6 avsnitt • Längd: 40 min • Veckovis: Tisdag
Intrepid Growth Partners’ Senior Advisors Rich Sutton (pioneer of reinforcement learning), Sendhil Mullainathan (MacArthur Genius recipient), and Niamh Gavin (Applied AI scientist) join Intrepid partner and co-founder Ajay Agrawal to explore what’s possible with the entrepreneurs implementing AI-based solutions and pushing out the productivity frontier.
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The podcast The Derby Mill Series is created by Intrepid Growth Partners. The podcast and the artwork on this page are embedded on this page using the public podcast feed (RSS).
Intrepid partner Ajay Agrawal and senior advisors Rich Sutton, Sendhil Mullainathan and Niamh Gavin are back to dig deep in this episode all about using artificial intelligence to increase the efficiency of mining exploration. That’s the act of using machine-learning techniques to analyze information from the earth, such as core samples, to decide multi-million-dollar questions, like where to build a mine or whether to expand an existing operation.
Our guests are CEO Grant Sanden and President of Resource Modelling Solutions Jared Deutsch from GeologicAI, a Calgary-based company that redefines geological and mining decision-making with advance core-scanning technology and AI-powered analytical and modelling solutions. From Sanden:
“You've got challenges in mining… You know, you're only touching a trillionth of the deposit… And it really is a structural problem in prediction… but then once you can deal with that well, you're now characterizing uncertainty. And with these new tools, we can plan through more robustly with uncertainty properly quantified, which is a challenging endeavour.”
And from President RMS Jared Deutsch:
“The application of AI and mining is so unique because we're so data-poor spatially, but so data rich, thanks to scanning and many other technologies, where we have millimetre-scale data. Challenge is, we're 100 meters away from our next millimetre scale data. So this makes for a very challenging problem in a very non-stationary environment, where no mineral deposit is like another one. And we can't really afford to sit around for a few 100 million years and wait to see how these things evolve. So it makes for a really fun and exciting application of AI, but a bit unique compared to other areas.”
EP 05 HOSTS
Ajay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, MacArthur Genius grant recipient and professor, MITNiamh Gavin, Applied AI scientist, CEO, Emergent Platforms
LINKS
GeologicAI website and a short explainer video highlighting a GeologicAI use case.GeologicAI CEO Grant Sanden LinkedInRMS President Jared Deutsch LinkedInRich Sutton’s home page. Follow Rich on XSendhil Mullainathan’s website. Follow Sendhil on XBe sure to catch every episode by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts
DISCUSSION POINTS
00:00 Introduction01:23 Meet the GeologicAI team, and learn what the company does04:22 Challenges and opportunities in mining data05:41 Deutsch describes how unique mining exploration is as an AI application06:53 Mullainathan asks about human-algorithm interaction08:07 Sanden explains AI- and human-algorithm approaches10:41 Gavin compares mining and healthcare as AI applications12:23 Sutton on the way AI can create a super geologist14:33 Sanden on the scale of GeologicAI’s operations15:48 Mullainathan asks about optimizing the data collection17:41 Agrawal on the extreme length of learning loops in mining19:44 Mullainathan: Are there ways to reduce the 20-year lag?25:13 The challenge of optimizing the data-collection cycle27:24 Agrawal describes the mine of the future30:08 The optimal path from limited loops to ultimate loops31:00 Closing remarks
NUGGETS (short excerpts from the full episode)
NUGGET 01: Human-Algo Interaction
AIs learn from human feedback. Humans learn from AI predictions in edge cases. Sendhil Mullainathan and Grant Sanden discuss what this human-algorithm interaction might look like at the limit.
NUGGET 02: Super Geologists
AIs have the opportunity to learn from more core sample examples than any person. We know about the impact of adding more data to training sets to enhance performance. How accurately can we estimate the marginal benefit to adding a bit more data relative to the cost of collecting it? Rich Sutton questions whether we can imagine any geologist that will be better at mineral classification than the best AI.
NUGGET 03: Data Strategy
How does data collection via following the "natural order of things" differ from the optimal data collection strategy? A 20-year feedback loop seems crazy ("a little bit of a time lag"). Sendhil Mullainathan and Jared Deutsch discuss how to decrease the feedback loop.
NUGGET 04: A cheaper alternative to mining cores?
In the prior clip, we discussed the shifting value of core samples. In this case, Grant Sanden and Niamh Gavin consider other, much cheaper data sources (chips, dust, aerial imagery) that might also provide predictive power regarding hidden underground mineral deposits. Sendhil Mullainathan discusses how new forms of high-fidelity prediction that are orders of magnitude cheaper, although perhaps less accurate, might transform the fundamental economics of the mining industry.
DISCLAIMER
The content of this podcast is for informational and educational purposes only and should not be construed as marketing, solicitation, or an offer to buy or sell any securities or investments. The opinions expressed in this video are those of the participants and do not necessarily reflect the views of Intrepid Growth Partners or its affiliates. Any discussion of specific companies, technologies, or industries is for illustrative purposes and does not constitute investment advice. Viewers are encouraged to consult with their own financial, legal, and tax advisors before making any investment decisions.
The new environment for global trade is dominating discussions in many business sectors, including artificial intelligence. To discuss the implications for global software companies and start-ups, Intrepid Growth Partners co-founders Dr. Mark Machin, Mark Shulgan and Ajay Agrawal arranged a conversation with global trade expert Marc L. Busch, a professor of international business diplomacy at Georgetown University. On the agenda: How may trade conflicts affect technology entrepreneurs and the development of machine learning applications? What can global tech companies do to protect themselves? And what are Prof. Busch’s predictions for how this all plays out?
EP 04 HOSTS
Marc L. Busch is the Karl F. Landegger Professor of International Business Diplomacy at the Walsh School of Foreign Service, Georgetown University, and a Global Fellow at the Wilson Center’s Wahba Institute for Strategic Competition.
Dr. Mark Machin, co-founder and managing partner, Intrepid Growth Partners
Mark Shulgan, co-founder and partner, Intrepid Growth Partners
Ajay Agrawal, co-founder and partner, Intrepid Growth Partners
LINKS
Derby Mill show website: https://insights.intrepidgp.com/podcast
Marc L. Busch’s personal website. Follow Marc on X and LinkedIn
Recent Marc Busch article on how “mode 5 services” can promote U.S. manufacturing without imposing new tariffs
DISCUSSION POINTS
00:00 Introductions
03:10 Ajay Agrawal introduces Professor Marc L. Busch
03:54 Busch on the legal bases for tariffs and executive orders
09:56 Non-Tariff Barriers and Intellectual Property
19:56 Impact on Software and AI Companies
26:26 Advice for Canadian and European AI Companies
29:16 Stargate, tariffs on semiconductors and subsidies as offsets for harm
33:46 Predictions on how this will play out amid political considerations
37:04 Potential for retaliation via anti-trust measures
40:23 Role of the WTO and International Compliance
45:32 Advice for Canadian AI companies
53:54 Lighting round: What should Canadian entrepreneurs ask their politicians to do?
54:53 How can Canada and the UK prevent a brain drain to US?
55:59 What should UK entrepreneurs ask their government to do?
56:41 Wrap up
DISCLAIMER
The content of this podcast is for informational and educational purposes only and should not be construed as marketing, solicitation, or an offer to buy or sell any securities or investments. The opinions expressed in this video are those of the participants and do not necessarily reflect the views of Intrepid Growth Partners or its affiliates. Any discussion of specific companies, technologies, or industries is for illustrative purposes and does not constitute investment advice. Viewers are encouraged to consult with their own financial, legal, and tax advisors before making any investment decisions.
In the first of our “unpacked” episodes, Intrepid partner Ajay Agrawal leads our senior advisors Rich Sutton, Sendhil Mullainathan and Niamh Gavin in a conversation that further explores the themes that arose in episode one. That episode featured a conversation with Rae Jeong, CEO of Maneva, which is using AI and reinforcement learning (RL) techniques to move factories toward autonomous operations.
In this episode, the team discusses the importance of making factories more "RLable" to enable incremental changes and ultimately achieve radical improvements. We explore the importance of continuous training data, the role of humans in active learning, and the balance between exploration and exploitation. The conversation highlights the challenges of implementing RL in manufacturing, such as the need for selective instrumentation and the potential for synthetic data.
EP 03 HOSTS
Ajay Agrawal, co-founder and partner, Intrepid Growth Partners
Richard Sutton, pioneer of reinforcement learning and professor, University of Alberta
Sendhil Mullainathan, MacArthur Genius grant recipient and professor, MIT
Niamh Gavin, Applied AI scientist, CEO, Emergent Platforms
LINKS
Derby Mill show website: https://insights.intrepidgp.com/podcast
The first episode featuring Maneva CEO Rae Jeong
Maneva AI website
Maneva CEO Rae Jeong LinkedIn
A short video about Maneva’s work transforming Laura Secord chocolate production
Rich Sutton’s home page. Follow Rich on X
Sendhil Mullainathan’s website. Follow Sendhil on X
DISCUSSION POINTS
00:00 Introductions and opening credits
01:39 Clip: Rae Jeong discusses Maneva's approach to autonomous factories
02:01 Rich Sutton comments on the challenge of active learning in operating factories
04:54 Niamh Gavin on the use of simulated environments for experimentation
06:29 Rich Sutton: “It’s hard to compete with a human” for experimentation
08:05 Can simulation actually recreate a factory in all its complexity?
09:42 Sendhil Mullainathan is confused where Maneva actually uses RL
10:41 Balancing exploration and exploitation
14:52 Discussion of temporal credit assignment in manufacturing
15:54 Clip: Sendhil asks how Maneva uses labels and exploration
17:42 Clip: AI needs to conduct exploration to achieve continuous improvement
16:34 Exploring the future of manufacturing with reinforcement learning
19:29 The challenge of making factories more “RL-able”
23:01 Why prediction tends to come before control
28:55 Discussion of selective instrumentation and the role of humans
32:09 Sendhil asks, do you know why EKG leads are placed where they are?
34:28 Clip: Temporal credit assignment and taking RL to the limit in factories
38:28 Sendhil emphasizes the need for a CEO-level sale for RL in manufacturing
44:00 Challenges of fully instrumenting a factory
49:00 Algorithms identifying valuable measurements
52:42 Conclusion and final thoughts
DISCLAIMER
The content of this podcast is for informational and educational purposes only and should not be construed as marketing, solicitation, or an offer to buy or sell any securities or investments. The opinions expressed in this video are those of the participants and do not necessarily reflect the views of Intrepid Growth Partners or its affiliates. Any discussion of specific companies, technologies, or industries is for illustrative purposes and does not constitute investment advice. Viewers are encouraged to consult with their own financial, legal, and tax advisors before making any investment decisions.
The Chinese tech start-up DeepSeek used reinforcement learning and other creative techniques to develop an ultra-efficient chatbot that was less costly to make, uses fewer chips and requires much less electrical power than better-known alternatives, such as OpenAI’s ChatGPT or Anthropic’s Claude.
To discuss the implications, Intrepid Growth Partners gathered the Derby Mill team, including the pioneer of reinforcement learning himself, Richard Sutton, as well as Sendhil Mullainathan and Niamh Gavin, all of whom are Intrepid GP senior advisors. The team joins show host and Intrepid partner Mark Shulgan along with special guest Kevin Bryan, economist and co-founder of the AI start-up, All Day TA.
Questions our hosts discussed:
* How can DeepSeek perform as well as OpenAI's most advanced technology for many tasks—but operate at a fraction of the cost?
* What potential economic effects could result from DeepSeek’s open-source code and technical specifications?
* What implications does DeepSeek have for investors seeking strategies to invest in the future of AI?
* We’ll also make some predictions about where things go from here.
LINKS
* Derby Mill show website: https://insights.intrepidgp.com/podcast.
* The DeepSeek academic paper that started it all. Plus: DeepSeek’s website.
* Find Kevin Bryan on X @afinetheorem and on Bluesky @afinetheorem.bsky.social. His website is kevinbryanecon.com.
* See Kevin Bryan’s start-up, All Day TA, which provides AI assistants for university professors.
* Rich Sutton’s home page. Follow Rich on X @RichardSSutton.
* Sendhil Mullainathan’s website. Follow Sendhil on X @m_sendhil.
* Ajay Agrawal’s website. Follow Ajay on X @professor_ajay.
DISCLAIMER
The content of this podcast is for informational and educational purposes only and should not be construed as marketing, solicitation, or an offer to buy or sell any securities or investments. The opinions expressed in this video are those of the participants and do not necessarily reflect the views of Intrepid Growth Partners or its affiliates. Any discussion of specific companies, technologies, or industries is for illustrative purposes and does not constitute investment advice. Viewers are encouraged to consult with their own financial, legal, and tax advisors before making any investment decisions.
In the premiere of the Intrepid Growth Partners’ podcast, we meet with Rae Jeong, the CEO of Maneva AI, a Toronto-based company whose mission is to use artificial intelligence to make factories autonomous—completely run, maintained and improved by machine-learning algorithms and manufacturing robots.
Rae joins our panel of experts:
Ajay Agrawal, co-founder and partner, Intrepid Growth Partners
Richard Sutton, pioneer of reinforcement learning and professor, University of Alberta
Sendhil Mullainathan, MacArthur Genius grant recipient and professor, MIT
Niamh Gavin, Applied AI scientist, CEO, Emergent Platforms
“The ambition that we have… is to leverage some of the work that [Derby Mill host Richard Sutton] pioneered in reinforcement learning,” says Jeong, who foresees a future with zero workforce injuries and where the cost of production is simply the cost of energy.
LINKS
Derby Mill show website: insights.intrepidgp.com/podcast
Maneva AI website
Maneva CEO Rae Jeong LinkedIn
A short video about Maneva’s work transforming Laura Secord chocolate production
Rich Sutton’s home page. Follow Rich on X
Sendhil Mullainathan’s website. Follow Sendhil on X
Intrepid Growth Partners is excited to release the official sizzle reel for our new podcast: The Derby Mill Series: Intrepid Pioneers of the Next Economy. Featuring discussions with entrepreneurs at the forefront of deploying machine intelligence and brainstorming sessions about where the technology will go—at the limit.
Intrepid Senior Advisors Rich Sutton (pioneer of reinforcement learning), Sendhil Mullainathan (MacArthur Genius recipient), and Niamh Gavin (Applied AI scientist) join Intrepid co-founder and partner Ajay Agrawal to explore the possibility frontier. Join them as they connect with guest founders and practitioners that are currently implementing AI-based solutions and pushing out the productivity frontier.
En liten tjänst av I'm With Friends. Finns även på engelska.