AI-podden

Ted Schönbeck, Nordic CTO, Google Cloud discusses the current and future landscape of AI, emphasizing its ability to perform tasks that typically require human intelligence, with machine learning allowing systems to learn independently. Google, an "AI-first" company since 2016, has integrated AI into products like Maps and Search. Schönbeck highlights recent advancements in large language models and generative AI, particularly the use of large token windows for analyzing extensive datasets and the rise of multimodal AI, which processes diverse data types like text, images, and audio. He also addresses the challenges businesses face in scaling AI, recommending fine-tuned, specialized models over generalized large ones.

This week, Anna Baecklund, Head of Data and Analytics at Handelsbanken, discusses AI's role in banking. She highlighted its potential to improve customer experience, compliance, risk management, and financial literacy. Though AI mimics human behavior, it lacks true human intelligence. Anna sees AI driving personalized banking and efficient systems while urging banks to adapt to new technologies and regulations. She recommended "Papers with Code" for learning more about AI.

This episode features special guest, Tom Sodestrom, AWS Enterprise Strategist, speaking on the latest trends in AI and edge computing. Tom shares his insights on the upcoming trends in the next 5-10 years, including the rise of generative AI, increased data volume and importance, productive edge computing, and digital twins and simulation at scale.

This episode, recorded live, is the second installment of Ather and Mimi's special news updates at Epicenter Stockholm. They discuss OpenAI and concerns about its shift from research to product development, as well as AI advancements in math reasoning by DeepMind and OpenAI’s new "Strawberry" model. The hosts also touch on Sam Altman's Worldcoin project and the intersection of blockchain, crypto, and AI. Autonomous vehicle progress is covered, particularly Uber's partnership with Wave, while an AI safety issue at Sakana AI raises concerns about system control. Lastly, they explore NVIDIA's growth and share a fun AI project predicting pole vaulter Armand Duplantis’ potential record-breaking jumps.

This week, guest host (Sifted's) Mimi Billing and Ather discuss June's AI news updates. Topics include Elon Musk's lawsuit against OpenAI over a nonprofit agreement, Anthropic’s Cloud 3 outperforming ChatGPT and Google's Gemini, and major investments in Anthropic by Google and Amazon. They also cover the EU AI Act's approval, marking the first regulatory framework for AI in Europe, and the UN's resolution on ethical AI development. The resignation of Stability AI’s CEO, Emad Mostaque, is discussed in light of the company's financial struggles. The episode highlights the crowded AI startup landscape and the need for innovation.

A quick reminder to everyone of our next live recording at Epicenter Stockholm on September 3rd.

Sign up at: https://ai-podden-live-at-epicenter.confetti.events/ invite=896d06ea9ecd5f2d0ac122d4cefa8d50c469

 Hope to see you all there!

In this episode, Ather interviews Tom Soderstrom, AWS Enterprise Strategist, on his career and insights into innovation and generative AI. Tom shares his journey from Sweden to the US, becoming NASA’s first CTO for IT at JPL, and introducing cloud computing. He emphasises innovation through small, low-risk experiments, or “two-way door decisions,” and the formula of Return on Attention plus Return on Interest leading to Return on Investment. The discussion focuses on the potential of generative AI and the gap between excitement and practical applications. Tom encourages leaders to experiment and continuously learn, likening this to being "technology teenagers", and highlights AI's democratisation and the need for a culture of experimentation to solve real business problems.

In this episode, Ather interviews Lele Cau, AI research scientist at MotherBrain, part of EQT Partners. They discuss AI as a system integrating software and hardware for intelligent decision-making. Lele describes MotherBrain’s role in aiding deal professionals with data and algorithms, emphasising the importance of knowledge graphs in large language models (LLMs) for maintaining relationships and entities. Lele highlights the need for hybrid AI systems combining various information sources and explore the future of AI hardware, including quantum computing. Lele recommends the movie "Her" and books "The Beauty of Mathematics in Computer Science" and "Algorithms to Live By."

In this episode, Ather meets Caroline Ohlsson, Data & AI Director at Verdane. Caroline explains Verdane's investment in tech-enabled companies and how her team supports them with data and AI. She discusses Verdane's use of generative AI tools like Verdain GPT and Microsoft Co-pilot to boost productivity, and shares examples of AI-driven improvements in code development and sales forecasting. Emphasizing the importance of a solid data foundation and responsible AI practices, she advises companies starting with AI to have a passionate business representatives, a data expert, and an AI owner. 

In our first ever live recording at Epicenter Stockholm, Ather and Mimi Billing open with Kai-fu Lee's prediction that AI will take 50% of jobs by 2027 and the market's projected growth to $184 billion by 2024. Despite major investments, the profitability of large language models (LLMs) remains uncertain. OpenAI's financial success is noted, but high development costs are a concern. Privacy issues with Microsoft's new AI hardware and Google's challenges with its AI overview feature are highlighted. Ethical concerns arise from Scarlett Johansson's lawsuit threat against OpenAI for voice theft. They also discuss recent AI reasoning research and the need for more efficient training methods.

In this episode, Ather interviews Anastasia Varava, Research Lead at SEBX, SEB Banken, about AI in banking. Anastasia's work at KTH and SEB Banken focuses on machine learning, robotics, and AI applications to enhance employee efficiency, decision-making, crime prevention, and customer experience. She discusses data sensitivity, the shift to cloud services, and security measures. Anastasia sees potential in simulating financial markets with AI, combining classical computer science with deep learning, and opportunities for startups. She highlights neurosymbolic systems and recommends Chris Bishop's AI texts.

In this episode host Ather interviews Mikael Huss, co-founder and Principal Data Scientist at Codon. They discuss the evolution of AI, noting the shift from traditional data science to large language models (LLMs) like ChatGPT. Mikael highlights the overshadowing of other AI applications by LLMs and generative AI. They emphasize the importance of deeply understanding business problems before applying AI solutions and the potential of open-source LLMs. The conversation also covers the challenges of causal inference in AI, the need for better explainability, and the future of artificial general intelligence (AGI).

This week our guest host, Sifted's Mimi Billing and Ather discuss April's AI developments, including; implications in geopolitics and business, highlighting Microsoft's warning about AI's potential use to disrupt elections in the US, South Korea, and India. They explore China's advancements in AI, the impact of quantum computing on AI development, and recent innovations in human behaviour modeling and reasoning algorithms in large language models. The episode also touches on AI's role in the food and beverage industry, exemplified by an AI-developed coffee blend in Finland, while acknowledging the technological hurdles in mimicking human sensory experiences. 

In this episode, Ather hosts guest Alex Baker, global retail strategist, entrepreneur, and Principal at Nordic Retail Hub. They discuss the evolution of AI in retail, highlighting its shift from backend applications to enhancing customer-facing experiences with technologies like dynamic pricing and personalized promotions. They also explore various AI applications that are transforming retail operations, from supply chain management to targeted advertising via retail media networks. The conversation also touches on AI's broader impact on personal productivity and corporate efficiency, underscoring the technology's potential to augment human capabilities. 

Ather interviews Vilhelm von Ehrenheim, co-founder and CAIO of QA Tech, discussing the use of AI in automating quality assurance for web applications. Wilhelm details how their AI agents test web functionality to ensure reliability before launch, leveraging large language models for enhanced decision-making. He also addresses the challenges of adapting AI to different platforms and anticipates future AI capabilities in broader applications, including the potential developments towards Artificial General Intelligence (AGI).

In this episode, Ather interviews Ramprakash Ramamoorthy, AI director at ManageEngine, who clarifies AI's role as a practical tool for pattern recognition and productivity in IT management, rather than a threat to human jobs. Ram discusses how ManageEngine has integrated AI across their product suite since 2011 to optimize IT operations and customer service, enabling proactive management decisions. He emphasizes the evolution of AI from a hyped technology to a crucial component in streamlining business processes and enhancing decision-making capabilities within the IT sector.

This week our guest host, Sifted's Mimi Billing and Ather discuss February's AI developments, including OpenAI's new video tool, Sora, and its careful release strategy amidst ethical concerns. They explore the bias issues in Google's Gemini AI and contrast different AI philosophies, highlighting the debate between practical AI applications and the pursuit of genuine intelligence. The conversation also covers NVIDIA's significant market valuation, the concept of an AI bubble, and Google's approach to AI-written content for publishers. Investments in robotics by NVIDIA and OpenAI are mentioned as forward-looking strategies. Finally, the hosts ponder the hype around AI compared to past excitement in the crypto industry.

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Salman Avestimehr, USC professor and FedML co-founder, discusses AI, federated learning, and large language models. This week's topics include; AI definition, distributed and federated systems research, current challenges in generative AI, and trustworthiness in ML. Ather and Salman explore the future of accessible LLMs on personal devices, stress the importance of data, and discuss challenges like distinguishing machine-generated outcomes. The conversation touches on enforcing regulations in the era of open-source tools and recommends the book "Life 3.0”

In this episode of the AI Podcast, host Ather Gattami interviews Michal Sustr, co-founder of EquiLibre, a company that uses game theory and reinforcement learning for trading.

Michal discusses the company's approach to trading, which is based on the idea that markets can be modelled as games. He explains that EquiLibre uses game theory to develop algorithms which can predict the behaviour of other traders and make profitable trades.

Ather and Michal also discuss the future of AI, and Sustr predicts that large language models (LLMs) will continue to be a major area of research in the coming years. Michal believes that LLMs will eventually be able to reason and solve problems in a way that is indistinguishable from human intelligence.

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Reinforcement learning is a type of machine learning that allows agents to learn by interacting with their environment. DeepMind researcher, David Abel is interested in using reinforcement learning to understand and build intelligent agents. One of the big questions in AI is what exactly "intelligence" is. Another big question is how to build intelligent agents that can reason and solve problems. Abel believes that it is important to achieve conceptual clarity in AI.  

Abel's research focuses on AI's core scientific questions, emphasizing the need for conceptual clarity about intelligent behavior and agents. David express skepticism about creating AI with certain reward functions, suggesting that multi-criteria objectives could better align AI with human interests.