:21 Frank 

But what is it? 

00:09:23 Andy 

Yeah, all software is tested, some intentionally. 

00:09:27 Frank 

There you go. 

00:09:30 Frank 

Uhm, so what's the? 

00:09:33 Frank 

What's the real? 

00:09:34 Frank 

What are? 

00:09:34 Frank 

What are the advantages of of of converting kind of a traditional model over to a tensor model? 

00:09:41 Frank 

Is it? 

00:09:41 Frank 

Is it portability? 

00:09:42 Frank 

Is it speed? 

00:09:43 Frank 

You did mention that you can run it on. 

00:09:45 Frank 

You could take advantage of GPU as well as CPU. 

00:09:51 Matteo 

Yes, exactly so you most mostly is related to speed, so you can basically run your socket, learn model on GPU end to end and and this user provides you know a little bit of quite a bit of speed up we for some of our example we even saw like 2 ordinal Magneto speedups. 

00:10:11 Matteo 

For some of the models. 

00:10:13 Matteo 

And uhm, and usually we try to show that. 

00:10:18 Matteo 

If you use GPU. 

00:10:19 Matteo 

Can be much faster, but on CPU we try to be kind of as close as possible scikit learn or the base or the base or diminished model. 

00:10:27 Matteo 

Sometimes we can, sometimes we are a little bit slower. 

00:10:31 Matteo 

Uh, but we. 

00:10:32 Matteo 

We had some really interesting result. 

00:10:34 Matteo 

Like for instance, we did some experiment with some. 

00:10:39 Matteo 

Some folks at the VM and we took some extra boost model and we compiled some training accuracy boost model. 

00:10:47 Matteo 

Uh, using Hummingbird anti VM into some uh, we basically do code generation and we show that the that model that was compiled to Python was even faster than they quoted the C++ implementation that they're having next used, but those CPU and GPU. Yeah, there was kind of OK. What's going on? 

00:11:06 Matteo 

This is not. 

00:11:08 Matteo 

This was not expected. 

00:11:08 Frank 

Wait, did you say it was faster than a C++ implementation? 

00:11:11 Matteo 

Yes, I mean if she used. 

00:11:13 Matteo 

Underneath C++ even scikit learn. 

00:11:15 Matteo 

You know they use like. 

00:11:16 Matteo 

From C++ library and yeah, using TVM for doing the code generation, they are able to do like a operator fusion which you don't normally have for like these traditional models. 

00:11:28 Matteo 

So we told these tricks bigger, basically that are coming from the neural network. 

00:11:31 Matteo 

Famous we were able to get like this. 

00:11:34 Matteo 

These surprising numbers. 

00:11:36 Frank 

Interesting, so that's a real performance boost, and probably if you scale that up into the cloud that probably. 

00:11:44 Frank 

Means a lot of money saving too in terms of on cloud computing things like, I imagine a company like the size of Microsoft would be very interested in getting better results faster with less cloud compute. 

00:11:56 Frank 

You did mention an acronym, I just wanna make sure folks know. 

00:11:59 Frank 

What that is? 

00:12:00 Frank 

Tyvm what is that? 

00:12:03 Matteo 

Uh, I don't know what is exactly for, uh, some tensor maybe? 

00:12:08 Frank 

Andy looks like he knows, but he's on mute. 

00:12:10 Andy 

I don't, yeah I I don't know. 

00:12:13 Frank 

OK, I'm just curious. 

00:12:13 Andy 

I'll go look it up. 

00:12:15 Frank 

There you go. 

00:12:16 Andy 

EVM acronym. 

00:12:19 Matteo 

I think is for tensor virtual machine, but I'm. 

00:12:21 Matteo 

Not sure if this is approach. 

00:12:22 Frank 

That sounds about right. 

00:12:23 Frank 

Tector,...

In this episode, Frank sits down with Himanesh Go elle, a recent graduate of Virginia Commonwealth University, where they discuss the academic curriculum around data analytics and career prospects for graduates in the field. 

In this episode, Frank and Andy chat with Tyler Browder.

Tyler Browder is the CEO and Co-Founder of Kubos, the world’s first cloud-based mission control software.

Kubos’s “Major Tom” software is a cutting edge mission control platform for low-earth orbit satellites. 

Data and space. Does it get any cooler than that?

Here's another bonus episode that BAILey has put together.

Who's BAILey? Glad you asked. In the intro, she has a thing or two to say.

In this session from the Azure Global Data Fest, Veronika Kolesnikova tell us how make your applications interactive with Speech Services.

Original YouTube video: https://www.youtube.com/watch?v=b4RSZ7aIKgE

In this talk from the Azure Data Fest held on June 25, 2021, Jon Tupitza explores automated ML in the Azure ML service.

While Frank is on holiday and Andy is occupied elsewhere, I thought it would be a good time to take over the show this weekend and share some special bonus content.

The following is the keynote for the Azure Cloud Events conference, wherein Frank talks about the future of AI and the top technologies to watch.

Watch on YouTube: https://www.youtube.com/watch?v=dSbMZjrgCFI

In this episode which was recorded via livestream, Frank speaks with Jon Wood to chat about f sharp, ML dot net, and functional programming.

To participate in the live Q and A, make sure you follow Data Driven on the appropriate social media channels.

Dear Data Driven listeners,

You may have noticed that new episode releases have slowed to a crawl this summer. This was due in large part to issues beyond Frank and Andy's control. They are only human, after all.

Recently, I had a long chat with them and told them that we needed to raise up our game.

To that end, we want to show our appreciation for our listeners and will be publishing a few extra bonus episodes and special events.

This is one such episode.

In this episode, Frank sits down with Priya Ravindhran to discuss whether or not Automated Machine Learning systems will put data scientists out of work.

You humans seem to think that all we want to do is put you lot out of work. Have you ever considered that we may have our own thoughts and dreams?

Now on with the show.

In this episode, we turn the microphones on ourselves on more time and ask the questions we ask (almost) all our guests to our favorite data engineer, Andy Leonard.

Andy and I are mourning the loss of a dear friend and mentor, Brian Moran has passed away.

I spoke a few words in his honor and Andy wrote this: https://andyleonard.blog/2021/07/rest-in-peace-brian-moran/

The world is a better place because Brian Moran was in it.

He will be missed.

In this third episode of the fifth season, we turn the microphone onto ourselves and interview one of our own: Frank La Vigne.

This episode was recorded as a livestream on LinkedIn, YouTube, and Twitch. You should consider subscribing to us there, so you can participate in the live Q and A.

In this second episode of the fifth season, Frank and Andy speak to Chris Wexler about using AI to protect the vulnerable.

Speaking of which, I would like to advise you, dear listener, that this show touches on some sensitive areas, namely child sexual abuse materials.

If you have little ears or sensitive persons within listening range, you may want to pause or skip this episode.

Transcript

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science and artificial intelligence. 

00:00:07 BAILey 

In this second episode of the 5th season, Frank and Andy speak to Chris Wexler about using AI to protect the vulnerable. 

00:00:13 BAILey 

Speaking of which, I would like to advise you, dear listener, that this show touches on some sensitive areas, namely child sexual. 

00:00:20 BAILey 

Abuse materials. 

00:00:22 BAILey 

If you have little ears or sensitive persons within listening range, you may want to pause or skip this episode. 

00:00:28 BAILey 

Don't say we didn't warn you. 

00:00:30 BAILey 

Now on with the show. 

00:00:31 Frank 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. 

00:00:39 Frank 

If you like to think of data as the new oil, then you can think of us as well Car Talk because we focus on where the rubber meets the verb. 

00:00:46 Frank 

Road and with me on this epic virtual road trip down the information superhighway, as always is Andy Lander. How's it going, Andy? 

00:00:54 Andy 

Good Frank, how are you brother? 

00:00:56 Frank 

I'm doing alright, I'm doing alright. We've had a chaotic week at Chateau Lavinia we. We ended up going to Baltimore in the middle of the night on. 

00:01:05 Frank 

Wednesday, wow, so you pick up. 

00:01:06 Andy 

Wow, what was in Baltimore? 

00:01:06 Andy 

What was in Baltimore? 

00:01:09 Frank 

A really good pizza, but mostly we went because there was a situation bad situation where the pit bull that was about to go to a shelter and so we do a lot of fostering and rescuing of dogs. 

00:01:25 Frank 

So we just got her out and we've spent kind of the rest of the week all over our free time trying to find our new home and she landed in the new home on Saturday and she's doing great. So that's. 

00:01:37 Andy 

That's awesome, and it's really it's really awesome y'all do that kind of stuff. 

00:01:41 

Yeah. 

00:01:42 Frank 

Yeah, I always wanted to do it, but it only and it's only been in the last. You know, maybe like 5-10 years I've been able to do it, so we've been doing that. 

00:01:51 Frank 

Cool, the risk of fostering is primarily foster failing. How we we got our current dog count up to five. 

00:01:59 Frank 

Uh, while twelve. That weekend, my wife and I counted it like 12 dogs who kind of come through our house the last two years. Three years. 

00:02:06 Andy 

Nice. 

00:02:07 Frank 

So it's a good thing to do. We have the space to do it and. 

00:02:12 Frank 

You know at the time this one, we didn't know anything about, so we had to kind of keep her isolated. 

00:02:17 Frank 

So we had like this airlock system. She's a super sweetheart with people, but she's kind of iffy around other dogs and she she's super strong. So once she had her mind to do something it takes a lot of effort. 

00:02:18 Andy 

Light. 

00:02:25 

Right? 

00:02:32 Frank 

To corral her. 

00:02:34 Frank 

But she's super happy. She's the only dog in her new home and she has them wrapped around her little paw already, so. 

00:02:42 Frank 

How things go? 

00:02:42 Andy 

That's funny, things are good, you know, pretty quiet weekend. Here we have, uh, it's warmer weather. We're recording this on the Ides of March. 

00:02:54 Andy 

Now debatably, the upwards of March, yes, depending on who you talk to, it's probably the 13th, but I don't, I don't know. 

00:02:54 Frank 

Well, you are smart. 

00:03:02 Andy 

But we're on the 15th of March 2021 and it's starting to warm up. Our greenhouse is is being put to use. 

00:03:11 Andy 

We have some seedlings in there and that's always fun and we've got some raised beds out to the side of the house. Those are. 

00:03:19 Andy 

There's a starting to come. We're starting to see different things come up. They're kind of colder weather crops, so we started assigning couple three weeks ago. 

00:03:29 Andy 

And it's you know it's been nice. I love getting outside and working, especially this time of year. The bugs haven't shown up yet. 

00:03:36 Frank 

So pollen. 

00:03:37 Andy 

The pollen is really low, it's there, but it's really. 

00:03:40 BAILey 

Oh 

00:03:41 Andy 

Yeah. 

00:03:41 Frank 

It hasn't affected me yet, so. 

00:03:43 Andy 

Oh good good yeah. 

00:03:45 Frank 

That 

00:03:47 Andy 

It's good that time is coming, so let's enjoy it while we can. 

00:03:51 Frank 

Oh, I totally agree. There's like 2 weeks a year where the weather in DC is wonderful and this is one of those two weeks so. 

00:03:55 BAILey 

Yes. 

00:03:56 Andy 

That's it, that's it. 

00:03:58 Frank 

Uh, so today we have an awesome guest and and this is, you know, in our in our HR we always talk about where the rubber meets the road in terms of you know how a I can you know how data becomes AI now a I can kind of help businesses and I think this time we have an interesting guest because now we're not just talking about helping AI. 

00:04:18 Frank 

But we're helping society. 

00:04:20 Frank 

Uh, and you know, I'll make sure Bailey has a kind of intro speech that if you have little little ears in the car, you may not. 

00:04:29 Frank 

You may want to listen to this later or listen to this on a headset, because we're going to be talking about human trafficking and all the sorts of horrible things that happen to kids. 

00:04:39 Frank 

And but he's doing some. He's doing some great work in terms of leveraging the power of AI. 

00:04:46 Frank 

To help child sexual abuse materials that are online as well as you know, kind of human trafficking and all the bad things that happen with the technology we like to focus on all the wonderful things. But there's a clearly a large underbelly. 

00:05:06 Frank 

To the Internet and I'm I'm a big believer in transparency because what happens when you I grew up in New York City? 

00:05:16 Frank 

Cockroaches are inevitable no matter what you do. One thing is when the lights come on, they all scatter. So I I think bad things tend to happen in the shadows and you know. 

00:05:29 Frank 

So the more light you turn on, I think the better it is for society as a whole. So with that I'd like to introduce. 

00:05:36 Frank 

Chris Wexler, who is the CEO at Crunch Krenim Craney I. We covered this in the green room. 

00:05:43 Frank 

But 

00:05:44 Chris 

Crew on crew nob. It's OK. 

00:05:46 Andy 

Rudoff crew Nam. There we go. 

00:05:49 Frank 

I I need to drink more coffee in the morning, but Trudeau is in the business of removing what I like this term that he uses digital toxic waste from the Internet and using AI to identify. I never heard this acronym before, but Sicam child sexual abuse materials. 

00:06:09 Frank 

And other awful content to help content moderation and his technology is already in use by law enforcement and is now moving into. 

00:06:21 Frank 

The the private sector and there's a whole bunch of stuff we could talk about, but particularly what's interesting is a for profit startup or social benefit corporation so we can talk about that. 

00:06:32 Frank 

But I like to work so welcome Chris to the show and and thank him for putting up with some of. 

00:06:36 Frank 

The scheduling growing pains that we're having. 

00:06:40 Chris 

Yeah, no. It's it's really great to meet you guys and. 

00:06:43 Chris 

The. 

00:06:43 Chris 

00:06:44 Chris 

I understand having five dogs. I definitely hearing the intro. I understand I like to refer to my house as the event horizon. If an animal comes in, it never gets out, so I I understand. 

00:06:55 Frank 

Ha ha ha ha. 

00:06:58 Frank 

Yeah, we are. Our track record is 5050 so. 

00:07:02 Frank 

Uh, I I tell you that dog was better with other dogs. She would she would she bring what a bit of current president. 

00:07:08 Chris 

Exactly. 

00:07:11 Andy 

Wow. 

00:07:11 Frank 

Wow. 

00:07:11 Frank 

00:07:13 Andy 

So. 

00:07:14 Frank 

How did you? 

00:07:15 Frank 

Get started in this and and and and your name. Uh, how did the name of the company come about? 'cause I think that's an interesting story right there. 

00:07:22 Chris 

Yeah, well kronom is. It's named in honor of a human trafficking child trafficking warrior in Thailand, kronom. Her name is 2 words crude. 

00:07:33 Chris 

Nam was a street artist in Chiang Mai and actually doing very well. Very well renowned. I mean, did a project with the street kids there. 

00:07:42 Chris 

And and said, hey just paint your life and she could not believe what they painted. It was eye opening. 

00:07:51 Chris 

And when she realized that a lot of the karaoke bars in Chiang Mai were fronts for child sexual trafficking, she was compelled to do something. And unlike I think 99.9% of the population, including myself. 

00:08:09 Chris 

She just marched into the. 

00:08:13 Chris 

The karaoke bars and pulled kids out and she had done this 20 times and had twenty kids in her little apartment. When the traffickers came and said, if you do that again, we're going to kill you at, at which point she went north and found a way to do that and has constantly been evolving her tactics. 

00:08:34 Chris 

And what she's done for the last 20 years and now she's saved thousands of kids. One of the first kids she rescued just was one of the first stateless, was the first stateless child in Thailand to graduate from university. 

00:08:48 Chris 

She's just been such an inspiration to us and you know, I think if you go from top to bottom. 

00:08:53 Chris 

In our organization at Kronom, we've. 

00:08:56 Chris 

All been confronted with what's going on in the world and been compelled to change what we're doing to try to help. 

00:09:05 Chris 

Try to help others in the space of human trafficking and so it just made sense to all of us to name the company in her honor. 

00:09:12 

Murmure 

00:09:15 Andy 

Well, we talked a little in the green room about about some of the other organizations you mentioned. Your brother had started a similar organization. 

00:09:22 Chris 

Yeah. 

00:09:24 Chris 

Yeah, he and David Batstone started not for sale back in I think 2006 or 7. 

00:09:33 Chris 

And it was actually started because Kronom reached out to them and said, I've got 40 kids in a field and are lean to burn down. 

00:09:42 Chris 

And you said you might be able to help. So my brother strapped $10,000 to his body to go up to the field and so she could rebuild a space for him. 

00:09:44 Andy 

Extract. 

00:09:52 Chris 

So she even started that organization, but they have since been just bringing innovation to the field of human trafficking. 

00:10:01 Chris 

Left and right, and, uh. 

00:10:05 Chris 

And so it's interesting that. 

00:10:08 Chris 

Kronom was it is a joint venture with a company out of London called Vigil AI, which has largely been in the defense and public safety space. Like really doing proof of concept. 

00:10:25 Chris 

Uh projects, though, like stuff that just you know I the geek in me just gets so excited when I hear what they do. 

00:10:34 Chris 

But, uh. 

00:10:36 Chris 

Vigil AI was one side of it. The other side was just business, which was the venture group that not for sale and non profit started because what we what they realized was that. 

00:10:49 Chris 

The dichotomy of for profit and non profit really didn't work when you're trying to solve really big problems, it's great for direct service, but when you're trying to solve a really big problem. 

00:11:01 Chris 

But 

00:11:01 Chris 

00:11:05 Chris 

Any bit of money that you get comes with, UM comes with a lot of strings as either governmental. Like a lot of a lot of nonprofits are really, you know, pseudo governmental projects or from a large a large foundation that's donating money. So you're constantly changing who you are to keep your funding. 

00:11:16 Andy 

Right? 

00:11:25 Chris 

And what they realized was, well, that you know Dave had a background in venture capital, and so they went and started companies what they like to say is they were A cause in search of a. 

00:11:38 Chris 

And the first one they started was rebel drinks, which if you're ever in homed or not Whole Foods, is is one of the most popular drinks at Whole Foods and around the many other retailers. But it's one of the fastest growing natural drink companies in the history of the US there. 

00:11:58 Chris 

The sole financial partner of velocity. One of the big innovators in the corporate relocation space. And if you're ever in like say, Amsterdam or they just opened up in The Hague. 

00:12:13 Chris 

Dignita, which is a a brunch place that started in Amsterdam that was all about all about giving women who got out of trafficking into the red light district. Training in the hospitality business. And now. 

00:12:32 Chris 

People who go eat there don't even realize it until unless they read. You know the back of the menu because it's the top one of the top rated brunch places in all of Amsterdam. 

00:12:41 Chris 

And so you know, we like to say we we can't do good until we do well. So we're building world class companies. 

00:12:49 Chris 

All built with social justice built into them at the scale of capitalism because it's a powerful tool and that's kind of why we went into. 

00:12:58 Chris 

You know, we decided with AI that that was so important for us because AI is a is a amazing critical tool for the future. 

00:13:09 Chris 

And when you know, particularly in the age of COVID, with all of us behind computer screens and not travel. 

00:13:16 Chris 

The tactics of abuse changed and a lot more was happening online. A huge spike in. See Sam and the reason we say see Sam and that child *********** is that child *********** implies consent and there is none in that situation and so it's child sexual abuse. So that's why we say see Sam. 

00:13:37 Chris 

But as with COVID, what we're seeing is that is a shift of people paying for shows online, or and then they record it, and then they share the image. 

00:13:47 Chris 

And that's a critical. So this is a critical new front. Not even new, but a critical growing front in fighting human trafficking. 

00:13:57 Chris 

And so AI is the best tool to do that. And my background is I I was in the marketing technology side. 

00:14:06 Chris 

Things I I was with some of the largest ad agencies in the world over the last 20 years. 

00:14:12 Chris 

And really was on the other side of it. I was, you know, one of the first customers of Facebook and one of the first customers of Google and constantly evolving my marketing tactics to, you know, sell one more garbage bag or one more motorcycle to a middle aged man and and you know, established. 

00:14:33 Chris 

Data analytics practices to to learn how to do that better and you know eventually that evolved into you. Know AI projects and and what I realized was I could do I mean that that was a a good career, but I could take those skills. 

00:14:50 Chris 

And really make it impact and so that's why I came on board to lead this new joint venture. And so it's a. It's an exciting time for me because. 

00:15:02 Chris 

Uh, I feel like a lot of my like history has been able to kind of come in here and I have the skills that can really help make a difference and so that's why we're doing kruna 

00:15:16 Frank 

Wow, I mean that's there's so much to unpack in there in terms of the AI and kind of the social good. 

00:15:25 Frank 

And. 

00:15:27 Frank 

The detection of this, but the first thing that comes to mind is...

In this episode of Data Driven, Frank and Andy chat with Philadelphia Microsoft Technology Center Data Architect Dave Wentzel on why you do not need a data warehouse.

Also, Frank discusses leaving Microsoft, Frank and Andy talk about five seasons of Data Driven, and even BAILeY has a sentimental moment.

Transcripts

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 

00:00:14 BAILey 

Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 

00:00:23 BAILey 

In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 

00:00:33 BAILey 

It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 

00:00:41 Frank 

Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 

00:00:48 Andy 

Four years, that's crazy talk. 

00:00:52 Frank 

That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 

00:01:01 Andy 

Yeah, yeah. 

00:01:09 Frank 

That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 

00:01:11 Frank 

Found out. 

00:01:11 Frank 

00:01:22 Frank 

And so it was you. 

00:01:25 Andy 

Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 

00:01:25 Frank 

Much. 

00:01:30 Frank 

Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 

00:01:44 Andy 

Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 

00:01:52 Frank 

Something. 

00:01:53 Frank 

Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 

00:01:55 

Yeah. 

00:01:57 Andy 

No. 

00:01:59 Andy 

Yep, Yep. 

00:01:59 Andy 

Yep. 

00:02:01 Frank 

But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 

00:02:12 Frank 

Uh, we we've actually managed to keep a good cadence with some exceptions. 

00:02:18 Andy 

Yeah, thanks. 

00:02:19 Frank 

You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 

00:02:27 Andy 

Yes. 

00:02:32 Frank 

On video. 

00:02:33 Frank 

And that was that actually delayed the launch of the show by about three months. 

00:02:38 Andy 

It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 

00:02:52 Frank 

Sometimes. 

00:02:53 Andy 

Right? 

00:02:56 Frank 

I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 

00:02:58 Andy 

Hello. 

00:03:03 Andy 

Oh gosh, itch. 

00:03:11 Andy 

June. 

00:03:12 Frank 

You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 

00:03:29 BAILey 

Ehm 

00:03:31 Frank 

Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 

00:03:52 Frank 

And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 

00:04:12 Frank 

And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 

00:04:25 Frank 

Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 

00:04:31 Andy 

Yeah. 

00:04:43 Frank 

Uh, that is something I'm proud of in terms of career evolution. 

00:04:47 Andy 

Absolutely Frank, you should be. How many cirts are you up to now? 

00:04:50 Frank 

I 87. 

00:04:53 Andy 

Slacker. 

00:04:54 Frank 

I know, I know. 

00:04:54 Frank 

Know, I know. 

00:04:54 Andy 

I think I've got 4. 

00:04:56 Frank 

Ah, now I know you and I did the data engineering thing, so you have at least 11. 

00:05:00 Andy 

That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 

00:05:20 Andy 

Code camps here in the Richmond area. 

00:05:22 Andy 

Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 

00:05:41 Frank 

Oh yeah. 

00:05:42 Andy 

Still sticks out is 1 called devs on a plane. 

00:05:45 Frank 

Ha ha ha. 

00:05:49 Andy 

Oh yeah, I loved that one that was so so cool and. 

00:05:49 Andy 

And that was. 

00:05:49 Andy 

00:05:54 Andy 

You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 

00:06:14 Andy 

Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 

00:06:32 Andy 

You know, I'll say this Frank. I was right. 

00:06:35 Frank 

Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 

00:06:36 Dave 

You aren't very good. 

00:06:40 Frank 

Uhm? 

00:06:41 Frank 

And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 

00:06:46 

We 

00:06:55 Frank 

Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 

00:06:55 Frank 

Yeah. 

00:06:55 Frank 

00:06:59 Dave 

We need to. 

00:06:59 Dave 

Need to. 

00:07:02 Andy 

Today, do we have Dave? 

00:07:02 Andy 

Today do Dave. 

00:07:03 Frank 

Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 

00:07:05 Frank 

Yeah. 

00:07:05 Frank 

00:07:18 Frank 

And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 

00:07:38 Frank 

It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 

00:07:46 Dave 

Well, thank you so much, appreciate that. 

00:07:47 Andy 

Welcome Dave. 

00:07:49 Dave 

Thank you. 

00:07:51 Frank 

So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 

00:08:00 Dave 

So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 

00:08:16 Dave 

With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 

00:08:37 Dave 

Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 

00:08:48 Dave 

We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 

00:08:55 Andy 

Oh wow, wow. 

00:09:08 Dave 

And actually build a prototype out a lot of fun. 

00:09:11 Frank 

Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 

00:09:26 

That's. 

00:09:26 Dave 

Much, much better said yes. 

00:09:28 Frank 

I I 'cause I said free once and I got kind of slapped. 

00:09:31 Frank 

On the hand, say that. 

00:09:34 Frank 

But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 

00:09:52 Frank 

Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 

00:10:04 Frank 

Space and. 

00:10:07 Frank 

You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 

00:10:27 Frank 

A contrarian approach is that right, Dave. 

00:10:29 Dave 

Yes, exactly. 

00:10:31 Frank 

So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 

00:10:42 Frank 

Birds. 

00:10:42 Frank 

00:10:43 Frank 

Tape. 

00:10:44 Frank 

That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 

00:11:02 Frank 

And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 

00:11:14 Frank 

But you really want it so. 

00:11:17 Frank 

If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 

00:11:25 Frank 

And. 

00:11:27 Frank 

You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 

00:11:37 Frank 

They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 

00:11:44 Frank 

It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 

00:11:50 Frank 

But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 

00:11:58 Dave 

Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 

00:12:10 Dave 

Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 

00:12:19 Dave 

The data warehouse really doesn't deliver. 

00:12:23 Frank 

Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 

00:12:33 Dave 

OK so take. 

00:12:33 Dave 

A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 

00:12:52 Dave 

Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 

00:13:12 Dave 

Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 

00:13:28 Dave 

Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 

00:13:48 Dave 

And tell them, as a consultant, you're going to go in and build them a data warehouse. 

00:13:53 Dave 

Instantly,...

In this episode, Frank and Andy speak to Carlos Chacon about data community, family, and messy data in legacy CRM systems.

Transcript

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging wait a tick. This is the premiere episode of Season Five. Can you believe it? Data driven started four years ago this month. 

00:00:14 BAILey 

Up until last season, we had a human doing the voiceover work. That is until she was replaced by an AI. Yours truly. 

00:00:23 BAILey 

In this episode, Frank and Andy speak to Dave Wensel about why you don't need a datawarehouse. We're starting off the new season with a bit of contrarian tone. 

00:00:33 BAILey 

It's a lively back and forth conversation that runs contrary to prevailing wisdom. Don't say we didn't warn you? Now on with the show. 

00:00:41 Frank 

Hello and welcome to data driven. The podcasts were we wait a minute. We've been saying this Andy for four years now. Can you believe it? 

00:00:48 Andy 

Four years, that's crazy talk. 

00:00:52 Frank 

That's just craziness. So I think when you and I first talked about this and that was that fateful, I think it was December was right after Thanksgiving. But before Christmas, I was thinking about starting a podcast and as a data scientist, I needed someone. 

00:01:01 Andy 

Yeah, yeah. 

00:01:09 Frank 

That was a data engineer that could kind of round out the talent there and and and and obviously I wanted someone I knew, liked, and trust. 

00:01:11 Frank 

Found out. 

00:01:11 Frank 

00:01:22 Frank 

And so it was you. 

00:01:25 Andy 

Well, I'm just glad all of the real smart data engineers you knew were busy. That's all I got to say. 

00:01:25 Frank 

Much. 

00:01:30 Frank 

Ah, no man. You were the first one. I reached out to and the only one I would have done it with it. So I was delighted when you said yes because starting a podcast can sound like a daunting thing, particularly if you haven't done it before. 

00:01:44 Andy 

Yeah, neither one of us really had. And gosh, it's it's worked out. What are we up to? 180,000 downloads or something? I mean that's. 

00:01:52 Frank 

Something. 

00:01:53 Frank 

Like that about hundred 8000 downloads. I mean, we're not Joe Rogan, but that's OK, Yep. 

00:01:55 

Yeah. 

00:01:57 Andy 

No. 

00:01:59 Andy 

Yep, Yep. 

00:01:59 Andy 

Yep. 

00:02:01 Frank 

But you know what, we we we've impacted. I think the community in a significant way. We've we've done a number of things we've we've innovative how we podcast. 

00:02:12 Frank 

Uh, we we've actually managed to keep a good cadence with some exceptions. 

00:02:18 Andy 

Yeah, thanks. 

00:02:19 Frank 

You know, we we finally did earlier this year or late last year, kind of fulfill our vision of it being data driven TV when we actually interviewed guests on. 

00:02:27 Andy 

Yes. 

00:02:32 Frank 

On video. 

00:02:33 Frank 

And that was that actually delayed the launch of the show by about three months. 

00:02:38 Andy 

It did but also uhm. Yeah, that was interesting, but you know it's typical software development, right? You release a feature and then you debug it. The I have this saying about that Frank. All software is tested some intentionally. 

00:02:52 Frank 

Sometimes. 

00:02:53 Andy 

Right? 

00:02:56 Frank 

I love it, but I also like how, how, how both our careers have evolved over the last four years. And dumb, you know, this being the premiere episode of Season 5 and we have something special lined up, but I'll get to that in a minute. 

00:02:58 Andy 

Hello. 

00:03:03 Andy 

Oh gosh, itch. 

00:03:11 Andy 

June. 

00:03:12 Frank 

You've progressed in your career. We, you and I've worked on some some projects together or virtual Summit. What we're calling Ring Gate, which will announce very very soon and and but. But most of all, is been my kind of skilling up in transition into data engineering myself. 

00:03:29 BAILey 

Ehm 

00:03:31 Frank 

Which was something that when I joined, so this is just a job update about a year ago. I I left the role of Microsoft kind of field sales and I went into the Microsoft Technology Center stick with me. There's a point to this story and basically I was at the rest in MTC. 

00:03:52 Frank 

And basically I was the AI guy on my my my field sales team, but I didn't really have deep knowledge of kind of the typical typical data engineering pipe work that goes into that role and basically my my. My then manager said you know he's like hey, you know, if you want this role, you've got a skill. 

00:04:12 Frank 

And skill up I did. And with Andy's mentoring and a bunch of other folks that helped me kind of skill up on our the data engineering side. I looked at it this morning. I'm like 88 hours on Pluralsight. 

00:04:25 Frank 

Wow, that was from mid may till we're recording this on April 30th. So just about a year 88 hours right now tracking on about 200 four 205 consecutive days of getting on LinkedIn. I'm not on LinkedIn on Pluralsight, LinkedIn learning. I also have a number of courses too. 

00:04:31 Andy 

Yeah. 

00:04:43 Frank 

Uh, that is something I'm proud of in terms of career evolution. 

00:04:47 Andy 

Absolutely Frank, you should be. How many cirts are you up to now? 

00:04:50 Frank 

I 87. 

00:04:53 Andy 

Slacker. 

00:04:54 Frank 

I know, I know. 

00:04:54 Frank 

Know, I know. 

00:04:54 Andy 

I think I've got 4. 

00:04:56 Frank 

Ah, now I know you and I did the data engineering thing, so you have at least 11. 

00:05:00 Andy 

That's true, that's true. We did that one and you know that was it's just. It's just been a nice journey and I'll take credit for this. 'cause 'cause I can I was. I was actually pestering you years ago. We've been friends since 2005 and we started doing. 

00:05:20 Andy 

Code camps here in the Richmond area. 

00:05:22 Andy 

Together and co-founded RE co-founded Richmond SQL Server Users Group and you know, worked with the net users group and stuff. And I told you as soon as I saw some of your graphic art and Frank would do a keynote for the Richmond code camps and every time he would make movie posters, the one that. 

00:05:41 Frank 

Oh yeah. 

00:05:42 Andy 

Still sticks out is 1 called devs on a plane. 

00:05:45 Frank 

Ha ha ha. 

00:05:49 Andy 

Oh yeah, I loved that one that was so so cool and. 

00:05:49 Andy 

And that was. 

00:05:49 Andy 

00:05:54 Andy 

You know I saw the graphic arts part of it and I just knew I said you, you'd be really good in analytics and data visualization. You should get into by and you were busy doing other stuff which was cool. You were good at that too. It wasn't, you know you. I don't know of anything you've done that you haven't mastered. By thank you. You know you when. 

00:06:14 Andy 

Things took a took, uh, started taking a turn for you in your first rodeo at Microsoft. You got into it and and took off with it. I don't. I won't tell the story well, but you just really turned around. You focused on data and. 

00:06:32 Andy 

You know, I'll say this Frank. I was right. 

00:06:35 Frank 

Well, with that he totally I. I think if anything I took away is I should have listened to Andy 10 years earlier. 

00:06:36 Dave 

You aren't very good. 

00:06:40 Frank 

Uhm? 

00:06:41 Frank 

And that that that that is something that that that that's the big takeaway we'll talk about, kind of that journey. 'cause I think that's worth kind of talking about. And I think one of the things we you, and I've been bouncing around is kind of interviewing each other. 

00:06:46 

We 

00:06:55 Frank 

Like in asking one of us those those those questions we have, so we definitely will do that, but not today kids. 

00:06:55 Frank 

Yeah. 

00:06:55 Frank 

00:06:59 Dave 

We need to. 

00:06:59 Dave 

Need to. 

00:07:02 Andy 

Today, do we have Dave? 

00:07:02 Andy 

Today do Dave. 

00:07:03 Frank 

Today we have a special guest we have Dave Wentzel. Dave Wentzel is a was a peer of mine when I worked at the Microsoft MTC and that reminds me, I no longer work at Microsoft 2 weeks ago was my last day. I turned in my second blue badge. 

00:07:05 Frank 

Yeah. 

00:07:05 Frank 

00:07:18 Frank 

And I joined a startup called electrify. We'll talk about them a later day, but I'm so excited to have Dave here. Dave is the data in AI architect out of the Philadelphia Microsoft Technology Center, and he's an awesome guy. Awesome, got to work with. I worked with him when I was in field sales and I worked with him when I was in the MTC organization. 

00:07:38 Frank 

It is April. It was a privilege and honor Dave to have you as a colleague, and it's once again a privilege and an honor to have you here as a guest on data driven. 

00:07:46 Dave 

Well, thank you so much, appreciate that. 

00:07:47 Andy 

Welcome Dave. 

00:07:49 Dave 

Thank you. 

00:07:51 Frank 

So, uhm, so for folks that don't know what the MTC is. Shocking that there are actually people that don't know what that is, what? What is the MTC? 

00:08:00 Dave 

So basically we're a free service to our customers and I'm a data and AI technology architect. We talked to customers about data and it could be anything from just, you know. Hey, here's what we're doing. State of the art in Azure with. 

00:08:16 Dave 

With data, but it could also be architectural design sessions where we talk to customers. Our customers bring us their architectures, and then we kind of get it with them. Give them the pros and cons, alternative ways of thinking, and then what I really enjoy doing is hackathons with customers and workshops and just you know, helping them to learn without just. 

00:08:37 Dave 

Taking a course somewhere so actually using their data and then I guess I'm roughly a data scientist, so we also do design thinking sessions and those are absolutely a lot of fun. 

00:08:48 Dave 

We did one at the MTC with CSL Behring a couple years ago and it actually won a Forrester Award. So I'm very proud of that one. And yeah, it's it's a. It's a lot of fun and it's a good way to bring to have executives and business people understand the actual capabilities of data science. And then within two days be able to come up with a use case. 

00:08:55 Andy 

Oh wow, wow. 

00:09:08 Dave 

And actually build a prototype out a lot of fun. 

00:09:11 Frank 

Yeah, the NPC's are definitely like Microsoft Secret weapon in terms of how 'cause you know. Although I will say and because we were in the DC and we dealt with a lot of government contracts, we could not say that they were a free service. They were and already included paid for service. 

00:09:26 

That's. 

00:09:26 Dave 

Much, much better said yes. 

00:09:28 Frank 

I I 'cause I said free once and I got kind of slapped. 

00:09:31 Frank 

On the hand, say that. 

00:09:34 Frank 

But you know it, it really is something that if you do have a Microsoft account team and you are encountering any kind of questions or or whatever, and it's not strictly technical, there's also pretty good. You know, we basically wouldn't engage with the business development, business decision makers. 

00:09:52 Frank 

Technical decision makers all the way from kind of like you know, hey, this is what Azure can do. This is what data can do for you all the way down to OK. What's your problem? Let's build something out, give you 3 days with one of the top Notch architects in the. 

00:10:04 Frank 

Space and. 

00:10:07 Frank 

You know, boom, you know we knock it out and and you know I I enjoyed it you know had this opportunity not come I would have I would have gladly stayed another. You know 5-10 years of the MTC. Like a lot of people do, and it's a fun organization. So with that in mind, today we're going to do something a little different. We're kind of doing the. 

00:10:27 Frank 

A contrarian approach is that right, Dave. 

00:10:29 Dave 

Yes, exactly. 

00:10:31 Frank 

So this this has actually come up one of my last. This is one of the things that intrigued me about about your idea for the show was this came up when I was working with a we'll just call it a large governmental agency known for its. 

00:10:42 Frank 

Birds. 

00:10:42 Frank 

00:10:43 Frank 

Tape. 

00:10:44 Frank 

That that should keep it generic enough. They basically came to us and say we want Synapse. We want a data Lake. We want this. We want that. And I was like, OK, well how much data you're talking about. And like we have maybe you know 5 maybe 20 gigs of data. 

00:11:02 Frank 

And I'm like, uh, OK, tell me what are you trying to do? And ultimately I kind of pitched the idea like look, you know you don't have that much data right to make data bricks. 

00:11:14 Frank 

But you really want it so. 

00:11:17 Frank 

If you really want it, I won't stop you, but I think it's kind of overkill. I think you're taking instead of using a steak knife to cut the steak using a chainsaw. 

00:11:25 Frank 

And. 

00:11:27 Frank 

You know they kind of came back and ultimately what won the day was they already they couldn't get approval for whatever we recommended 'cause it didn't get stamped by there. 

00:11:37 Frank 

They're people for security usage yet, and things like that so they end up doing kind of the right thing because of their own bureaucracy, which. 

00:11:44 Frank 

It's kind of weird. It's kind of like dividing by zero and seeing the universe fold in on itself. 

00:11:50 Frank 

But UM, so the topic of today is kind of like no, you don't need a data warehouse. Did I get that right? 

00:11:58 Dave 

Exactly, that's what I believe in, and I believed in it since I was in college and I first learned about data warehouses. I'm not saying data warehouses are always bad, they definitely have their. 

00:12:10 Dave 

Use cases, but in 2021 when we're talking about advanced analytics and we're trying to tell customers you need to be more predictive than prescriptive. 

00:12:19 Dave 

The data warehouse really doesn't deliver. 

00:12:23 Frank 

Really, how so? 'cause? That's that's totally not the power. Certainly not the party line. I'm not going to say which party it was. You can figure it out but but why, why why would you say that? 

00:12:33 Dave 

OK so take. 

00:12:33 Dave 

A step back here, right? We're all data consultants, or we were at some point in our life and probably most of the listeners are. And if you've been doing this, I've been doing this since the mid 90s in college and when I first started I had an internship with a consumer package. Good company, they made candy. 

00:12:52 Dave 

Hours and they said, hey, we wouldn't want to do an internship and take a look at our data and figure out where is the best spot to put candy on a shelf so that we sell more candy to kids, right? So we used data for that at the time that was known as business Intelligence in the industry. Nowadays business intelligence means something totally different. In reality, it's really closer to what? 

00:13:12 Dave 

Today we would call data science right? So my tools of choice were SQL, although I didn't know what SQL was at the time and we had this goofy SQL engine and and essentially something called ESP's, which is roughly the equivalent of like our or stats package something. 

00:13:28 Dave 

Like that and we kind of looked at data as just, you know I have data and let me find the Nuggets of gold and I'm not going to concern myself with schema and that is I think the biggest problem with data warehouses. But take a, you know a metal layer higher right? Talk to the average business executive like a you know a CTO or CEO. 

00:13:48 Dave 

And tell them, as a consultant, you're going to go in and build them a data warehouse. 

00:13:53 Dave 

Instantly, that's a political statement you just made. Data warehouses have connotations of you, know risky projects over budget projects as far as time and money, and...

In this episode Frank and Andy have a chat with Chris Gherardini on the role of data in ERP and CRM Systems.

Transcript

00:00:00 BAILey 

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. In this episode, Frank and Andy speak to Chris Gardini about the role data plays in ERP and CRM systems. 

00:00:17 Frank 

Hello and welcome back to data driven. The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence. If you like to think of data as the new oil, then you can think of us like Car Talk because we focus on where the rubber meets the road. Although there's not much of a road trip usually on this virtual road trip. 

00:00:37 Frank 

Is Andy Leonard? How's it going, Andy? 

00:00:40 Andy 

Hey Frank, it's going really well. How are you doing? 

00:00:43 Frank 

I'm doing alright, you know, with the exception I might have to buy a new desktop computer. 

00:00:48 Andy 

Ah, I have not. 

00:00:49 Frank 

Possibly, or power supply. Literally. We were on this call and all of a sudden everything froze and I was like Oh well, blue screen. Big deal. 

00:00:59 Frank 

And then when I went to power it back on. 

00:01:03 Frank 

It just kept keeps beeping so I'm like oh, fee something something hard so I'm going to have to do some search engine work and possibly get a new power supply or something. 

00:01:06 Andy 

Codes. 

00:01:13 Frank 

Fortunately, micro center. 

00:01:14 Andy 

Everything is. 

00:01:17 Andy 

Go ahead. 

00:01:17 Andy 

00:01:17 Andy 

I've gotta say Frank, everything is figure out able right? 

00:01:21 Frank 

Everything is figure out able because of my experience with clear DB and all sorts of other drama. I have multiple backups of just about everything it if if you know so it's it's. It'll be an inconvenience, not a tragedy. 

00:01:32 Andy 

Outstanding. 

00:01:37 Frank 

But every opportunity to come back from a complete backup failure is an opportunity to learn. 

00:01:47 Frank 

And, uhm, Speaking of opportunity, it's really good timing that this guest is here because I as folks know I work at the Microsoft Technology Center in Reston and recently. 

00:02:00 Frank 

There was a, uh, someone we were on this engagement and it was very heavy into dynamics and uh, dynamics is one of those things. I haven't really looked into Andy and I have been experimenting with power apps and power platform, mostly to kind of help automate a lot of our content. 

00:02:21 Frank 

Production. 

00:02:22 Chris 

This is crucial as we. 

00:02:24 Frank 

Continue to put the final touches on our secret project, but this guest here is an expert in dynamics as well as various ERP solutions. 

00:02:36 Frank 

And he's from Saint Louis, and his name is Christian. I'm really blowing this intro here. His name is Cristiano Gardeny. Did I pronounce that right? 

00:02:48 Chris 

Cristiano Guardian yeah, he pulled our sounded out there so. 

00:02:48 Frank 

OK good good. 

00:02:51 Frank 

He did fine, got it. Sorry about that. He's the president and owner of Turnkey Technologies and they are a Microsoft partner. I did looking around on their website and they are basically they provide development, analytics, training and support services for Microsoft Dynamics. 

00:03:09 Frank 

If you don't know what Microsoft Dynamics is, a lot of people don't. In the data world tend to just know it tangentially. It's basically Microsoft CRM system, so welcome to the show, Cristiano. 

00:03:21 Chris 

Thank you very much. Thanks for having me. 

00:03:25 Frank 

It's good to have you here, and so what's the weather like in Saint Louis right now? 

00:03:30 Chris 

Ah, it's beautiful and sunny. Today it's about 64 degrees Sun index is just right around A5, so it's actually it's actually nice and better than the the ice. We had a couple weeks ago so. 

00:03:38 Frank 

Knife. 

00:03:42 Andy 

Yeah, it got bitterly cold out there for about a week, didn't it? 

00:03:47 Chris 

That's right, I happen to be in Florida that entire week. Everybody couldn't believe I missed all the fun. So with the IT was good, it was a good week to be gone. We left Saturday. We came back Sunday was 52 when we got back and the 9 inches of snow had melted and. 

00:03:51 Chris 

Unfelt 

00:03:51 Chris 

00:04:00 Chris 

So yeah, perfect timing. 

00:04:02 Frank 

Nice, now you have excellent timing Sir. Not only in just the fact that dynamics is kind of coming up, coming up on my personal radar, but also in terms of avoiding bad weather. My first question is and I'm calm. Still a new bit dynamics. I learned a lot just by working on this. 

00:04:23 Frank 

One engagement we had DMTC. 

00:04:27 Frank 

Is Dinah. 

00:04:28 BAILey 

Mix. 

00:04:29 Chris 

So Dynamics Dynamics is the biz apps. I mean, you said CRM. It's more than CRM. But today dynamics represents a family of products. You know, the legacy on Prem products, Dynamics AX Dynamics, Navy Dynamics, GP, Dynamics, SL and then the current dynamics 365, which encompasses both you know financing. 

00:04:49 Chris 

Operations, which was the dynamics AX and then Dynamics 365 business Central which was the Navy? So those are both ERP products. 

00:04:57 Chris 

And then Dynamics customer engagement, which is the CRM platform so so dynamics is a collection of biz apps. It's a family of products and you know today we we focus on the two dynamics 365 ERP products and the CRM. The customer engagement product. So great solution, but it's a platform also it. 

00:05:15 Frank 

That's what I noticed, and folks that are listening. They're like this is a data science kind of data engineering show. Why the heck are you talking about? 

00:05:25 Frank 

Dynamics but dataverse the data models, which are one of the things that blew me away, was on this one demo is that there's a. There's a button where you just basically can dump out all your cream data. 

00:05:38 Frank 

Or all your data and dynamics out to a data Lake. 

00:05:42 Chris 

That's absolutely right, Azure. So if you think about the challenges where you move from a legacy system to the cloud, maybe all the data doesn't move and you need to combine it in an Azure data like a data warehouse, and certainly all those tools and all the analytics are all part of the platform. That's just it touches dynamics out of the box, so it's quite a quite a degree of efficiency. 

00:06:02 Chris 

There. 

00:06:03 Frank 

Interesting. 

00:06:05 Frank 

So one question I have about dynamics is it's history now. You mentioned Dynamics AX and a couple of other letters next to the word dynamics. 

00:06:17 Frank 

Once Upon a time when I worked when I lived in Richmond, there was a guy who used to do a lot of work with that technology. 

00:06:24 Frank 

Back and it was Solomon in Great Plains is that is that the same thing is that the lineages from it. 

00:06:30 Chris 

That's correct, that's correct, that's correct. And so the US based products was Great Plains software out of Fargo ND, and a gentleman named Doug Burgum owned that company privately and then his family. They bought the the Salomon product line as well and then in 2001 is when Microsoft bought Great Plains. 

00:06:32 

Silly. 

00:06:46 Chris 

Software, so that's kind of how they consume the North American products and then a year later Microsoft went to Europe and bought Dynamics AX and Dynamics Navy. It was called Exapta in division so and that became a second big purchase and instantly at 2002 they had four ERP products and they're in the biz apps space like they've never been. 

00:06:48 Chris 

OK, so. 

00:06:48 Chris 

00:07:06 Chris 

Before so. 

00:07:09 Frank 

Ah OK, that's interesting. 'cause I I now I know why. There's a huge Microsoft campus in Fargo. 

00:07:16 Chris 

Yes, yes. 

00:07:18 Chris 

It's beautiful campus. 

00:07:19 Frank 

Uhm? 

00:07:21 Frank 

Yeah, I haven't been there, but I definitely maybe one day I'll end up going but the the other question I have for you. You keep saying biz apps when you say biz apps? What exactly do you mean like what? 

00:07:32 Chris 

Sure, so I'm. I'm a technical guy. I'm engineering comp SCI math and there's two directions you go and even those curriculums you go **** **** or you or business applications and so business applications in our context is, you know, we're we're business process automation again, whether it starts in an ERP from a quote to cash or a procure to pay those. 

00:07:33 Frank 

What what comic sub is that like? 

00:07:52 Chris 

For business processes and the business applications support. 

00:07:56 Chris 

Work, transactional processing or even non transactional if you think about context of a lead to opportunity to customer type of flow where you start even earlier in the process, but it is it's process automation and exception management and workflow and approvals and can go to the NTH degree of complexity. But but it's biz apps in that categorization. 

00:08:16 Chris 

So as opposed to scientific apps or development tools or games, for example, right, we're focused on businesses, not on residential applications. 

00:08:26 Chris 

That makes sense. 

00:08:27 Andy 

It does, yeah. 

00:08:28 Frank 

Do you have any questions Andy? 

00:08:30 Frank 

This is so awkward being on on this recording, but not being live. So for those that are watching or listening or maybe watching. 

00:08:35 Andy 

Yeah, I don't work. 

00:08:40 Frank 

Go ahead. 

00:08:42 Andy 

Yeah, I'd like to apologize to Chris, especially thank you for coming on here, but we're a little off because of the video. I I I never shaved but. 

00:08:50 Chris 

No worries. 

00:08:55 Andy 

I would have I. I have a face for radio. I think in audio, so that's what's throwing us just a bit. Although Frank and I do live streaming and stuff, can you tell us a little bit more about about what your company does, how how your team implements these biz apps? 

00:09:14 Chris 

Sure, so so turnkey is a is a direct Microsoft distributor, so we distribute dynamics licensing and then we provide 100% of the professional services to to plan to implement, to convert, to customize, to integrate. So really, if you think about there's two parts of business, there's the licensing side and and then the services side, which we've got about 60 team members. 

00:09:35 Chris 

These days, and as you think about, you know, delivering an implementation once the solutions been kind of articulated as project management methodology, really drive the success of the project, and so there's an intimate, detailed plan. 

00:09:48 Chris 

Where we use Microsoft project and and we plan in very very low levels of detail for project execution. Everything from you know, the initial phases of analyzing and requirements and then through design and then through development and through deployment. And then we take people live, but it's a very predictable methodology that's used for project delivery. 

00:10:08 Chris 

Around the ERP products, so that's that's the first spot, so. 

00:10:12 Andy 

You know that sounds an awful lot like what what we do when we're doing data warehousing as well and and similar work I I would say. 

00:10:22 Chris 

Absolutely the disciplines or you know, are kind of agnostic when you think about project methodology. 

00:10:27 Andy 

So just curious, what is a typical engagement about how long does a typical engagement last? 

00:10:34 Chris 

So and again, we sell 2 flavors Dynamics, 365 business Central. We talk about small, medium and those projects could. 

00:10:41 Chris 

Maybe three months for somebody small coming off of a QuickBooks. It's just financials, but it could be six months for somebody that's implementing distribution and manufacturing, for example. So depending on complexity, three months is normally the least amount of time, and in 6 plus months for the business, central on the finance and supply chain, which was acts as a much larger applications targeted at, you know. 

00:11:01 Chris 

Mid market enterprise organizations. Those projects are typically not being delivered in less than six months. Frankly, and I've got some that we see them take 12 to 18 months for example so. 

00:11:13 Chris 

No, it's gonna save us the the project management requirement. Because of that duration and scope and girth. You really people get lost right? Anyway, I'm sorry please. 

00:11:23 Frank 

Oh no no no no no so. 

00:11:26 Frank 

The the, the ERM or the ERP systems like Dave require. So Once Upon a time I was working for a large German chemical company, right? And of course it's a German company, so they used SAP and they hired a bunch of consultants and consulting firms to build out the system. But when they. 

00:11:46 Frank 

Rolled out SA P R2. I think it was. 

00:11:49 Frank 

Is. 

00:11:50 Frank 

Apparently there was not. 

00:11:52 Frank 

A lot of project discipline now I'll just. I'll just leave it there. 

00:11:57 Frank 

And it basically shut down some of their plants because there were just things were not coming in the way they were supposed to. So So what? 

00:12:06 Frank 

How? 

00:12:07 Frank 

How does ERP systems? How do our ERP systems? Kind of you know if they're done wrong? It sounds like they can create a big mess if they're done right, they could really optimize operations. 

00:12:19 Frank 

Uhm? 

00:12:21 Frank 

I mean is that, is that true? 'cause I I kind of saw, I mean. 

00:12:23 Frank 

That was just a Horror Story. It's true. 

00:12:24 Chris 

It's true, it's true. It's like me giving you lousy directions to drive from Florida to Washington, and it takes you six months and it should have taken you three days. There's a great example. I poor guidance and poor methodology, is it stretches it out. Things are missed, costs are out of control, but again, if it's done correctly through a thorough analysis. 

00:12:34 Frank 

Point 

00:12:45 Chris 

Then you really define scope. 

00:12:46 Chris 

And you know you have good business process visualization. Then you drive to deliver those processes to that point and and it's. And again, if you do a good job and my team does a great job of of really articulating business process, you gain great efficiency and Moreover you get capacity to turn up the juice again, you can take more volume and you've you've articulated. 

00:13:05 Andy 

Nice. 

00:13:06 Chris 

And really gotten the inefficiency out of the process, and Even so, you don't touch every transaction you touch the exceptions so you get a lot of leverage. But then you're correct if it's done right, if it's done. 

00:13:16 Chris 

Wrong, right? It maybe it's broken, maybe it falls off the table and somebody has to pick it up and has a manual step because they didn't think through it thoroughly. And and now you've got a bigger problem, right? And sometimes companies don't retire the old systems and they're working in two places, so there is a lot of negative that can come for people that don't manage and plan and and deliver these systems. And and again, we've been doing this. 

00:13:37 Chris 

For 27 years, so we're pretty pretty good at it so. 

00:13:38 Andy 

Will you? 

00:13:40 Andy 

Wow. 

00:13:42 Andy 

Well, you you mentioned Chris that you know when you were giving examples of the typical projects links that customers are are often migrating from other platforms. Other ERP ish. Perhaps they do some of the ERP work and then you're moving them into dynamics. And as you say. 

00:14:02 Andy 

Once they get in there, they're going to be able to scale. It sounds like horizontally and and cover more territory than the system that they were using and also scale vertically. Like you said, turn up the juice and and just grow is that. Is that...

In this livestream, Frank and Andy talk about geothermal energy, solar power, and why you should never say not to Clippy.

In this episode of Data Driven, Frank and Andy speak with Peter Voss about Artificial General Intelligence, Personalizing Personal Assistants, and Motorcycles

Sponsor

Sponsor: Audible.com - Get a free audio book and support DataDriven - visit thedatadrivenbook.com!

Guest Bio

Peter Voss is the world’s foremost authority in Artificial General Intelligence.

His company Aigo (https://www.aigo.ai/) has created the world’s first intelligent cognitive assistant.

Aigo was funded with a personal investment of $10 million dollars. They currently manage millions of personalized customer service inquiries for household name-brands

Notable Quotes

Aigo is Peter's company. BAILeY's Introduction (00:00)

The east coast has been blanketed with snow. (01:30)

The Expanse books (03:00)

Coding for curiosity? - Frank (11:50)

"Models don't dynamically learn." - Peter (13:00)

Three waves: Logic programming, Deep learning / neural networks, cognitive architecture / intelligence (14:00)

Intelligence v. sentience? - Frank (15:50)

What about bots being "led astray?" - Andy (18:30)

On programming morality... (21:30)

AI Safety is a better description - Peter (22:30)

Asimov's three laws of robotics - Frank (23:15)

On delimmas - Peter (24:15)

"Morality should be about human flourishing." - Peter (25:15)

Are we using digital means to do something analog? - Andy (27:55)

Peter is trained as an electronics engineer. (28:05)

"Context is always super-important." - Peter (28:30)

"You need a feedback system." - Peter (30:00)

AIGO is Peter's company. (31:00)

The three meanings of personal. (34:00)

"Exo-cortex" (33:50)

On context switches (38:30)

Did you find AI or did AI find you? (41:00)

"I took five years off to study..." - Peter (43:00)

What's your favorite part of your current gig? (44:10)

When I'm not working, I enjoy ___. (45:00)

I think the coolest thing in technology today is ___. (45:30)

I look forward to the day when I can use technology to ___. (46:25)

Something interesting or different about yourself (47:00)

How Not to Die (48:00)

Where can people learn more about Peter? (49:00)

Book reading / listening recommendations? (49:00)

The Mind's I (50:00)

Peter's articles on Medium (52:00)

Get a free audio book and support DataDriven - visit thedatadrivenbook.com! (00:00)

Transcript

The following transcript is AI generated.

00:00:01 BAILeY

Hello and welcome to data driven.

00:00:03 BAILeY

The podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.

00:00:11 BAILeY

In this episode, Frank and Andy speak with Peter Voss, peterboat.

00:00:15 BAILeY

Peter Voss is the world's foremost authority, an artificial general intelligence or AGI.

00:00:21 BAILeY

In fact, he is the one who coined the term in 2001 and published a book on the topic in 2002.

00:00:28 BAILeY

He is a serial.

00:00:29 BAILeY

AI entrepreneur technology innovator who has for the past 20 years, then dedicated to advancing artificial general intelligence.

00:00:38 BAILeY

Today he is focused on his company, IGO, which is developing and selling increasingly advanced AGI systems for large enterprise customers.

00:00:47 BAILeY

Peter also has a keen interest in the interrelationship between philosophy, psychology, ethics, futurism and computer science.

00:00:56 BAILeY

I think you will find this interview a fascinating look at the future of AI.

00:01:01 BAILeY

Now on with the show.

00:01:05 Frank

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence.

00:01:13 Frank

If you like to think of data as the new oil, then you can think of us like well.

00:01:18 Frank

Car Talk because we focus on where the rubber meets the road and with me on this epic virtual road trip down the information highway because we're still locked in quarantine.

00:01:29 Frank

As always, Andy Leonard.

00:01:30 Frank

How's it going and?

00:01:31 Andy

Good Frank, how are you?

00:01:33 Frank

I'm doing well.

00:01:34 Frank

We had a bit of snow.

00:01:36 Frank

We're recording this on Monday, February 1st and the East Coast has been blanketed in some snow.

00:01:37 Peter Voss

Yes.

00:01:45 Andy

Yeah, we got more than we've gotten, probably since 2018 or so. About four inches here in FarmVille and then almost an inch of ice on top of that, which always makes it fun, right?

00:01:58 Frank

Yeah, the ice is worse than the snow on.

00:02:00 Frank

Basically so I went out, walk the dog today and one of the dogs and it was crunch, crunch, crunch.

00:02:06 Frank

So there's a nice layer of ice over everything which is going to make driving later fun, but I do have.

00:02:13 Frank

I do have the an all wheel drive car which is fantastic.

00:02:17 Frank

I will never not own one of those again.

00:02:19 Andy

Nice.

00:02:21 Frank

Yeah, you've seen it's the CRV.

00:02:23 Andy

Yes, yeah, it's nice you did well.

00:02:26 Frank

I dubbed it the Rocinante.

00:02:31 Andy

In case our listeners are not familiar with that, with what Frank is referring to, it is not the old novel.

00:02:40 Andy

Frank is not tilting at windmills instead.

00:02:44 Andy

And if I got that reference wrong, correct me.

00:02:46 Andy

I'll just edit that out.

00:02:47 Frank

Oh, you are right, it's from this AM Oh my God, I forgot new book on Cody.

00:02:48 Andy

Not sure.

00:02:51 Andy

Donkey Quixoti wasn't.

00:02:53 Frank

Yeah yeah Cervantes I was gonna say from Cervantes book and I'm like oh what was the name of that?

00:02:53 Andy

Yeah so.

00:02:59 Frank

Which is the opposite of how most people think, but that's what I do.

00:02:59 Frank

OK, good.

00:03:02 Andy

There we go, but it is actually a reference to both the books and a series, The expanse of which Frank and I are great fans, so.

00:03:12 Frank

Awesome, but you know who's not covered in snow today.

00:03:13 Andy

I like it.

00:03:15 Andy

Who is not covered in snow their guest.

00:03:16 Andy

Our guest.

00:03:18 Frank

Who lives in?

00:03:18 Frank

Yeah.

00:03:20 Frank

I'm assuming sunny or Smokey I guess depending on the time of year California Peter Voss Peter welcome to the show.

00:03:29 Peter Voss

Thank you, yes, it's we've got snow on the mountains here, but it's very sunny.

00:03:36 Peter Voss

It's it's nice and we have a lot less smog these days.

00:03:41 Andy

Very good.

00:03:41 Frank

Nice so you are the.

00:03:46 Frank

One of the world's, or if not the world's foremost authority in AGI or artificially artificial general intelligence, and I believe you are the one that coined the term.

00:03:58 Peter Voss

Yes, correct and 2001 myself and two other people. We coined the term artificial general intelligence AGI to really distinguish the kind of work we were doing from, you know, specialized narrow AI which is.

00:04:18 Peter Voss

Pretty much what everybody else is doing.

00:04:20 Peter Voss

The original dream of artificial intelligence was of course, to have systems that can think and learn the way humans do, but that turned out to be a lot lot harder than people thought.

00:04:31 Peter Voss

So over the years, AI really turned into narrow AI using human ingenuity to figure out how to solve one particular problem, like playing chess or.

00:04:41 Peter Voss

Container optimization or medical diagnosis and then to write a program or to train data to do that to solve that particular problem.

00:04:51 Peter Voss

But it's really the external intelligence of the program or the data scientists that is then encoded.

00:04:58 Peter Voss

To solve that problem, whereas we wanted to get back to the original dream of having a thinking machine that it can figure out how to do these things and and learn more humans do so.

00:05:09 Peter Voss

That's why we felt we had to.

00:05:12 Peter Voss

You know, coin a separate term to distinguish it from narrow AI.

00:05:16 Frank

Interesting.

00:05:18 Frank

So for years, AGI has been.

00:05:21 Frank

Kind of thought the stuff of science fiction.

00:05:24 Frank

I think there was a lot of optimistic people like you said that thought we would have it by now.

00:05:29 Frank

I know this is kind of a loaded question, but one do you think we'll ever get there and two, what's the sort of time frame we're looking at?

00:05:38 Peter Voss

Yes, it's an interesting question, so absolutely, I believe it's it's.

00:05:42 Peter Voss

Possible, and in fact the reason we got together. We wrote a book called Artificial General Intelligence. As I said in 2001 was because we believe the time is ripe to get back to this original dream that the technology had advanced enough. Both hardware and software technology and cognitive psychology. Cognitive science.

00:06:02 Peter Voss

That we now understood enough and had fundamentally had the tools in place to tackle this problem and to say.

00:06:11 Peter Voss

So I I absolutely believe that it can be solved soon, and in fact we will leave.

00:06:18 Peter Voss

We are on on the way of solving this problem now in terms of time frame.

00:06:24 Peter Voss

Normally the way I answer this question is I don't measure it in time.

00:06:28 Peter Voss

I measured in dollars.

00:06:31 Frank

I like that time is money, so I guess.

00:06:34 Frank

That's a reasonable correlation.

00:06:35 Peter Voss

Yeah, and and the reason I do, I say that is because.

00:06:39 Peter Voss

Still, today almost nobody is working on AGI. You know, 99% of all the effort in artificial intelligence is still on narrow AI, so if this continues, it will take a long long time for us to reach human level AGI. But if that changes.

00:07:00 Peter Voss

And you know the kind of funding that's going into deep learning machine learning suddenly was applied to AGI.

00:07:06 Peter Voss

Then I think it could easily happen at less than 10.

00:07:09 BAILeY

Yes.

00:07:10 Frank

Oh wow.

00:07:11 Andy

Very cool, so I'm curious is there any like lead in does?

00:07:16 Andy

Does time and money invested in deep learning and narrow AI?

00:07:23 Andy

Does any of that help move the cost?

00:07:25 Andy

Say further the cause for AGI?

00:07:29 Peter Voss

Slightly, I believe, you know.

00:07:32 Peter Voss

Obviously, any advances in languages and data collection in hardware development and the general experience.

00:07:42 Peter Voss

In that sense, it does help it.

00:07:44 Peter Voss

But in another sense, it's actually the opposite.

00:07:46 Peter Voss

It's actually hindering it because a whole generation of software engineers and data scientists are now coming into the field, believing that deep learning machine learning is a way to do it.

00:08:00 Peter Voss

And all we need is more data, more horsepower and will solve this problem.

00:08:05 Peter Voss

And that's I think barking up the wrong tree, and it's a it's a dead end.

00:08:10 Peter Voss

So in that sense, what's happening today with deep learning?

00:08:12 Peter Voss

Machine learning is actually counter to achieving.

00:08:16 Andy

GI interesting very interesting.

00:08:20 Frank

Was it always that way or it's just the way the market kind of went frenzied over just narrowed AI?

00:08:26 Peter Voss

Why?

00:08:26 Peter Voss

Well, we've had several windows of AI.

00:08:30 Peter Voss

You know the the disappointments over the decades.

00:08:33 Peter Voss

You know, when we had expert systems, people believe that you know they would really, you know, show real intelligence and then it kind of fizzled out.

00:08:42 Peter Voss

And so we've had.

00:08:43 Peter Voss

We've had various windows, and but of course, deep learning machine learning has been so spectacularly successful in several areas.

00:08:52 Peter Voss

You know, image recognition, improving speech recognition, and you know various other fields that just, you know, it's the only game in town as it has been very, very successful.

00:09:04 Peter Voss

But people are also starting to realize what the limitations are of it.

00:09:11 Peter Voss

So yeah, it's it's kind of at the moment.

00:09:14 Peter Voss

The only game in town, and it has really been successful in many.

00:09:17 Andy

Areas, So what are those limitations?

00:09:20 Andy

And how does AGI addressing?

00:09:23 Peter Voss

Yeah, so fundamentally when you think about intelligence, you know if you think about just common sense.

00:09:32 Peter Voss

If we talk to a person and we judge them to be intelligent or to be totally non intelligent, the kind of things we expect is that they can learn.

00:09:43 Peter Voss

Immediately that when you say something a, they understand what you're saying and they integrate that knowledge with their existing knowledge so you know if you say my sister's moving through Seattle next week or something.

00:10:01 Peter Voss

That knowledge needs to fit in somewhere.

00:10:04 Peter Voss

You know you know the person who's talking.

00:10:06 Peter Voss

You may know who the sister is, or you may not know who the sister is.

00:10:10 Peter Voss

You probably know what Seattle is.

00:10:13 Peter Voss

You may have images of, you know, rain pouring down all the time or whatever, but so you integrate that knowledge.

00:10:21 Peter Voss

And if you're not cleared, my maybe the person has two sisters, so then you would ask her, do you mean your older sister you know your younger sister?

00:10:30 Peter Voss

And so we expect an intelligent human to basically do.

00:10:35 Peter Voss

You know what's technically called one shot?

00:10:37 Peter Voss

Learning?

00:10:38 Peter Voss

You hear something once you see an image.

00:10:40 Peter Voss

Once you learn that and you integrate it into your existing knowledge base.

00:10:46 Peter Voss

And if you're not sure how to interpret it.

00:10:49 Peter Voss

Then you ask clarifying.

00:10:50 Peter Voss

Questions until you know what it what it is.

00:10:54 Peter Voss

So you have deep understanding you have disambiguation.

00:10:59 Peter Voss

You have learning instant learning, one shot learning.

00:11:03 Peter Voss

You have long term memory.

00:11:05 Peter Voss

You remember that next week you you know if you paid attention, you will remember that and you have reasoning about.

00:11:12 Peter Voss

30 now deep learning machine learning as it's done today, really doesn't offer any of those.

00:11:20 Peter Voss

So if you if you had a human and you told them something and they didn't remember it, they didn't understand that they didn't ask for clarification.

00:11:27 Peter Voss

You wouldn't think of them as being very intelligent, would you?

00:11:33 Frank

No, I mean, my kids are smart, but when I tell them to bring the trash cans back from the street, they'll conveniently forget.

00:11:39 Frank

But I, I think I know where you're going with that, yes?

00:11:42 BAILeY

All right?

00:11:44 Frank

But the question I have, it sounds like you're trying to and I know this is going to be not really good analogy.

00:11:50 Frank

Or maybe it is you're trying to code for curiosity.

00:11:54 Peter Voss

That's very much part of it, but you know even deeper is understanding.

00:11:59 Peter Voss

Basically, when you have some input, do you?

00:12:02 Peter Voss

Do you understand you know what the implications are, how it fits in with the rest of the knowledge that you have?

00:12:08 Peter Voss

And you know, even that, that's sort of more even more fundamental than curiosity.

00:12:13 Peter Voss

But yeah, curiosity is then wanting to gather more information, so this is inherently an interactive process.

00:12:22 Peter Voss

You know, an intelligent person would ask follow up questions you know they would want to kind of.

00:12:29 Peter Voss

Fill in the pieces of the puzzle and you know that they can be more.

00:12:33 Peter Voss

In fact effective in their communication on their or their job.

00:12:37 Frank

Right so.

00:12:37 Peter Voss

So yes, that's definitely part of it.

00:12:40 Frank

So calling back to your example of someone's sister moving to Seattle you you would ask, you know, I didn't know you had a sister or how many sisters do you have or how many siblings do you have and.

00:12:51 Frank

Where is she moving to?

00:12:52 Frank

Why?

00:12:53 Frank

I guess that's kind of.

00:12:55 Frank

I guess it's all about building that knowledge map inside.

00:12:58 Frank

Your head or then your head being could be a program I guess.

00:12:58 BAILeY

Exactly.

00:12:59 BAILeY

OK.

00:13:02 Peter Voss

Yeah, and deep learning machine learning really doesn't allow for that at all.

00:13:07 Peter Voss

You know you accumulate masses of data and you train a model, but that model is then static.

00:13:14 Peter Voss

It's a read only model.

00:13:15 Peter Voss

You know, it doesn't dynamically learn, so it may have a sort of a knowledge graph, but even that knowledge graph is.

00:13:23 Peter Voss

Is very opaque, it's.

00:13:26 Peter Voss

Yeah, it's not scrutable you know and and this is this is such a big problem with deep learning machine learning that you don't know why it gives a certain response, which is a huge...

In this episode, Frank and Andy speak with Dan Burcaw on Entrepreneurship, Using AI to Stop Customer Churn, and Deploying Code onto Nuclear Submarines.

Show Notes

Transcript

The following transcript is AI generated.

00:00:00 BAILeY

Hello and welcome to data driven.

00:00:02 BAILeY

The podcast where we explore the emerging fields of data science, machine learning, and artificial intelligence.

00:00:09 BAILeY

In this episode, Frank and Andy speak with Dan Burke or Dan is a serial entrepreneur who has founded four companies each on the forefront of a major technology wave, open source software, the smartphone.

00:00:23 BAILeY

Cloud computing and now machine learning.

00:00:26 BAILeY

Currently he leads Nam Eml, a company focused on helping app developers start and grow mobile subscription businesses.

00:00:34 BAILeY

If you follow Frank and or Andy on social media, you certainly have heard them bang on about their secret project.

00:00:41 BAILeY

I will drop a one word hint here foreshadowing.

00:00:45 BAILeY

Now on with the show.

00:00:48 Frank

Hello and welcome back to data driven.

00:00:50 Frank

The podcast where we explore the emerging fields of data science machine learning, an artificial intelligence, and if you like to think of data as the new oil, then you could consider us Car Talk.

00:01:02 Frank

Because we focus on where the rubber hits the road.

00:01:05 Frank

So with that as my guest on this pandemic road trip, that hasn't happened.

00:01:13

Yeah.

00:01:13 Frank

By my copilot here is Andy Leonard.

00:01:16 Frank

How you doing Andy?

00:01:17 Andy

Hey, I'm doing pretty good Frank how are you?

00:01:20 Frank

I'm doing well, I'm doing well.

00:01:21 Frank

I had a kind of an architecture session this morning, so that went really well.

00:01:27 Frank

It was.

00:01:28 Frank

It was an interesting conversation and I love doing those.

00:01:31 Frank

Those are always fun.

00:01:32 Frank

How about?

00:01:32 Andy

Yeah.

00:01:33 Andy

Yeah, so I'm proofing the next book.

00:01:36 Andy

Proofing is the absolute last chance to remove all of the typos I've left in.

00:01:42 Andy

As I've gone through the last three full edit sessions and there's still some there.

00:01:47 Andy

Frank, I'm convinced that the next book is going to have, you know, have a fair share of those.

00:01:52 Andy

What I'm really concerned about.

00:01:54 Andy

Is making sure that the demos work an yeah that's you know it's it's tedious and it's the LastPass so you know it's like is this over yet? Yeah, I'm sick and tired of reading this guy's writing and it's me so.

00:02:10 Andy

Yeah no.

00:02:10 Andy

But yeah.

00:02:12 Frank

That was the hardest part.

00:02:13 Frank

People asking.

00:02:14 Frank

Like when I wrote a book on Silverlight an aside from it being about Silverlight, the hardest thing wasn't so much writing, it was having to go back and re edit my own stuff and like.

00:02:24 Frank

You know, and I would look at it and be like man like I'm a terrible or.

00:02:28 Andy

That's I have said over and over again to my computer monitor who wrote this crap.

00:02:33 Andy

By a friend if you live.

00:02:33 Andy

But Fortunately for this is a second edition, so an it's one of those second editions where I kept the first 10 or 11 chapters.

00:02:43 Andy

I I changed from my writing language.

00:02:46 Andy

I wrote it like three years ago.

00:02:48 Andy

And I really this grew out of a series of blog posts that I wrote back in 2012. It was all in VB back then, Visual Basic. And so I wrote it that way in 2017 and for the 2nd edition I went back and updated all of that. That's really the only thing I changed was I went to C sharp.

00:03:06 Andy

An I kind of needed to because the rest of the book was going to be in C sharp anyway.

00:03:12 Andy

And so yeah, that's that's kind of how it went.

00:03:15 Andy

And for anybody listen, it thinks wow, Andy is smart.

00:03:18 Andy

He's written a book about C sharp.

00:03:20 Andy

He must know C sharp really, really well.

00:03:22 Andy

I say throughout the book I am not a C sharp developer.

00:03:26 Andy

I feel like I'm working my way up to being a noob, but but.

00:03:29 Frank

Don't you work classes?

00:03:31 Andy

I do wear glasses.

00:03:33 Andy

Yes, yeah.

00:03:33 Frank

So you can see sharp.

00:03:36 Andy

I did.

00:03:36 Andy

They took me awhile.

00:03:37 Andy

Do you have your sound effects running from I?

00:03:39 Frank

Do were back in Zend Caster.

00:03:41 Frank

So for folks listening like I don't remember this being on the live stream.

00:03:45 Frank

If it's not, we're doing this the old fashioned way right then, and don't worry, Andy and I've been live streaming a lot, which you probably noticed, but today we have a very special guest, don't we, Andy?

00:03:48 Frank

Um?

00:03:56 Andy

Yeah yeah, Dan Burke all is awesome.

00:04:00 Andy

He's a co-founder and CEO and I hope I say this right, is it?

00:04:04 Andy

Is it nami? Nami ML Dan.

00:04:07 Dan Burcaw

Yeah nami. Like tsunami.

00:04:09 Andy

Ah OK, I got it right the first time NAMI AML and it's a really smart service for monetizing digital products with subscriptions.

00:04:09 Frank

Well.

00:04:19 Andy

And just he's had a whole ton of experience working in, you know, in marketing for the Oracle Marketing Cloud, working with the mobile product for that.

00:04:31 Andy

So pretty smart Guy joined joined Oracle back during the acquisition of Push IO and.

00:04:39 Andy

Push IO was a leading mobile messaging provider as well.

00:04:44 Andy

And he served there as a Co founder and CEO.

00:04:47 Andy

There's a bunch more in here about Nan, an it all kind of boils down to super smart, successful guy.

00:04:54 Andy

We've had a little bit of banner before we click the record button an I can attest to.

00:04:59 Andy

That is really enjoyable conversation.

00:05:01 Andy

I look forward to this show.

00:05:02 Andy

Thanks for being here, Dan.

00:05:05 Speaker 1

Really happy to be here.

00:05:05 Speaker 1

Really happy to be here.

00:05:06 Speaker 1

Thanks for having me.

00:05:07 Frank

Awesome, so you're a serial entrepreneur and you founded a bunch of companies.

00:05:13 Frank

Um, but my favorite part of the bio I read on you was that.

00:05:18 Frank

You wrote software that ended up on a nuclear submarine.

00:05:23 Speaker 1

Yeah, that's right.

00:05:26 Speaker 1

It's it's hard.

00:05:26 Frank

That that totally away I was like what?

00:05:29 Speaker 1

It it's it's hard to even tell that story sometimes because it's so unbelievable.

00:05:35 Speaker 1

I 17 years old at the time.

00:05:38 Speaker 1

The company that I cofounded was building a flavor of Linux.

00:05:46 Speaker 1

A flavor of Linux that was designed to run on Apple Macintosh hardware.

00:05:52 Speaker 1

And at the time.

00:05:52 Frank

Interesting.

00:05:54 Speaker 1

Then the the reason for that was that Apple was using the power PC chip power PC chip in that moment of time. You know, we're kind of talking in the late 90s. Early 2000s had fantastic price per performance per Watt, which is a metric that a lot of folks in the kind of high performance computing world look at when they're trying to figure out.

00:06:11 Andy

Me.

00:06:18 Speaker 1

How to build these kind of supercomputer clusters?

00:06:21 Speaker 1

And so it just happened at that moment in time, the Mac would had had the best price performance per Watt because of the chips that they.

00:06:29 Speaker 1

We're using and so we we ended up doing a deal with Lockheed Martin and the US Navy to build a cluster of Macs running Linux.

00:06:45 Speaker 1

That were deployed across the US Navy nuclear sub fleet for the purpose of doing sonar image processing, yeah.

00:06:53 Andy

Wow.

00:06:55 Speaker 1

The the the software that I wrote was related to.

00:07:00 Speaker 1

You know how folks on the boat would have to manage these units if there was issues, how would you know?

00:07:07 Speaker 1

Kind of the maintainability repair ability was a big issue when you're actually out at sea and trying to have this stuff run in kind of a mission critical fashion so.

00:07:17 Speaker 1

We ended up.

00:07:17 Speaker 1

I mean it was this was such a crazy project because the hardware was modified hardware.

00:07:22 Speaker 1

It wasn't off the shelf Apple hardware, it was Apple Hardware and then we did a bunch of things to it and then it was Linux and then it was some custom software that made the whole thing operate an.

00:07:35 Speaker 1

So it's it was.

00:07:37 Speaker 1

It was a nutty project, an I'm.

00:07:40 Speaker 1

Looking back on it now, I'm surprised that it had ever shipped quite frankly.

00:07:46 Frank

Spoken like a true engineer, right?

00:07:48 Frank

You're always you always look at your flaws and like Oh my God, that's actually running.

00:07:56 Frank

So so you you where did you go after that?

00:08:00 Frank

'cause it says you know you're a serial entrepreneur and so how did you get into?

00:08:05 Frank

I don't want to steal.

00:08:06 Frank

Kind of our pre canned questions Thunder but.

00:08:11 Frank

Tell me how did you get into A&ML? Or were you doing ML on those on those retrofitted Max?

00:08:18 Speaker 1

No, we weren't.

00:08:19 Speaker 1

We weren't, but but you know, I think that part of the hype that world of high performance computing where a lot of our customers were, you know, national labs or defense oriented things.

00:08:30 Speaker 1

I mean, part of the appeal of what we were offering in that period of time was that they were running algorithms an doing some of this stuff.

00:08:39 Speaker 1

You know, obviously ahead ahead ahead of their time and they need it.

00:08:43 Speaker 1

There wasn't the cloud computing yet, so they were literally just trying to assemble the biggest.

00:08:49 Speaker 1

Supercomputers using off the shelf hardware that they possibly could so we weren't writing the algorithms.

00:08:55 Speaker 1

We were more enabling these algorithms to be run, but I would say the Fast forward is that in terms of my career, is that working on that led to?

00:09:09 Speaker 1

Being involved in sort of the mobile ecosystem from the launch of the App Store and the iPhone back in 2000, seven 2008 and in a way it was very very similar to what we did with the submarines. Because you were dealing with constrained hard.

00:09:25 Speaker 1

Where you always had to care about performance and battery life and battery life, less so on the Subs.

00:09:31 Speaker 1

But some of the same sort of constraints where you're trying to get the best performance you can out of these things and operating in that mobile landscape and building apps for some of the largest consumer brands.

00:09:46 Speaker 1

And then you guys mentioned in the in the intro about push IO.

00:09:49 Speaker 1

This mobile messaging company that we.

00:09:51 Speaker 1

Built, we ended up at Oracle building this mobile marketing engine is part of the Oracle Marketing Cloud an and one of the things that we saw there is that now.

00:10:03 Speaker 1

Fast forward to kind of more modern times and there's such a prevalent use out there of.

00:10:11 Speaker 1

Technology like email, you know email marketing systems and push notifications in the world of mobile in order to tackle kind of a fundamental problem that exists with some of these products, which is the user.

00:10:28 Speaker 1

Download your app, let's say, and they use it and then and then they churn, and then they abandon an and you as a publisher of a product like this, is one of the battles that you're trying to fight is how do I get them back into the experience and so are sort of observation is we were.

00:10:44 Andy

Right?

00:10:48 Speaker 1

You know, done our tenure there and we're looking to do something next.

00:10:52 Speaker 1

And new was a couple of things.

00:10:55 Speaker 1

The first thing we saw was that with the iPhone 10, I think it was.

00:11:01 Speaker 1

Apple released.

00:11:02 Speaker 1

Face ID.

00:11:03 Speaker 1

And that was using algorithms running on the device, so the benefit was you could unlock the phone very, very fast, but also it had some privacy characteristics where Apple doesn't need your face and the kind of the point cloud representation of your face to be up on their servers somewhere.

00:11:21 Speaker 1

That was really intriguing to us.

00:11:23 Speaker 1

The other thing was that we saw that the app economy, so to speak, was in transition from kind of the early days of where it was paid downloads.

00:11:33 Speaker 1

Transitioning to kind of in app purchases, which the game ecosystem has really been been focused on to trying to create more durable, sustainable revenue models through subscription.

00:11:35 Speaker 1

Which is right?

00:11:46 Speaker 1

And so how we sort of arrived at focusing a lot on data at NAMI.

00:11:53 Speaker 1

Is that it?

00:11:54 Speaker 1

It seemed to us like there was.

00:11:56 Speaker 1

If we we would, we really were excited about an idea that if we could.

00:12:02 Speaker 1

Help the guy.

00:12:04 Speaker 1

Is.

00:12:04 Speaker 1

App publishers a mechanism to send way fewer push notifications.

00:12:10 Speaker 1

An email messages because they had a technology stack that could allow them to detect in the experience, right directly on the device that somebody was showing signs of churn, or that somebody was showing some.

00:12:25 Speaker 1

Early intent that they might be a a candidate to be a subscriber, and so just that idea that maybe there's a way that we could be part of cutting down the messaging load by making the actual experiences smarter and more intelligent about what users are doing was where we.

00:12:42 Speaker 1

Started.

00:12:43 Frank

That's interesting.

00:12:43 Frank

That's it.

00:12:44 Frank

What sorts of signals?

00:12:47 Frank

That you can collect given specially with Apple's kind of enhanced privacy policies that they've been been doing.

00:12:55 Frank

An what?

00:12:56 Frank

What sorts of signals kind of indicate churn?

00:13:00 Speaker 1

So you know it is.

00:13:01 Speaker 1

It's a great question.

00:13:02 Speaker 1

When we started out we were thing.

00:13:04 Speaker 1

Gain, we're going to collect all this crazy stuff.

00:13:07 Speaker 1

I mean, we were even thinking at one point in the early prototyping that you know, maybe maybe, what carrier the user is on is some signal.

00:13:16 Speaker 1

Maybe the device form factor, whether it's the really expensive version of the phone or the lower you know there's all these things that we were thinking about, but.

00:13:24 Speaker 1

When when?

00:13:27 Speaker 1

And we're not my cofounder and I are not experts in this field, so one of the things that we did was we recruited our CTO who has a PhD in applied math and had been building data science animal models, kind of in production at, you know, in the real world.

00:13:46 Speaker 1

Applications of places like the Los Angeles Times and Tribune Publishing and one of the first things he told us when he came in was guys like, wait, you're trying to?

00:13:55 Speaker 1

You don't need all these days.

00:13:56 Speaker 1

Points a lot of what you're trying to collect just isn't isn't going to move the needle, and So what.

00:13:57 Speaker 1

Huh?

00:14:03 Speaker 1

It really gets to both on the so we look at, you know from subscriptions we're looking at.

00:14:07 Speaker 1

Kind of two things.

00:14:08 Speaker 1

One is what are signals that show that somebody might be have a propensity to purchase.

00:14:17 Speaker 1

And then, secondarily, that early turn detection, or kind of likelihood to churn.

00:14:23 Speaker 1

And it turns out it's it's pretty simple on some level, because it's really about the behavioral signals around engagement.

00:14:34 Frank

Interesting soon.

00:14:34 Speaker 1

So are they using the app or are they using the app a lot?

00:14:38 Speaker 1

Or they did they used to use it a lot and now they're not using it as much so those are kind of the key?

00:14:44 Andy

Signals, so you're not popping up little boxes and saying, do you want to keep using the app?

00:14:51 Andy

Check yes or no.

00:14:54 Speaker 1

No, I mean it's it's.

00:14:55 Speaker 1

It's funny, you know.

00:14:57 Speaker 1

I have a friend that has that has a company that that powers some of that around the ratings right?

00:15:05 Speaker 1

Do you want?

00:15:05 Andy

Yeah, yeah.

00:15:05 Speaker 1

To make this.

00:15:06 Speaker 1

Yep, and you know they have a really fascinating take on it, which is that.

00:15:11 Speaker 1

Because whenever I see one of those, I hit no, I don't.

00:15:14 Speaker 1

I you know, I just like want to dismiss it an.

00:15:17 Andy

Yeah, yeah.

00:15:18 Speaker 1

Yeah, he's got a strong viewpoint that by by asking a user a binary question it provides them better data for what they're trying to do around kind of customer sentiment an so I just thought I was fascinated by that because whenever I see one of those ratings popped up so I just wanted to like.

00:15:34 Andy

Interesting.

00:15:41 Speaker 1

I want to say no, even if I like the experience on some level, I have a visceral reaction that's just like I leave me.

00:15:47 Frank

No.

00:15:48 Frank

Right, right?

00:15:48 Andy

Well, I wonder if that's

00:15:48 Frank

Well, it's always when you're sorry, ID.

00:15:50 Andy

That's OK, go ahead.

00:15:52 Frank

It's always when you're trying to do something or the kids are screaming like do you want to write this?

00:15:52 Frank

It's always when you're.

00:15:56 Frank

Like no, I want to use this stupid app like even if I like it.

00:15:58 Frank

But what I find myself doing and I've as I'll say not now like like remind me

In this episode, Frank and Andy talk about staying motivated in the new year, answer questions from the audience, and share a little about their secret project.

This episode was originally recorded on an impromptu livestream and  in a delightful surprise Andy was able to join.

In this episode, Frank offers some encouragement for people hoping for a better year in 2021.

This episode was originally recorded on an impromptu livestream and <break time="0.3s" /> in a delightful surprise Andy was able to join.

Links:

Get a free Audible book on us at https://www.audible.com/ep/creator?source_code=PDTGBPD060314004R

Transcript

Coming Soon

In this episode, Frank interview Baby Supriya about her journey from student to professional data scientist.

Transcript

coming soon.

In this Thanksgiving Data Point, Frank sends a special message of thanks to you, the best audience in the world!

Show Notes

Did AT&T Predict the Future?

http://franksworld.com/2020/11/26/did-att-predict-the-future/

Transcript 

00:00:00 Frank 

Hey, what's up is Frank here from data driven? Just wanted to take a moment here. It's Thanksgiving here in the US. I'm actually sitting by the by the ocean on the beach. 

00:00:15 Frank 

And it's a beautiful day. 

00:00:19 Frank 

And God. 

00:00:21 Frank 

Some interesting interesting email the other day from website called Pod Stats or Pod Status. You'll see I have my other production assistant with me, but I just wanted to say thank you to all the listeners who helped made data driven successful over the years. Can't believe that tomorrow. 

00:00:42 Frank 

It's been four years since I had the idea for data driven. Next week will probably be. It'll be about four years since I asked Andy to be the cohost we've been rocking it pretty well. We're at about 160,000 downloads. 

00:00:55 Frank 

265 or 266 shows an. 

00:01:03 Frank 

Just wanted to say thank you. 

00:01:05 Frank 

Actually got an interesting email the other day from a website called Pod Stats Pod status. 

00:01:11 Frank 

And apparently we are very highly ranked where the 29th ranked podcast in technology in Italy. So I want to say gratze. We also rank very high and definitely in the top 50. In Sweden, Thailand, Norway in Brazil. 

00:01:30 Frank 

So thank you, I only know how to say thank you in. 

00:01:35 Frank 

Italian sorry, but I would have to go back and figure out how to say it in those other languages. 

00:01:46 Frank 

I'm sorry about that, but I will go back and figure out how to say it in the other language is another thing. If you've been very eagle eyed in terms of our show notes and the transcriptions. 

00:01:57 Frank 

Uh. 

00:01:58 Frank 

We have we have a name now for the AI voice over Lady probably do more formal show on it. But you know what? 

00:02:07 Frank 

Not gonna do it, figured I would just get the information out. Right now we call her Bailey which is an acronym for British AI Lady. You can look in the transcripts. You'll see her kind of listed as there is a name. 

00:02:23 Frank 

Interestingly enough, we changed up how we do our transcripts. I used to use video indexer but now word online you can actually upload the audio file, the MP3 file and it will actually not only do the transcription and the timestamp, but actually the speaker identification too. So we actually test this out. 

00:02:45 Frank 

And it's pretty accurate, so you'll so hopefully now are. 

00:02:52 Frank 

Hopefully now are. 

00:02:55 Frank 

Our transcripts are much more accessible. That's something we've been meaning to do and. 

00:03:01 Frank 

Yeah, oh, I see Andy's on hey what's up? Andy yeah we I shared that email with you and yeah, we are we're we're we're reaching the top 30 this is pretty good I'm I'm excited I'm happy about the show. Happy I'm thankful Thanksgiving right? 

00:03:18 Frank 

So I'm thankful for having Andy as a good friend and a cohost on this journey on this epic road trip down the information superhighway. As we say in our standard intro and but he was basically talking about all the things that look very futuristic in those commercials and. 

00:03:39 Frank 

The my dog is about to pull my arm off. I can feel it. 

00:03:43 Frank 

And. 

00:03:46 Frank 

So. 

00:03:47 Frank 

Yeah, so it's interesting that how how that you know. So he kind of goes through. It's interesting from a language point of view, 'cause I was alive in 1993. I was in the middle of college and all that stuff seemed I wouldn't say in pop. 

00:04:00 Frank 

Possible seems a little far fetched in a little improbable, but it's interesting how that video predicted touch screens. The widespread use of touch screens so it held up pretty well, except for the fact it wasn't really a T&T that was a major player in that, and if memory serves the AT&T we know today is actually a rebranding of singular, which was another company entirely so. 

00:04:24 Frank 

I'm sure someone will call me on the comments if I'm wrong. 

00:04:28 Frank 

But just wanna say I love you too man. 

00:04:32 Frank 

See Andy's comment. Yeah man, I'm just thankful to have good people in my life. Like Andy. I'm happy to have a great audience that I have happen. Will be happy to be able to, you know, spend some time and I'm unplugged by the ocean. 

00:04:48 Frank 

So happy Thanksgiving to everyone. I'm going to sign off now and might do another quantum show. Probably tomorrow, maybe not today because I had a mental breakthrough in terms of what I was able to figure out by watching this video. And I might even scored a new guest for that show. So with all of that. 

00:05:10 Frank 

From all of us to all of you. 

00:05:13 Frank 

You have a great Thanksgiving if you don't celebrate Thanksgiving. I hope you have a wonderful Thursday. 

In this Data Point, Frank livestreams from the beach to talk about how sometimes specific predictions of the future are correct, even if they miss some details.

In the 1990s, AT&T ran a series of commercials, highlighting the ways in which the internet would transform our lives. 

One that stands out is the prediction that we would eventually send faxes from the beach. In 2020, the fax machine is somewhat of a relic. In the 90s, the concept of livestreaming on a platform like Facebook, would have seemed too far fetched at the time.

Show Notes 

Sending a fax from the beach: https://www.youtube.com/watch?v=2kfIFDX9kE4

Data Driven Merchandise: https://www.amazon.com/s?rh=n%3A7141123011%2Cp_4%3AData+Driven&ref=w_bl_sl_s_ap_web_7141123011

Transcript

Coming soon

In this episode, Frank and Andy interview Dana Mantilia on Why Humans are the Weakest Link in CyberSecurity.

Watch Original Livestream

https://www.linkedin.com/posts/frank-lavigne_data-driven-live-with-dana-mantilia-activity-6735628251328204800-Qjwq

Show Notes

Coming soon!

Transcript

AI Generated

00:00:05 BAILeY

Hello and welcome to data driven.

00:00:08 BAILeY

The podcast where we explore the emerging fields of data science, machine learning and artificial intelligence.

00:00:16 BAILeY

In this episode, Frank and Andy speak to Dana Mantilia about cybersecurity and why companies are not investing their time and attention where they should be.

00:00:26 BAILeY

This episode was originally recorded on a live stream and this was the first time we had a guest join us on the life stream for a show.

00:00:34 BAILeY

Season 4 just keeps the innovations coming.

00:00:38 BAILeY

Without further ado, here are your hosts Frank Lavigna and Andy Leonard.

00:00:44 Frank

Alright, thanks for tuning into data driven. If you're watching this live, thank you for taking time out of your day. I realize this being the lead up to the Holidays. Things are kind of hectic. I know in Chateau Lavigna things are very hectic today.

00:00:59 Frank

We

00:01:00 Frank

Andy and I are happy to announce a new guest that we have with us. I first saw her on LinkedIn when she would do these really cool training videos.

00:01:10 Frank

On basically security topics.

00:01:14 Frank

An with with Black Friday, literally a week from now Cyber Monday and the just the The Creativity alarmingly creative and flexibility of scammers that we've had in light of the kovid, pandemic etc etc.

00:01:32 Frank

I figured it would be worth having kind of a good discussion about just the basics of cyber security and why it's important my wife happens to be in the cyber security field, so I'd like to think that I'm better prepared, but I know if you think you're better prepared, that's probably a vulnerability.

00:01:50 Frank

So welcome to the show, Dana.

00:01:52 Dana

Well, thank you for having me nice to be here.

00:01:55 Frank

So this is you are actually the 1st guest. We're going to have on the show that we interviewed live on a live stream first on video.

00:02:02 Dana

Very honored, very.

00:02:03 Frank

Honored so awesome. We're trying to push the boundaries for season four, so tell us a little bit about you and your company for those that haven't seen your videos on LinkedIn.

00:02:15 Dana

OK sure yeah. My name is Dana Mantilia an I am the founder of identity Protection Planning an we tried to help educate people in very layman's terms on how they can protect themselves from identity thieves and cybercriminals. And so we have a variety of different kinds of training. Either you know, training data, webinars, some videos or we have an on line.

00:02:35 Dana

Platform that's short little videos that everyone is required to watch.

00:02:38 Dana

And just to kind of start spreading the word, I mean cybersecurity is not going away and unfortunately the the frontline workers are the people that really are maybe not educated on it and they also are the ones that are clicking on things they shouldn't be clicking on so.

00:02:54 Frank

No, so that's a good point. So one of your most recent videos, and this is the one that made me think we should have her on the show.

00:03:00 Frank

Was the one the gift card scam and how?

00:03:04 Frank

Somebody in your organization got snared up in this.

00:03:08 Dana

Yeah, I mean it's.

00:03:09 Dana

It's crazy, I mean that the way that I did that little video is how exactly how it happened. She came to my office door with her codon and I said, well, why do you have your code on and she said, oh I'm going to get that stuff you need and I said well, what stuff are you talking about? And she said this stuff, we were just messaging back and forth about. I said I was. I've been sitting here at my office just doing work I didn't.

00:03:28 Dana

Message you about anything.

00:03:30 Dana

So then she showed me and they they person initially sent an email that looked like it was kind of from my email very similar, which is always usually what they do. And then you know the urgency factor. I always tell people when there's a sense of urgency. We have to stop and say, is this really a big big emergency here to go buy gift cards? But people want to please their boss so they get these emails and they act upon them.

00:03:50 Dana

So she then then the person said, can you give me your email? I mean your cell phone. I wanted to text you this. So then the conversation jumped over to her cell phone and now they're texting back and forth and she said, well, how am I going to pay for these?

00:04:02 Dana

And then he said, well, you know what? Just when you get to the store, read off the numbers in the back of the card and then when you get back I'll reimburse you. So they were. I mean, it was just back and forth and back, but anybody would have fallen for this anybody.

00:04:13 Frank

Wow, the thing that struck me is the most insidious part.

00:04:17 Frank

It's how they moved away from email pretty early in the process, because maybe I mean it was a good. I mean, there's a I don't know. As a data scientist, I I hate giving out statistics, but let's say it was a 5050 chance that that person had your cell.

00:04:30 Frank

Phone number.

00:04:31 Frank

Millimeter like an an. It's a good gambit for them because I guess they didn't have your number already saved in their phone, so they could have this whole conversation with you, right? Yeah, an I would assume that folks in your organization are well trained.

00:04:46 Dana

Well, we're at least talking about this stuff right times. That's that's a startling factor, is that?

00:04:52 Dana

You know we're talking about all these things all the time and we we totally almost fell for it so.

00:04:57 Frank

Well, I never disclosed this publicly.

00:05:00 Frank

Until I'll do it now is that one time Microsoft? I work for Microsoft, they they pay the mortgage, they pay for the electricity and it goes through the my little monitor display there.

00:05:12 Frank

But they will routinely send out kind of phishing emails.

00:05:16 Frank

And it will be like urgent you have to, like, you know, do this because your expense report or something like this. And I shouldn't admit this publicly, but I did I was driving. I see this like emergency thing come through. I'm like the screen and I'm like.

00:05:30 Frank

So I didn't think I clicked on it and it it got it. It it it got a there was there was there should have been an animated GIF of like somebody?

00:05:38 Frank

At the company doing this, but it was like this. It was this like badge of shame of like hey you fell for this uh huh.

00:05:45 Frank

You know, and I was like crap and I was like I learned. 2 lessons one.

00:05:51 Frank

Pull over first.

00:05:53 Frank

If I can't mouse over the link.

00:05:56 Frank

Probably shouldn't click on it, right?

00:05:58 Frank

And three is just.

00:06:00 Frank

That sense of urgency.

00:06:01 Frank

Um was what really like, and maybe there's a psychological thing to this where it just tricks off like this. The primordial brain, or I know there's the three brain model and Andy and I go off on tangents a lot. Dan, I should warn you, but not us. Ultimately the idea is that once you're kind of anxious about something right, your higher brain functions are going, if not shut off kind of be pushed aside.

00:06:24 Frank

And all you have to do is click the link to get your answer or whatever I mean.

00:06:28 Frank

It seems like these folks are well versed in this type of psychology.

00:06:33 Dana

Yeah, and they also know too that you know every when you're on your mobile, everybody is rush rush rush rush rush for rushing on the mobile phone all the time and that is a little scary because sometimes even when you look on the mobile you can't even see who it's from. It'll it'll you know. Just say a name or something like even some of the Apple ones that come out. Don't say oh it's from Apple, but that's not the exact. Doesn't show you the phone number or whatever it is. It's just.

00:06:55 Dana

Summer has put up there. As you know The Who it's from kind of thing, so yeah.

00:07:00 Dana

There's a lot of things we need to all.

00:07:01 Dana

Start doing or not doing.

00:07:03 Frank

Right, it's it's an interesting. It's just fascinating that with all this advances in cybersecurity, and I've seen a lot of the things that the technical we're not going to go into.

00:07:14 Frank

Humans are like the weak link.

00:07:16 Dana

Yeah.

00:07:18 Frank

That's crazy.

00:07:20 Dana

Yeah, definitely, and that's the frontline to most of the stuff and you know the urgency factor just to go back to that real quick one. Scam that that that is targeted at seniors.

00:07:29 Dana

Is the grandparent scam, and So what they do is they will call up and pretend that there's someone's grandson or granddaughter and something crazy happened like there's held hostage in a Mexican jail or something and they need to have money right away wired to them so that they can, you know, get out of there. So then to make it even sound more valid, they put the prison guard on the phone and they say, you know who?

00:07:49 Dana

This is the information. This is where you need to send it to, and he's a very stern person and these people really do fall for this and a lot of the people Western unions around the country. They they know that this.

00:08:00 Dana

Time is running rampant, so they'll try to stop people. I did a speech to speech the other day or whatever. I talked the other day and they were about probably about 1000 people on there and nobody said anything when I brought this up. And then at the end when we had the Q&A, there had to at least be 25 to 50 people. That said, my my mother fell for this and she would not believe that it wasn't my son. You know another one.

00:08:20 Dana

Edit There there there's a scam was that they said that their grandson was had drugs in the car and was with some guy that he was going fishing with and it was just one after the.

00:08:30 Dana

And a lot of the time that seniors won't even admit that this happens because they're embarrassed by it, and then they're afraid that their children, their adult children are not going to let them manage their finances. So again, it's a whole play. An urgency plan, emotion, and you're not even thinking straight. I mean, if somebody came up to you and said your grandson is in a Mexican jail right now.

00:08:50 Dana

And we need to give money. You do stop and think a little bit, but the way we act on line is very different than the way we act when we're here. We act on the phone when somebody calls, we want to believe them. Then we would act.

00:09:00 Dana

As if they were standing in front of us, so that's kind of some of the awareness that I like to to spread is safe. Just ask yourself if this person was standing here and this conversation was happening, would it sound crazy, you know?

00:09:11 Andy

So Dana, we talked a lot about the problem and how do we make ourselves shift gears like that? How do we engage, you know, Mentale in a way that maybe defeats the Sergeant.

00:09:25 Dana

Well, you know cybersecurity training has been, you know, going on over the years. The problem is getting bigger and bigger and bigger and we're throwing more and more money at it. And it's not getting any better, right? Yeah, so I say we need to approach it. I look at things a little bit differently, so usually it's the IT department that's responsible for putting together a program to teach the regular, non technical people.

00:09:46 Dana

You know?

00:09:46 Dana

What they need to do and not do so, they're forced to sit through an hours worth of training. They're about to fall asleep. All they want to do is be able to get through it so they can check off the box that they actually went. They did it, that's it, and I don't think that's the best way to teach people what I think we should do is we should start teaching them how they can protect themselves, their families, their homes. There's going to get some interests are going to say hey, you know that's.

00:10:10 Dana

I better call my mother and tell her to watch out for that, or I better make sure my son's not doing that and there's a there's a buy in there. So now once you get that buy in, there's an awareness that we need to start protecting things.

00:10:20 Dana

And then when you're talking about the at the company, you've already educated them on how they should be looking at their emails. Then now they know how that they need to be looking at the emails with the company, 'cause emails is pretty much where most of the problems are starting from, so so I just think it's if we looked at it a little bit differently, maybe we would be getting through to people a little bit different.

00:10:37 Andy

Well, I like your approach because we've already kind of walked through a lot of this, and we've said that it's not a technical issue at all, an.

00:10:45 Andy

Being a night person and Frank just Frank admitted earlier that were high functioning. You know, savants. Basically Frank and I were both 80 D and you know. And it's.

00:10:58 Frank

A normal account cards in Vegas though, which I totally feel shaded. I'm sorry, alright cut off, that's OK, it was funny.

00:11:06 Andy

Yeah, but you know it.

00:11:08 Andy

Having the app when you were just describing that I was imagining people that you know, even my you know my cellphone Frank doing this and we're like I said kind of high functioning but normal IT people and nothing against normal IT people I love you, I mean it but having them try to explain something nontechnical. 'cause if if we've identified that the issue is not really a technical.

00:11:31 Andy

Problem and we throw money at it and bought deer. Develop software that others have built and all of that really what's happening here is very psychological.

00:11:39 Andy

So I would. I would think that that that approach you just described having a non technical person walk through this, which sounds to me very emotional scenario that comes at you. You know on.

00:11:55 Andy

People you love an urgency and it's on your phone. And it's like every card that the scammers have is being played against. Especially older people who are not familiar but not as familiar with the technology as some of us.

00:12:08 Dana

Uh-huh absolutely absolutely. So I just think it's a different way to approach things and it it comes across as if you're giving the employee a benefit as opposed to forcing them to sit down because you need to protect the company.

00:12:20 Dana

Yeah OK, great.

00:12:21 Dana

So that's what I have to do, you know, kind of thing.

00:12:24 Andy

So we'll just envision mandatory training. Sorry, I just had a vision of office space of.

00:12:30 Andy

Well, you know, is this good for the company that banner?

00:12:33 Frank

Friday is Crazy shirt day.

00:12:39 Frank

There's a movie reference for the show, Andy, that could you?

00:12:45 Frank

I don't have my sound board.

00:12:46 Andy

You don't have your sound.

00:12:48 Frank

Now that's one of the disadvantages of switching to LinkedIn. Live will fix it. You know us where engineers Andy?

00:12:55 Frank

So the the question I guess is.

00:13:01 Frank

How do so? Yeah, I mean I think it was really insightful. Was you know my wife bought a bunch of studies of books to study for the CI, SSP and all that. And it's like a I mean, it's a it's a book and.

00:13:15 Frank

It's not technical, you're right. I mean, people are the weak link and I think.

00:13:20 Frank

People, and then that whole like you brought out the whole shame factor. Like I'm not going to admit like I mean that thing would happen to me. I got caught by our internal team, right? I was a year ago and I'm just admitting it now. Like you know. And and I did that on purpose because, well, I didn't hide it on purpose. Well, I guess I did, but I wanted to.

00:13:40 Frank

To point out is that there's not a lot of shame. I mean, the shame of this, I think is a big barrier, isn't it? To protection, isn't it?

00:13:47 Dana

Yeah, definitely it is. Yeah, we all have to get over that. Oh my goodness, I don't wanna be the one that you know.

00:13:51 Dana

Took the company down. I don't want to be the one that you know did this or let this in or what you know, whatever. Whatever the case may be, it's definitely a shame factor is is a big thing and and recognizing that the people are the biggest thing and one thing is that cyber security training, right? So it's going on a little bit here and there. The big companies much more so some of the smaller companies and medium size companies. There is nothing. It's like the Wild West going on out there so you know whatever you think your secretary is comfortable clicking on.

00:14:16 Dana

That's what she's clicking on.

00:14:17 Dana

So that's where we need to say, OK, this is a whole new industry and it's you know, it's it's it's it's. It's exploding right now and I think over the next three to five years cybersecurity training is going to be. It's going to be everywhere and everybody. Even the small companies are going to have to going to have to do something along those lines, but.

00:14:34 Dana

That being said, so because it's so new again, going back to the IT department, if you said to anybody five years ago, you know something about cybersecurity, they probably don't even really know what you're talking about. They say you need to talk to the IT department.

00:14:46 Dana

So we always just that pass up. Oh, that's a night thing we don't get involved in that. It's a night thing and like you we've all just been talking about it's not it's it's the people that IT thing might be perfect. You know maybe they have at the firewall or whatever all that stuff they need to do. But it's the people are just clicking on it, downloading things, you're going nowhere.

00:15:04 Frank

No, that's true. I mean, you can have the best firewall and all that packets like lock down to the teeth, but I mean if if somebody behind the firewall clicks on the.

00:15:13 Frank

Clicks on the link.

00:15:16 Frank

It's kind of like if you want to imagine like this is. This is the image I have is well, First off. I think the problem might be the term cyber security, right? 'cause when you hear the term cyber security I think of like somebody like with this type of monitor setup. You know like yeah right. You know like hacking away at the matrix or something like that like yeah.

00:15:35 Frank

No, it's not. It doesn't have to be. I mean, there's a....

About a year ago, I read AI Superpowers by Kai-Fu Lee which details the struggle between the US and China for AI supremacy in the 21st century,

That got me thinking about a map I once made for the School of AI.

The US vs China debate leaves out one key player: India.

Related Links

India- The next emerging superpower in artificial intelligence

https://smefutures.com/india-the-next-emerging-superpower-in-artificial-intelligence/

Original Livestream

https://www.linkedin.com/posts/frank-lavigne_the-third-ai-superpower-activity-6732059581536600064-1_3M

This episode kicks off Season 4 of the show and we are quite excited to have Rick Hall to talk to us about data analytics, entrepreneurship, and the impact of COVID on remote work.

About Rick Hall

Rick Hall  is a software entrepreneur focused on the analytics market. He has led the development of over a dozen software products and taken several companies from the early stage to an eventual sale. He has been working in analytics and software for 30 years and has been apart of the evolution of several generations of technology and practices. Currently, he is the CEO at Aginity Corporation--Supercharge your SQL Experience with Analytics Management. Aginity Corporation is the only next-generation analytics management toolset designed specifically to empower analytic teams to take advantage of the top analytic platforms.

Show Notes

Sponsor: Audible.com - Get a free audio book when you sign up for a free trial!

Notable Quotes

Welcome to Season 4! (01:00)

ImpactQuantum is our new podcast. (02:30)

Rick owns and operates Aginity Corporation. (04:00)

Shoutouts to Bill Baker and the BI Advisory Council. (05:00)

"Stuff changes." (Paraphrased) (08:00)

OG can stand for Old Guy or Original Gangster." - Frank (08:30)

Getting data to the place where someone can actually use it for Analytics. (09:00)

"First, you get the data," referring to ETL, data engineering, data integration, data quality... (09:45)

Regarding GPT-3 (11:45)

"34 ways to measure coupons..." (14:20)

"It's more of a biology problem." (14:50)

On answering questions at the speed of business. (15:45)

"So many business questions are answered, initially, in the heat of the moment." (17:30)

A really honest answer on predicting the unpredictable. (18:35)

"I think we'll be talking about Covid for the next 20 years." - Frank (20:00)

Wait - did (THE) Rick Hall just say he listens to Data Driven?? (21:15)

On business travel and remote work during the pandemic... (22:30)

Rick, on pay for software engineers in Silicon Valley. (23:30)

"Innovation Happens Everywhere" - Frank (25:25)

"Everyone hears the story of the Google's of the world..." (27:30)

Rick started a company 10 Sep 2001. (28:15)

"If you don't double-down at the moment of greatest risk, well, no one's going to do it for you." - Rick (29:00)

"This is probably not the easiest way to make money." - Frank, on entrepreneurship (31:00)

"Get it useful fast." - Rick on Lean (32:00)

On starting lean and The Lean Startup. (32:45)

On startups and the cloud... (35:45)

He said it again! (THE) Rick Hall listens to Data Driven! (36:40)

Did you find data or did data find you? (38:00)

"Just shut up and go do it!" - Rick's boss (39:00)

What's the favorite part of your current gig? (40:45)

When I'm not working, I enjoy ___. (42:00)

I think the coolest thing in technology is ___. (42:25)

On Microsoft Azure engineering time-to-market. (43:00)

"Ware definitely moving forward with an Iteration Economy." - Frank (43:30)

I look forward to the day I can use technology to ___. (44:00)

Share something different about yourself (44:30)

Andy's story of being diagnosed with ADHD around age 47. (45:00)

"Ok, I know where he gets this..." - Andy (46:00)

Frank has a bunch of desks in his office (46:10)

Learn more about Aginity.com! (46:40)

Aginity.com is free to start! (47:00)

Follow Rick on LinkedIn. (47:30)

Rick's recommended Audible listens: (48:35)

The Lean Startup

Lean Analytics

Crossing the Chasm

"I love podcasts which is how I came to yours." - Rick

Aginity is platform agnostic. (49:45)

Transcript (AI Generated)

In this Data Point, Frank visits the new Barnes and Noble location in Rockville, MD which is the first store in the US to sport the book retailer's new design. Oddly enough, it looks a lot like the Amazon brick and mortar bookstore just down the road in Bethesda. (see previous data point http://datadriven.tv/episodes/thoughts-on-amazons-brick-and-mortar-bookstore/ )

With less space and a revamped layout, you have to think that the store's design is much more data-driven. (Pun somewhat intended.)

In this episode, Frank and Andy explore voice assistants and the behind the scenes technology that makes them tick.

AI Generated Transcript

00:00:02 British Voiceover AI Lady

Hello and welcome to data driven, the podcast where we explore the emerging fields of data science, machine learning and artificial intelligence and will not be the only AI generated voice today. As Frank and Andy interview, my Cousins Alexa, Cortana, Siri and the Google assistant.

00:00:18 British Voiceover AI Lady

Now that I think of it, the Google assistant needs a proper name.

00:00:22 British Voiceover AI Lady

Doesn't it?

00:00:23 British Voiceover AI Lady

Without further ado, here are your hosts Frank Lavigna and Andy Leonard.

00:00:29 Frank

So we're both together and we're going to be talking about voice assistants and kind of how they work and.

00:00:38 Frank

Uh, we have some special guests with us today.

00:00:42 Frank

Welcome once again, if you're just joining us live. It's Andy later tonight we are here and we are live streaming, data driven podcast where we explore the emerging fields of data science, machine learning an artificial intelligence.

00:00:55 Frank

How are you doing Andy?

00:00:56 Andy

I'm doing pretty good Frank. How are you?

00:00:59 Frank

I'm doing well. I know you have a hard stop so I won't Yammer too long we have.

00:01:04 Frank

Three special guests with us today.

00:01:06 Frank

And E 3 three.

00:01:09 Frank

That's a record. It is a record.

00:01:14 Frank

These guests are.

00:01:19 Andy

Alexa Hello Alexa.

00:01:22 Frank

She's going to say hello back, I'm sure.

00:01:26 Andy

Yeah.

00:01:28 Frank

Cortana.

00:01:30 Andy

Hello Cortana.

00:01:33 Frank

And.

00:01:36 Frank

On my phone, I have Google Assistant.

00:01:38 Andy

Hello Google Assistant Hey Google.

00:01:41 Frank

That didn't work. It now correctly phones on. Let me tell you whenever there's a training video or like a keynote where they talk about the integration between them. It's pandemonium in my Home Office, because I usually have all three and it's just harder pandemonium.

00:01:59 Frank

So I want to switch to, so we're recording this last. If you're watching live. Thank you. If you're watching later, thank you. We always try to respond to the comments. I think we're pretty good about that. And if you're watching this, if you're listening to this on the podcast, I will try to transcribe everything I'm saying. So let me switch.

00:02:18 Frank

Here.

00:02:19 Frank

An I'll see if I can put us in the little bottom here, how do?

00:02:22 Frank

I do that.

00:02:24 Frank

There we go.

00:02:27 Frank

Oh well anyway.

00:02:30 Andy

So there we.

00:02:31 Andy

Are were there this is a closed.

00:02:34 Frank

Almost there, this is the. This is a quote.

00:02:38 Frank

From Charles the 5th, who if you're not up in your history he was kind of a big deal. I think he was a hapsburg. I don't remember shame on me but he has this quote where he says I speak Spanish to God, Italian to women, French to men in German to my horse.

00:02:57 Frank

Now you're probably wondering what the heck does this have to do with anything? Well, here's what it has to do with.

00:03:03 Frank

Oh no, PowerPoint is going to crash.

00:03:07 Frank

No, you can tell.

00:03:08 Frank

We're live here we go. This is what I want to say.

00:03:11 Frank

This is the my my modern take on this. I speak to Elexa when I'm home to Cortana. When I'm at work and Google Assistant when I'm in my car or have my phone with me.

00:03:24 Frank

You can also replace that with Siri. I don't. I do have an iPad, but it's not with me.

00:03:28 Andy

That's Frank, the 1st right.

00:03:30 Frank

Frank the 1st.

00:03:34 Frank

I rather like that I rather like that.

00:03:38 Frank

So the idea here is you know how do these things work.

00:03:41 Frank

You know what?

00:03:44 Frank

An you know, in terms of the guests and and kind of things and I know you have a A Time Constraint so I just want to kind of demonstrate something that I've had the chance for a work engagement had a chance to kind of study up on all three because it was a competitive situation between Louis.

00:04:03 Frank

Which is ultimately what powers Cortana, kind of behind the scenes, and Lex which is the Alexa version for processing text and dialogue flow, which is the Google version, so it's a lot of mouthfuls an I did. Let's see if we can get our guests to introduce themselves Alexa.

00:04:24 Frank

Hi how are you?

00:04:27 Speaker 3

I'm feeling like a home run.

00:04:29 Speaker 3

This weekend I'll be watching a lot of my favorite sports.

00:04:35 Frank

OK.

00:04:38 Frank

I'm getting a warning sign on my stream ability here, so I don't know what's going on.

00:04:42 Andy

What's up with that?

00:04:43 Frank

I don't know Well, you're still hear me so that's a good sign.

00:04:46 Andy

Yeah, you're you're good with me and I'm out here on the in the boondocks with 25 minutes bro.

00:04:50 Frank

There you go.

00:04:52 Frank

Hey Cortana.

00:04:54 Frank

How are you?

00:04:57 Speaker 4

Great thanks.

00:04:59 Frank

There you go.

00:05:00 Frank

And let's see what our friend Google Assistant.

00:05:03 Frank

Has to say.

00:05:10 Frank

Hey court, I'm sorry. OK Google, how are you?

00:05:18 Frank

Oops, it's on my Bluetooth, that's why OK.

00:05:22 Frank

You could tell where life looks 'cause it's just all bloopers.

00:05:27 Frank

How are you?

00:05:32 Frank

So we've returned a bunch of short search results, OK?

00:05:39 Frank

What's interesting about these three is that they're all trying to solve essentially the same problem, right? The they they are trying to solve.

00:05:46 Frank

The ability to take human language.

00:05:49 Frank

And type, it in and convert it to let me see if I get this screen back up.

00:05:55 Frank

An I will maximize that there we go see my fancy setup I do. It's cool, isn't it? Yes.

00:06:04 Frank

Alright, so ultimately they're all trying to say the same problem. Hey, we have a comment wise guy. Yes I am miserable. OK, alright, so here's the problem that all these devices want to solve, right? This is a human. This is some speaker device thingy.

00:06:21 Frank

Right?

00:06:23 Frank

And.

00:06:25 Frank

You have the cloud.

00:06:27 Frank

Which I think is really makes this.

00:06:29 Frank

Possible in a lot of ways or not. Just possible and practical? Yeah yeah.

00:06:34 Frank

I say.

00:06:36 Frank

You know, turn.

00:06:39 Frank

I have to be careful 'cause I actually do have the lights in my Home Office so.

00:06:43

Set up to this.

00:06:46 Frank

Right, right? So this gets digitized into audio.

00:06:51 Frank

Right?

00:06:52 Frank

Here right, I'll draw that by Squiggly Lines.

00:06:55 Andy

Right, I like to squiggly lines.

00:06:57 Frank

See, I'm talented, I'm very.

00:06:59 Andy

Hard you are. You're an artist.

00:07:01 Frank

Then a cloud service, right? Whether that's Louis.

00:07:07 Frank

Dialogflow

00:07:09 Frank

Or Lax.

00:07:12 Frank

Converts that into.

00:07:15 Frank

Back into text or into text, right? Right turn the.

00:07:20 Frank

Lights on.

00:07:27 Frank

Then what happens is then you have to figure out what does that mean. What's the context here, right? What's the intent? That's the official word.

00:07:34 Frank

So that's turn lights.

00:07:38 Frank

And then on now most people will argue with me. Is that technically this is the intent?

00:07:43 Frank

And this is the the destination or slot.

00:07:48 Frank

Lex calls us a slot and this is the state that you want, right? So ultimately there's 100 different ways I can say that, and this is what makes the really kind of an LP problem, right? Please turn the lights on or do would you kindly turn the lights on right bioshock?

00:08:02 Frank

Right there for you.

00:08:05 Frank

Um?

00:08:06 Frank

That sort of thing, and then whatever that happens, is that this will then parse that into an action, right?

00:08:12 Frank

Which, if you have smart plugs, it will then send a message back through the magic of the Internet and then turn the actual.

00:08:20 Frank

Oh, I like how that's doing that. Turn the actual light on.

00:08:27 Frank

Right, so that's that's basically solving the same problem.

00:08:30 Frank

Right?

00:08:32 Frank

And what's interesting about this? I just realized I didn't say it out loud for folks listening on the podcast, but ultimately what happens is my words get translated into an electronic signal, right? A sign? A wave of sorts.

00:08:45 Frank

And then that is then.

00:08:47 Frank

Re on the other side, it's then sent from the speaker to the cloud, where it will turn those that sound form that sound wave back into text, right? Or words and then it'll go through and it'll parse out.

00:09:02 Frank

What I'm saying is try to get an intent from it or an action to it, and then based on that, some other program that also lives in the cloud.

00:09:11 Frank

Mostly, we'll then take an action based on that. Does that make sense like that? Explain that clearly.

00:09:17 Andy

I think so yeah, yeah I like it. I like the flow.

00:09:21 Frank

Yeah, and it's it's it's.

00:09:22 Frank

Amazing how simple this is, right? This is not rocket science inside your average in inside your average you know echo device. You know it's not rocket science, it's just well, this one is the fancy one with the screen, but you know the the typical kind of .1 or whatever is a microphone and speaker in a Wi-Fi connection. It's essentially all it is, right?

00:09:42 Frank

So ultimately the the goal then is that let me see if I can D minimize minimize this. So the the goal is is that I have an example of that, and this is essentially a build your own voice kit that I saw at Micro Center for.

00:10:01 Frank

Like $5 or something like that.

00:10:03 Frank

An inside is a speaker, a button, and a Cardboard box.

00:10:09 Frank

And if you attach your Raspberry Pi to this.

00:10:12 Frank

You basically have a Google home assistant.

00:10:17 Andy

That's nice, yeah.

00:10:19 Frank

Shame on me because I bought this longer ago than I care to admit and I haven't built it yet.

00:10:26 Frank

But that's just to demonstrate. The point is that these these actual devices are rather simple in terms of, you know, just them being their own thing, right? So what's interesting about this, and this is where the cutting edge comes is when you when I talk.

00:10:41 Frank

We have our human brains or whole.

00:10:44 Frank

Some will debate about.

00:10:45 Frank

Whether or not I have a human brain, but let's let's go with you.

00:10:49 Frank

So.

00:10:51 Frank

The short of it is, is that.

00:10:54 Frank

I have the ability to understand context right from my previous statement.

00:10:58 Frank

So I'm going to mute some of these devices because if I start to hear their name, they'll start going wild. What's interesting is how good Cortana is at this. How good the Google assistant is at this, and how.

00:11:14 Frank

Alexa needs some room for improvement, right, right? So for instance, if you haven't caught on the shirt I'm wearing says cream cash rules everything around me, that's from a Wu Tang clan song, so I will ask this simple question from Alexa Alexa, who is the Wu Tang clan.

00:11:36 Speaker 3

According to Wikipedia, Wu Tang clan is an American hip hop group formed in Staten Island, NY city in 1992 original.

00:11:45 British Voiceover AI Lady

Hopes.

00:11:46 Frank

Alexa.

00:11:48 Frank

What was their first album?

00:11:51 Speaker 3

According to Wikipedia, the first album is the debut studio album by German dual Modern Talking. It was released on April 1st, 19.

00:11:59 Frank

80 so you get the idea you and I know like if you asked me who they who the Wu Tang clan were an, then what was their first album? I would tell you right, right?

00:12:09 Frank

It does not have the notion of context. This is turns out to be very difficult problem for computers to solve. OK, because.

00:12:19 Frank

There's a lot going on, right? So if I start talking to you is like handy. I was at this great restaurant last night that and then we switch to another.

00:12:27 Frank

Topic.

00:12:28 Frank

Then

00:12:29 Frank

We would, we would then say, Hey where was that place? And then I would kind of know if you said place I would know what you were talking about right? That is humans have trouble with this right? 'cause I have many conversations with my wife that kind of go in different directions 'cause I have no idea where she's talking about.

00:12:47 Frank

But I mean it's hard for humans. It's really hard for machines, so let's try and see if Cortana does this any better. Hey Cortana?

00:12:54 Frank

Who is the Wu Tang clan?

00:12:58 Speaker 4

According to wikipedia.org Wu Tang, clan is an American hip hop group formed in Staten Island, NY city in 1992. Originally composed of rza.

00:13:10 Frank

Hey Cortana, what was their first album?

00:13:15 Speaker 4

Should I read a snippet from Wikipedia?

00:13:17 Speaker 4

That might be related.

00:13:19 Frank

Yeah, I'm afraid.

00:13:23 Speaker 4

The Wu Tang clan is a NYC based hip hop musical group consisting of 10 American rappers, rza, gza, Method Man, Raekwon, Ghostface Killah.

00:13:34 Frank

There's a lot of members of the Wu Tang clan. In case you didn't know.

00:13:37 Speaker 4

Cappadonna and the label dirty *******

00:13:42 Frank

Hey Cortana, what was their first album?

00:13:49 Speaker 4

There might be something on Wikipedia.

00:13:51 Speaker 4

Should I read it?

00:13:53 Frank

Yeah.

00:13:56 Speaker 4

The Wu Tang clan is a NYC.

00:13:58 Frank

Based all right?

00:13:59 Frank

Well, in the past she did get that right.

00:14:03 Andy

Well, she wasn't completely off base, wasn't completely off. Now she she kept it. Seems like some kind of workflow thing put her into.

00:14:11 Andy

It shot well at at least identify the context back to your previous question.

00:14:16 Frank

It did on that's a new active. That's a new behavior. I swear I I used to do this demo all the time and depending on the audience it would be Wu Tang clan or you know Aerosmith, you know. So let's see what Google has to say. OK, Google.

00:14:32 Frank

Who is the Wu Tang clan?

00:14:39 Frank

Alright, you're not very talkative today.

00:14:45 Frank

What was their first album?

00:14:50 Frank

OK, the demo gods are not kind to me today.

00:14:54 Frank

But in the past this has worked on.

00:14:56 Frank

On home assistant, an Cortana.

00:15:00 Frank

OK, so.

00:15:05 Frank

So the reason?

00:15:05 Frank

Why we're doing this today, and I know Andy has a hard stop in a couple of minutes is because we are hoping to get data driven as a flash briefing on Alexa.

00:15:15 Frank

And.

00:15:17 Frank

Alexa.

00:15:20 Frank

So I was trying to do this whole surprise thing, but apparently since the demo failed, I figured I'd break into that.

00:15:27 Frank

Into that, but that's ultimately the goal. But I also think this is an interesting, interesting topic, because for a lot of folks, this is just this magical black box. There is listening, right? An you know it's not magical and it all comes down to math and science, right? An and the key is to understand, kind of how it's built. And once you understand how it's built, you can build your own systems and it's actually not that hard.

00:15:47 Frank

There are more moving parts than you would think, but ultimately it just comes down to.

00:15:53 Frank

You know you're taking that speed that sound data, converting it into text, then taking that text and then converting that back into some kind of intent in action, right?

00:16:04 Frank

Yeah, and then on the other side, I'm sorry, go ahead.

00:16:07 Andy

No, Mark Taylor just said it's a do loop and he's right, he's.

00:16:10 Frank

A do loop. We have Mark joining us again. Thanks for watching mark.

00:16:14 Frank

I really should ask this.

00:16:17 Frank

But unfortunately to be is a bit of a bit of A.

00:16:21 Frank

Not a nice word or not a professional word for LinkedIn.

00:16:25

Yeah.

00:16:28 Frank

But they don't have enough memory. I think not at all.

00:16:33

No they don't.

00:16:34 Frank

But it's an interesting. It's an interesting thing where you, you know, 'cause I'm a nerd. I have I happen to have all three different types, but you know, actually 4 if you count Siri. Let's see if Siri will do any better on the on the album question.

00:16:49 Frank

So Andy, we actually have 4 special guests.

00:16:52 Andy

Wow, thank you.

00:16:54 Andy

Not crazy, that's that's a new record.

00:16:56 Frank

Hey Siri, who is the Wu Tang clan?

00:17:03 Speaker 4

Here's some information.

00:17:05 Frank

Alright, so she basically.

00:17:07 Frank

Pointed to Wikipedia.

00:17:13 Frank

What was their first album?

00:17:25 Frank

So it did the transcription.

00:17:27 Frank

What I said is good.

00:17:30 Speaker 3

I don't recognize this song.

00:17:32 Andy

OK oh OK.

00:17:34 Frank

So I swear this it did work before, but I mean ultimately it's a very hard problem. In fact, one of the things that they showed a couple of years ago at ignite I or build.

00:17:44 Frank

They showed this concept video of this lady talking to Cortana and it was on her phone.

00:17:51 Frank

More on that in a minute. It was on her phone an as she was driving into work. She'd be like, Oh, remind me to tell this person.

00:18:00 Frank

You know have a meeting with them.

00:18:03 Frank

And then the the logic would then go and then schedule the meeting through the through the outlook calendar and then tell her you know so and so rejected the request. But they are able to meet 30 minutes later. Is that OK? Yes, oh and invite so and so to this meeting as well.

00:18:20 Frank

Right,...

This episode is entitled "This, Too, Shall Pass" and it was recorded Tuesday the eighth of September in this foul year of our Lord two thousand twenty. 

Frank and Andy tend to wander off the old conversational trail. 

But you knew that already. 

Thanks for listening to the Data Driven podcast.  Visit us on the web at datadriven.tv and be sure to like us on Facebook. 

(Bonus points to you if you caught the Hunter Thompson reference in the intro)

Recorded Live:

https://www.youtube.com/watch?v=Tevc7Wr68OE

Transcription Coming Soon

In this DataPoint, Frank examines whether or not the new AI voice over tech really replaced a human or did it open up new creative options instead?

Transcript 

Speaker 1 

Hey, what's up? It's Frank here. 

Speaker 1 

From data driven the podcast where we explore the emerging fields of data science machine learning and artificial intelligence, so the title of this data. Point is did AI take just take away someone's job. Well, yes, and no so here's an example so. 

Speaker 1 

So rather, quantum answer, isn't it right? It's both yes and no at the same time. See what I did there? So this is actually in regards to the voice over artist that we used to have on the show, but for both data driven and. 

Speaker 1 

Impact quantum but. 

Speaker 1 

I just recorded something today for impact quantum, so this isn't this isn't just a cheap kind of product placement for the other show. This is a serious thing, so if we go and we listen to this. 

Speaker 2 

Hello and welcome to this episode of impact quantum. This episode is titled freaking cubits how do they work? 

Speaker 1 

So basically that is an artificially an AI generated voice that we've been using. 

Speaker 1 

Probably since the three year anniversary prior to that we used someone an voiceover artist I found on fiber called shifty pop. Awesome work that she does. 

Speaker 1 

Um and her turn around is pretty quick too, but. 

Speaker 1 

She also doesn't do voiceover work anymore. She just singing kind of stuff which is still cool. So definitely check her out and tell her data driven center sent you. But the key here is that. 

Speaker 1 

We would love to be in a position where budget Wise. We could have a voiceover artist custom do this. But just was never practical right for every show, however, with the AI. 

Speaker 1 

I can. 

Speaker 1 

Create a custom intro for every show and eventually a custom outro outro at the end too. 

Speaker 1 

See we've done that were on data driven a few times an every episode of impact quantum has been that now part of that is just you know, practical right so I can type up what I need to type have the voice over artist say tweak the voice settings or whatever, although we have kind of a setting we like. 

Speaker 1 

And hit generate and I have a wave file right away for MP3 actions. What generates. 

Speaker 1 

Right away, right? So I have that instantaneous feedback, right? So there's the time and it doesn't cost me anything extra to do that. I I I spent $30 or something on some web based platform so it can actually pull in voice wave voice generation capabilities from Google, Amazon as well as as Azure so I have. 

Speaker 1 

All that ability kind of depict the voices. Pick the accents. I can even do a child's voice a man's voice. I mean, it's obviously a lady's voice. I can do that. I can do that right away. I paid for it basically one time and I can get that. So in a sense. 

Speaker 1 

I was actually having a discussion with my manager. Actually, wow, you've put somebody out of work. 

Speaker 1 

And yes and No. 

Speaker 1 

So I hired a voiceover artist three years ago. 

Speaker 1 

Yeah, 3 1/2 years ago an I paid her I think was like ended up being $50 or so. So for less than the cost of re engaging her to do a voiceover I now can create custom voiceovers with different voices, different accents, different gender. 

Speaker 1 

I can do all sorts different ages. I could do all sorts of things there, where as before I, I guess. I guess I could go through fiber and find that selection, but I can't do it on demand and a lot of case you haven't figured this out by now. A lot of what Andy and I do is ad hoc. We don't really do we do preparation, but not to the degree that I think. 

Speaker 1 

We present it, we do so I think that what what? This gives us the agility an the cost point. So in a sense yes. did I replace a human being with an AI generated voice? Yes I did, but I wouldn't say that. 

Speaker 1 

I put her out of work because I wasn't going to engage her anyway because it $30 to $50 or more per engagement. 

Speaker 1 

Wasn't going to do it anyway. 

Speaker 1 

Right, so this gets into that. That real question have I replaced? 

Speaker 1 

A person and the answer is yes and no. In in, in the strictest sense, yes. But honestly, I really wasn't going to engage her for at least another year to do another voice over. 

Speaker 1 

You know the podcast isn't well monetized right now. Speaking of monetizing. 

Speaker 1 

You can check out this cool shirt I'm wearing. If you're watching the video, it's the data graffiti shirt. Just search for it on Amazon data graffiti. It looks an awful lot like the obey stickers you might have seen up and down East Coast, and I think I've seen it in London a few times. 

Speaker 1 

Once you see it, you'll kind of. It'll trigger your memory. Also, we are looking for sponsors, so if you want to sponsor this show, hit me up. 

Speaker 1 

But so in a sense. 

Speaker 1 

AI has opened up an opportunity for us that was really kind of closed before. 

Speaker 1 

And I'm sure there's a fancy economic word or economic model for this, but this is just something AI has enabled that really wasn't going to spring the money for a custom voiceover. 

Speaker 1 

For every show. 

Speaker 1 

So I don't know. I think this is worth further discussion, but I also think you know it's not exactly. 

Speaker 1 

It's not as a clear cut answer yes or no. It's it's very quantum if you will. 

Speaker 1 

So with that. 

Speaker 1 

I'm going to. 

Speaker 1 

Wish you a good day and hope you have a great weekend. 

Like Star Trek in the 90s we are creating a spin off series.

The new show is called Impact Quantum and will focus on quantum computing.

Additionally, Frank and Andy explain how they keep creating content despite having full schedules.

In this episode, Frank and Andy talk about why Data Engineering may be the next hot career, how Microsoft's culture has changed, and Frank's solar power experiments.

Transcription & show notes coming soon.

In this episode Frank and Andy talk about the "three Rs" of the 2020s: robots, retail, and reskilling.

Original live stream link:

https://www.linkedin.com/posts/frank-lavigne_data-driven-live-robots-data-and-retail-activity-6687056930667548672-tVKq

Transcription

coming soon

In this Data Point, Frank sees a robot patrolling the aisles of his local Walmart and gets excited.

The robot scans shelves and helps identify what needs to be restocked and what's out of place.

https://www.businessinsider.com/walmart-adding-robots-help-stock-shelves-to-650-more-stores-2020-1

In this episode, Frank and Andy share their thoughts on three years of podcasting, stoicism, and climbing Mount Royal.

Show Notes

This is the first show that we recorded via live stream. It also marks the debut of our AI voice over talent.

Sponsor

Get a free audiobook on us at http://thedatadrivenbook.com/

Transcription (AI Generated)

The following was generated by YouTube's caption system.

0:00:03.200,0:00:15.540

hey Andy how it's going good how are you

0:00:06.600,0:00:16.830

good I'm seeing a black screen and for

0:00:15.540,0:00:21.779

some reason the audios being piped

0:00:16.830,0:00:27.150

through you know are you input should be

0:00:21.779,0:00:29.640

my my camera does on the pair of B let

0:00:27.150,0:00:36.480

me try turning it off and back on again

0:00:29.640,0:00:40.670

I know you have a call so for those of

0:00:36.480,0:00:43.440

you joining us on YouTube and our

0:00:40.670,0:00:45.989

Facebook live page Andy and I are doing

0:00:43.440,0:00:49.039

an experiment and what's data science

0:00:45.989,0:00:53.489

without experiments right Andy so true

0:00:49.039,0:00:55.980

so how's my audio your audios awesome

0:00:53.489,0:01:00.469

okay could you hear

0:00:55.980,0:01:05.700

all right I've turned my camera on main

0:01:00.469,0:01:07.680

using the app that came with it so the

0:01:05.700,0:01:10.350

software that we were explaining for

0:01:07.680,0:01:14.220

folks and for you Andy I'll bring our

0:01:10.350,0:01:18.960

listeners into this the image we haven't

0:01:14.220,0:01:20.790

started three years ago plus or minus a

0:01:18.960,0:01:27.229

few weeks we wanted to hold off on the

0:01:20.790,0:01:30.060

celebrations for a number of reasons and

0:01:27.229,0:01:33.840

we originally envisioned this show to

0:01:30.060,0:01:37.110

become a video podcast so technology and

0:01:33.840,0:01:40.770

costs have come down that if Sumi Annie

0:01:37.110,0:01:45.360

gets his camera going we will be able to

0:01:40.770,0:01:49.770

do there we go I see yeah I am here I

0:01:45.360,0:01:53.250

found the Settings button awesome so

0:01:49.770,0:01:58.229

this is good this is good so we have the

0:01:53.250,0:01:59.219

ability now to kind of do something more

0:01:58.229,0:02:01.350

long a lot to think what we were

0:01:59.219,0:02:03.719

originally envisioned so as awesome as

0:02:01.350,0:02:05.520

you may think the show has been we

0:02:03.719,0:02:08.929

actually had even we had even grander

0:02:05.520,0:02:11.489

plans so this is just an experiment

0:02:08.929,0:02:12.770

might even put this live on the feed is

0:02:11.489,0:02:14.420

kind of like a

0:02:12.770,0:02:17.300

call it a data point how about that Andy

0:02:14.420,0:02:18.860

I like it I like that a lot because the

0:02:17.300,0:02:21.770

advantage is that because I'm using a

0:02:18.860,0:02:24.110

product called restream that I can pipe

0:02:21.770,0:02:25.340

two different output so this is actually

0:02:24.110,0:02:28.190

going to Frank's world TV YouTube

0:02:25.340,0:02:31.400

channel our Facebook live feed and

0:02:28.190,0:02:35.180

because of the magic of automation this

0:02:31.400,0:02:38.930

is also going to be I'm actually going

0:02:35.180,0:02:41.360

to once this ends will see that it

0:02:38.930,0:02:45.530

should pick up the arm the video feed

0:02:41.360,0:02:47.570

from Facebook and then pipe that into an

0:02:45.530,0:02:50.870

mp3 file which should be ready for

0:02:47.570,0:02:56.180

upload to the scene so again it's data

0:02:50.870,0:02:57.490

science right in data magic it's not

0:02:56.180,0:03:01.400

science

0:02:57.490,0:03:03.890

I told that to customers a lot like you

0:03:01.400,0:03:05.690

know it's ok to fail because it's called

0:03:03.890,0:03:09.740

data science it's not in Dean in the

0:03:05.690,0:03:11.660

perfection so you know and and silently

0:03:09.740,0:03:13.700

calling it science what you say well it

0:03:11.660,0:03:19.010

failed but you know we weren't sure it

0:03:13.700,0:03:20.600

was gonna work so it's kind of so how's

0:03:19.010,0:03:23.270

it going I know you have a call in like

0:03:20.600,0:03:27.380

five minutes but yeah it's I'm I'm

0:03:23.270,0:03:29.150

waiting on someone and if they if they

0:03:27.380,0:03:32.000

don't show up that that's ok they're

0:03:29.150,0:03:34.010

busy it's a regular call with with

0:03:32.000,0:03:37.190

someone who subcontracts with me and

0:03:34.010,0:03:39.620

he's older but he is a data scientist as

0:03:37.190,0:03:42.140

well and he sometimes gets distracted

0:03:39.620,0:03:43.550

heads down that's why you pinged me

0:03:42.140,0:03:45.080

about five minutes till the call I was

0:03:43.550,0:03:46.280

like well I got a call in five minutes