The Derby Mill Series

• Mining Exploration Unpacked (The Derby Mill Series ep 06)

  In the first episode of The Derby Mill Series to post since our co-host Rich Sutton won the Turing Award, the highest distinction in the field of computer science, Sutton joins our panel of experts to further discuss the application of artificial intelligence to the task of mining exploration. What ensues is a remarkable conversation about the increasing relevance of cheap and easily discoverable data sources in an age dominated by artificial intelligence and reinforcement learning.The analogy begins with mining, where core samples may provide an element of ground truth but are, at the same time, tough and very expensive to get. Other data sources, such as aerial imagery, chips and dust, are cheap and more easily available. So can the pattern-recognition abilities of artificial intelligence elevate the relevance of that lower-fidelity, more easily available information?Extending the analysis, Intrepid Senior Advisors Niamh Gavin and Sendhil Mullainathan draw parallels with health care. Apple Watch’s skin sensors are certainly less accurate than an annually drawn blood test. But as the Watch conducts its tests numerous times a day, and as AI better recognizes troubling sensor patterns, the cheaper Watch data could become just as important as more expensive medical diagnostics.Generalizing to other areas, Intrepid partner Ajay Agrawal notes that lower-fidelity data that is more easily available could become as informative as high-fidelity data that is tougher to extract. Our experts’ ultimate prediction, then, observes that cheap data plus artificial intelligence could transform the fundamental economics of many different industries.Our panel of expertsRichard Sutton, 2024 winner of the Turing Award, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, MacArthur Genius grant recipient and professor, MITNiamh Gavin, Applied AI scientist, CEO, Emergent PlatformsAjay Agrawal, co-founder and partner, Intrepid Growth PartnersLINKSIntrepid Growth Partners’ Senior Advisor Rich Sutton wins the Turing Award. NY Times. Financial Times. Betakit.This episode extends a discussion in Derby Mill episode 05: Mining Exploration.Referenced in this episode: Sendhil Mullainathan's heart attack studyyRich 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 PodcastsDISCUSSION POINTS00:00 Introductions and opening credit01:43 Recap of Mining Exploration06:01 Clips: Mining industry transformation09:52 Niamh on narrowing the search zone12:18 Rich on sequential decisions and pattern recognition15:08 Sendhil on using supervised learning to train predictors19:34 Niamh on non-invasive markers21:52 Signals in healthcare vs. mining25:02 The combination of human + AI27:47 A new age of data analysis29:50 Data sources and reinforcement learning35:53 A cognitive barrier for data42:24 The indicator analogy45:58 Closing remarksNUGGETS (short excerpts from the full episode)NUGGET 01: Sum > Whole of Its PartsNiamh Gavin argues that human + AI intelligence is better than either in isolation.NUGGET 02: A More Interactive Feedback ProcessRich Sutton advocates for an awareness that important mining exploration problems require a wide diversity of data inputs.NUGGET 03: The Less Invasive, Far Cheaper Data Axis“What if I had a sweat test that was 10% as good as a blood test?” asks Sendhil Mullainathan, noting the way AI can make use of data from cheap and more easily available diagnostics to improve numerous different industries.NUGGET 04: AI and the Increasing Relevance of Little TestsExpert intelligence is expensive today, notes Rich Sutton, but as computational power decreases, AI will help to bolster the importance of all sorts of cheap and easy tests.DISCLAIMERThe 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit insights.intrepidgp.com

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• Mining Exploration (The Derby Mill Series ep 05)

  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 HOSTSAjay 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 PlatformsLINKSGeologicAI 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 PodcastsDISCUSSION POINTS00:00 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 remarksNUGGETS (short excerpts from the full episode)NUGGET 01: Human-Algo InteractionAIs 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 GeologistsAIs 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 StrategyHow 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.DISCLAIMERThe 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit insights.intrepidgp.com

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• Tariffs, Trade and the AI Stack (The Derby Mill Series ep 04)

  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 HOSTSMarc 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 PartnersMark Shulgan, co-founder and partner, Intrepid Growth PartnersAjay Agrawal, co-founder and partner, Intrepid Growth PartnersLINKSDerby Mill show website: https://insights.intrepidgp.com/podcastMarc L. Busch’s personal website. Follow Marc on X and LinkedInRecent Marc Busch article on how “mode 5 services” can promote U.S. manufacturing without imposing new tariffsDISCUSSION POINTS 00:00 Introductions 03:10 Ajay Agrawal introduces Professor Marc L. Busch 03:54 Busch on the legal bases for tariffs and executive orders09:56 Non-Tariff Barriers and Intellectual Property19:56 Impact on Software and AI Companies26:26 Advice for Canadian and European AI Companies29:16 Stargate, tariffs on semiconductors and subsidies as offsets for harm33:46 Predictions on how this will play out amid political considerations37:04 Potential for retaliation via anti-trust measures40:23 Role of the WTO and International Compliance45:32 Advice for Canadian AI companies53:54 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 upDISCLAIMERThe 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit insights.intrepidgp.com

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• Factories Unpacked (The Derby Mill Series ep 03)

  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 HOSTSAjay Agrawal, co-founder and partner, Intrepid Growth Partners Richard Sutton, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, MacArthur Genius grant recipient and professor, MITNiamh Gavin, Applied AI scientist, CEO, Emergent PlatformsLINKS    Derby Mill show website: https://insights.intrepidgp.com/podcastThe first episode featuring Maneva CEO Rae JeongManeva AI websiteManeva CEO Rae Jeong LinkedInA short video about Maneva’s work transforming Laura Secord chocolate productionRich Sutton’s home page. Follow Rich on XSendhil Mullainathan’s website. Follow Sendhil on XDISCUSSION POINTS 00:00 Introductions and opening credits 01:39 Clip: Rae Jeong discusses Maneva's approach to autonomous factories02:01 Rich Sutton comments on the challenge of active learning in operating factories04:54 Niamh Gavin on the use of simulated environments for experimentation06:29 Rich Sutton: “It’s hard to compete with a human” for experimentation08:05 Can simulation actually recreate a factory in all its complexity?09:42 Sendhil Mullainathan is confused where Maneva actually uses RL10:41 Balancing exploration and exploitation14:52 Discussion of temporal credit assignment in manufacturing 15:54 Clip: Sendhil asks how Maneva uses labels and exploration17:42 Clip: AI needs to conduct exploration to achieve continuous improvement 16:34 Exploring the future of manufacturing with reinforcement learning19:29 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 humans32:09 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 factories38:28 Sendhil emphasizes the need for a CEO-level sale for RL in manufacturing44:00 Challenges of fully instrumenting a factory49:00 Algorithms identifying valuable measurements52:42 Conclusion and final thoughtsDISCLAIMERThe 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit insights.intrepidgp.com

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  53:26
• DeepSeek (The Derby Mill Series ep 02)

  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.DISCLAIMERThe 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. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit insights.intrepidgp.com

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