The Derby Mill Series

AI-enabled cyberattacks are increasing in sophistication and creativity. For example, recently, a vending machine became a potential entry point for attackers targeting a large financial institution in a major city. So how can manufacturers protect devices in the age of AI and LLMs? How can that effort be helped by open source software and hardware? And what does this mean for the future of connected devices?All this and more is on the agenda in the latest episode of the Derby Mill Series, which sees our usual team of Ajay Agrawal, Rich Sutton, Sendhil Mullainathan, Niamh Gavin and Suzanne Gildert joined by Intrepid growth partner Ken Nickerson and our special guest, Gianni Cuozzo from Exein, as they explore embedded cybersecurity and how it protects billions of connected devices around the world.GUESTS AND HOSTSGianni Cuozzo, founder and CEO, ExeinAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist and CEO, Emergent PlatformsSuzanne Gildert, founder and CEO, Nirvanic Consciousness TechnologiesKen Nickerson, senior advisor, Intrepid Growth Partners, and founder and CEO, iBinaryLINKSExein websiteExein explanation videoExein raises €100m in new funding to accelerate its global expansionMentioned in the episode: Read Anthropic’s report: Disrupting the first reported AI-orchestrated cyber espionage campaignSubscribe to The Derby Mill Series at our Substack (main site) or on YouTube, Spotify or Apple PodcastsDerby Mill is created by the team at Intrepid Growth Partners and produced by Ghost Bureau.DISCUSSION POINTS00:00 — What is embedded cybersecurity?01:23 — How IoT devices become attack vectors02:20 — The vending machine breach at a major bank06:00 — Lateral movement and malware expla11:05 — What is embedded cybersecurity?13:49 — What makes Exein unique in cybersecurity16:06 — Reinforcement learning and hacking17:29 — Physical risks in robotics19:24 — Pattern recognition vs expected behaviour25:56 — Historical lessons from computing vulnerabilities31:05 — AI and cybersecurity at the limit32:13 — Future equilibrium: open hardware and software36:44 — Scaling attacks and defence in cyber-physical systemsDISCLAIMERThe 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

Suzanne Gildert, founder/CEO exploring AI–human integration. Rich Sutton, Turing Award pioneer in reinforcement learning. Niamh Gavin, applied AI scientist and CEO focused on foundation models. They debate whether AI justified the software selloff, how AI rewrites product cycles and orgs, risks from opaque models and hallucinations, and a possible future of AI-merged humans versus those who opt out.

Barney Hussey-Yeo, founder and CEO of Cleo, a profitable AI personal finance app used by millions. He talks about Cleo’s proactive AI, scaling to $350M ARR, and how models turn messy transaction data into individualized financial guidance. The conversation explores onboarding to build trust, reward functions for reliable advice, and visions for agentic, automated financial management.

In this enlightening discussion, Tobias Lütke, CEO of Shopify, shares insights about the recent launch of their Winter '26 AI edition designed to empower small businesses through AI. He reveals the exciting capabilities of SimGym, an AI-driven simulation tool that helps merchants test strategies without real customer data. Behavioral economist Sendhil Mullainathan weighs in on the importance of using AI for supporting human decision-making. The duo explores the potential of tools like Sidekick to enhance merchant efficiency and discusses the future of decentralized AI in commerce.

Does the Canadian AI community have a communications problem? Too often, AI investors feel they have to go outside of the country to find great targets for deals. Similarly, domestic AI companies find it difficult to attract dollars from Canadian sources of capital. Too few investors and companies actually talk to one another. And fewer still have the kind of trusted relationship required to get deals done.So in this episode, Derby Mill host Ajay Agrawal, a co-founder and partner at Intrepid Growth Partners, gathers some of the key figures working to create the Canadian AI community, to discuss how to improve things. We’re excited to welcome Canada’s first Minister of Artificial Intelligence, Evan Solomon, in a discussion that also includes one of the driving forces behind Canadian growth equity, Mark Shulgan, also a co-founder and partner at Intrepid, as well as Adam Keating, the co-founder and CEO of CoLab, a software platform that uses AI to accelerate and improve engineering design processes, based in St. John’s, Newfoundland.Their discussion highlights the special moment in which Canadian AI finds itself—as well as the challenges the country must overcome to achieve international success.GUESTS AND HOSTS (extended bios below)Evan Solomon, Canada’s Minister of AI and Digital InnovationAdam Keating, CEO & co-founder, CoLabMark Shulgan, co-founder and partner, Intrepid Growth PartnersAjay Agrawal, co-founder and partner, Intrepid Growth PartnersLINKS Derby Mill series website. Derby Mill is created by the team at Intrepid Growth Partners.Be sure to catch every episode of The Derby Mill Series by subscribing on the following platforms: YouTube // Spotify // Apple PodcastsDISCUSSION POINTS00:00 Cold open01:35 Context for episode02:19 What is CoLab?04:21 Role of AI06:21 AI beyond hotspots07:44 Canada’s AI potential17:09 AI in St. John’s24:22 CoLab’s innovation29:04 Canada’s greatest risk37:36 Final remarksEvan Solomon is Canada’s first Minister of Artificial Intelligence and a Member of Parliament representing Toronto Centre. Before entering politics, he was one of Canada’s most recognized journalists for more than 25 years, known for his incisive interviews and deep coverage of national and global issues. He co-founded Shift, an award-winning international magazine exploring the rise of the digital age, and is the author of two best-selling books, Fueling the Future and Feeding the Future. Today, Evan leads Canada’s efforts to build a responsible and ambitious AI future — one that reflects Canadian values and strengthens the country’s digital sovereignty.Mark Shulgan is the co-founder and Partner of Intrepid Growth Partners, a growth-stage investment fund. Previously, Mark founded and led OMERS Growth Equity, which he launched in 2018. During his time at OMERS, Mark invested $1 billion in private North American software and healthcare companies and served as the chairman of the investment committee. Prior to joining OMERS, Mark co-founded and then led the Thematic Investing team (now called Venture and Growth Equity) at CPP Investments.Adam Keating is a mechanical engineer who co-founded CoLab out of sheer frustration when he saw how engineers were being held back by inadequate tools for working together. He led development of one of the world’s first Hyperloop vehicles (taking home 2nd place internationally at SpaceX’s 2017 competition), he’s invented an electric propulsion system for large-scale aircraft, designed systems for biology-guided radiotherapy, and managed elements of multi-billion dollar energy projects—just to name a few achievements!NUGGETSEvan Solomon on Canada’s AI Problem (2001)Many Canadian tech companies struggle to gain recognition and funding at home, says Canada’s Minister of AI and Digital Innovation, Evan Solomon.Evan Solomon on Canada’s AI Potential (2002)Canada’s Minister of AI and Digital Innovation Evan Solomon says Canadian talent and innovation are the “lowest-hanging fruit” for global AI leadership.Canada’s Greatest AI Risk (2003)Intrepid co-founder and Derby Mill Series host Ajay Agrawal asks Canadian AI Minister Evan Solomon about the biggest risks AI poses for the country.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

Engineering is growing more complex—but design reviews still drag through email screenshots and PowerPoints.In this episode of the Derby Mill Series we welcome Adam Keating, CEO & co-founder of CoLab, whose platform uses AI to accelerate and improve engineering design reviews. One client achieved a 40% reduction in the cost of poor quality in a single year.With 160 employees and clients like Ford, Hyundai, GE, Johnson Controls and Lockheed Martin, CoLab is headquartered in St. John’s, Newfoundland.This week we’re also proud to note that Intrepid Growth Partners, the Derby Mill Series’ parent firm, led a US$72 million Series C financing round in CoLab, marking a major step in scaling the company’s AI work for engineering.So what would that scaling look like? What’s the future of AI and engineering? And how can machine learning improve generative design? These topics and more are explored in today’s episode by our hosts Ajay Agrawal, Rich Sutton, Sendhil Mullainathan, and Niamh Gavin, along with special guest Suzanne Gildert. They ask: what if AI didn’t just assist engineers, but fundamentally changed how design decisions are made—faster, smarter, with fewer errors?GUESTS AND HOSTSAdam Keating, CEO & co-founderSuzanne Gildert, co-founder & CEO, Nirvanic Consciousness TechnologiesAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsLINKSIntrepid leads the Series C investment in CoLabCoLab secured US$72 million in venture capital funding.Series C round press from Axios and The Globe and Mail.Adam Keating’s LinkedIn post announcing the Series C round, which features a cool video that provides some great contextCoLab website.Video explainer of what CoLab doesVideo explainer of CoLab AutoReview.Mentioned in the episode: genetic algorithms to design radio antennas.Derby Mill series website.Derby Mill is created by the team at Intrepid Growth Partners.Rich Sutton’s home page. Follow Rich on X.Sendhil Mullainathan’s website. Follow Sendhil on X.Be sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts // SubstackDISCUSSION POINTS00:00 Cold open01:29 Context for episode02:59 About CoLab05:25 Niamh: ML techniques07:54 Suzanne: Training data11:25 Rich: Language & application18:30 Niamh: Open vs. closed foundations22:52 CoLab customer base24:34 Sendhil: ML similarity model30:49 Protein model for parts33:26 CoLab at the limit39:50 Rich: Value functions45:44 Feedback cycles52:35 Adam Keating responds56:05 Final remarksNUGGETSWhy Are People in the Loop At All? (1901)CoLab CEO and Co-founder Adam Keating talks about designing a waterbottle. MacArthur Genius Award recipient Sendhil Mullainathan responds with why are humans in the loop at all?The Future of Collaborative Design (1902)Why does Suzanne Gildert, CEO of Nirvanic, worry about the future of collaborative design?Automotive Design and AI (1903)Derby Mill host Ajay Agrawal and co-host Niamh Gavin debate the limitations of automotive design.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

A trillion-dollar clash of ideas is roiling the artificial intelligence community. Today, in a special episode, our host Ajay Agrawal leads Rich Sutton, Sendhil Mullainathan and Niamh Gavin, and special guest Suzanne Gildert, in a fascinating exploration of the issue: Are Large Language Models (LLMs) sufficiently “bitter lesson pilled” to live up to their hype?“Bitter lesson pilled” is the AI community’s term of art for scaling with the constantly falling cost of compute (e.g., search and learning). The term arises from Rich Sutton’s 2019 essay, The Bitter Lesson.As he recently told independent journalist Dwarkesh Patel on the Dwarkesh Podcast, Rich Sutton does not believe that LLMs are sufficiently “bitter lesson pilled.” In other words, Rich believes LLMs suffer from a key vulnerability: A limit exists on their ability to improve – and it’s much closer than we’ve been led to believe.GUESTS AND HOSTSAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsSuzanne Gildert, founder and CEO, Nirvanic Consciousness TechnologiesLINKSThe Dwarkesh Podcast episode featuring Rich Sutton. The computer scientist Andrej Karpathy’s take. Rich’s original Bitter Lesson essay.Meta machine-learning engineer Chris Hayduk’s tweet about the debate on X, retweeted by Rich and referenced in this episode by Sendhil.Good description of the train-fly problem that Sendhil mentioned, from Presh Talwalkar. Derby Mill series website. Derby Mill is created by the team at Intrepid Growth Partners.Rich Sutton’s home page. Follow Rich on X.Sendhil Mullainathan’s website. Follow Sendhil on X.Be sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple PodcastsDISCUSSION POINTS00:00 Cold open00:39 Context for episode01:39 The bitter Lesson02:49 Supervised learning04:30 Challenge of RL09:49 Discussing a Tweet13:30 Rich’s opinion on the big lesson21:28 Tension in the LLM space23:25 Behaviour and extrapolation25:27 What is considered AI26:05 Final remarksNUGGETSWhy Squirrels Still Outthink Supervised AI (1801)Derby Mill Series host Ajay Agrawal asks co-host Suzanne Gildert, why can’t AI learn like a squirrel?Addressing Rich’s Tweet (1802)MacArthur Genius Award recipient Sendhil Mullainathan responds to a tweet that underscores a key difference between LLMs and humans.What Happens if LLMs Don’t Pay Off Soon (1803)The Bitter Lesson says, “look out if you’re putting all your eggs into the basket of human knowledge,” according to Turing Award recipient Richard Sutton.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

The Derby Mill Series hosts are back to kick off Season 2 with an episode about automating factories—an extension of a discussion we began in the series’ first-ever episode. Here, hosts Ajay Agrawal, Rich Sutton, Sendhil Mullainathan and Niamh Gavin sit down with Vention founder and CEO Etienne Lacroix and CTO Francois Giguere. Vention’s mission: to become the default operating system for factory automation, combining modular hardware, intuitive design software, and low/no-code programming tools to speed deployment and enhance performance. The team asks, What if AI could go beyond design assistance and run fully autonomous, self-optimizing factories from concept to deployment?About VentionVention is a vertically-integrated manufacturing automation platform. Its primary AI application today is predicting optimal component selection and system design. When a manufacturer specifies their automation needs, Vention’s AI recommends compatible parts, layouts, and configurations from its proprietary dataset of 400,000 labelled designs, with real-time pricing and compatibility checks. Vention serves more than 4,000 factories across more than industries, including facilities belonging to Tesla, L’Oréal, Amazon and Lockheed Martin.GUESTS AND HOSTSEtienne Lacroix, founder and CEO, VentionFrancois Giguere, CTO, VentionAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsLINKSVention CEO Etienne Lacroix explains the mission at Nvidia GTC 2025Vention websiteVention’s video tutorials mini-siteDerby Mill series website. Derby Mill is created by the team at Intrepid Growth Partners.Rich Sutton’s home page. Follow Rich on XSendhil Mullainathan’s website. Follow Sendhil on XBe sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts DISCUSSION POINTS00:00 Cold open01:52 Automating manufacturing with Vention03:45 Factory assembly tasks05:40 AI for design07:48 Faster and cheaper10:28 When automation reaches its limits10:43 Pragmatic control system design12:02 AI training datasets12:58 Vention’s end-to-end platform15:20 Hybrid AI model approaches17:47 AI spotting unmet needs21:28 Manual versus automated processes27:46 Full process of factory automation37:20 Customer interfaces40:59 Data feedback and improvement45:58 Distribution shift in AI1:00:17 Adaptive AI in factories1:04:59 Final thoughtsNUGGETSWhy Automating Factories Is Becoming Faster and Cheaper (1701)Intrepid’s Ajay Agrawal asks Vention founder and CEO Etienne Lacroix why automating factories is becoming faster to do, and cheaper to implement.Automating Automation (1702)Vention CTO Francois Giguere describes the future of AI-driven workflows, which he says includes the counterintuitive tagline of “automating automation.”ML Can Fix the Black Box Model Challenges (1703)Why MIT’s Sendhil Mullainathan believes machine learning can do what physical models can’t.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

Our hosts chat with Liran Belenzon, CEO and co-founder of BenchSci. Based in Toronto, BenchSci has raised more than $215-million to date, and is backed by such funds as former U.S. vice-president Al Gore’s Generation Investment Management, private and public markets investment giant TCV, Google-backed Gradient Ventures and F-Prime Capital Partners. More than half of the world’s largest pharmaceutical companies are clients of BenchSci, which is officially known as Scinapsis Analytics Inc.The company’s mission is to accelerate the speed and quality of life-saving R&D to improve patient health. This episode touches on the challenges and potential of using AI in drug discovery, emphasizing the importance of understanding disease biology and the need for significant investment in data collection and analysis. The name, BenchSci, is a reference to “bench science,” the fundamental laboratory research that uncovers the biological mechanisms underlying diseases and forms the foundation for drug discovery.With machine intelligence, BenchSci seeks to automate hypothesis generation and experiment design by deeply analyzing scientific publications, preprints, and pharma data. Central to their approach is building a comprehensive knowledge graph that maps bio-entities such as genes, proteins, and diseases, along with their complex relationships.GUESTS AND HOSTSLiran Belenzon, co-founder and CEO, BenchSciAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsLINKSBenchSci explanation videoBenchSci websiteBenchSci ranked #29 on Deloitte’s 2024 Technology Fast 500™BenchSci named to The Globe and Mail’s Canada’s Top Growing Companies 2024 listLiran’s 2023 TechTO talk about fundraisingMentioned by Sendhil in this episode: Don R. Swanson, a pioneer in information scienceDerby Mill show websiteRich Sutton’s home page. Follow Rich on XRead Sendhil’s co-written journal on Machine Learning as a Tool for Hypothesis GenerationSendhil Mullainathan’s website. Follow Sendhil on XBe sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts DISCUSSION POINTS00:00 Cold open and introductions01:33 R&D for drug discovery and BenchSci02:07 A shocking number of drug trials fail04:33 What BenchSci does and doesn’t do09:50 What kind of feedback is sent to BenchSci?14:09 Where does BenchSci fall on these extremes?16:39 Is BenchSci too ambitious?21:20 Niamh’s take25:37 Rich’s take27:15 Hypothesis generation29:31 What Niamh loves about AI34:47 Final remarksNUGGETSSmall Changes in Drug Research Matter (1601)Intrepid's Sendhil Mullainathan explains why even a 1% improvement in drug trial success can be worth millions.AI for Discovery (1602)Intrepid's Niamh Gavin shares how AI’s "global sweep" could unlock science’s blind spots.AI’s Biggest Scientific Breakthrough (1603)Intrepid’s Sendhil Mullainathan explains the hidden obstacle holding back AI’s biggest scientific breakthroughs.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

Joining the usual Derby Mill team of Ajay Agrawal, Rich Sutton, Sendhil Mullainathan and Niamh Gavin are two experts in the automation of business workflows: AppliedAI CEO and founder Arya Bolurfrushan, and member of the technical staff Phillip Kingston.AppliedAI closed a $55 million USD Series A round of financing in February 2025 led by G42 and with backing from Palantir and McKinsey, among others. With a pre-investment valuation of $300 million, the UK-founded, Abu Dhabi-based firm develops software to enhance the efficiency of businesses by automating their back-office processes, particularly in highly regulated industries such as healthcare, insurance, and pharmaceuticals. For example, AppliedAI processed more than four million pages of U.S. medical records in 2024. On its client list are such firms as Abu Dhabi’s M42 Healthcare Group, U.S. law firm Morgan & Morgan and UK-based drug safety firm Qinecsa.In this discussion, Arya and Phillip join the Derby Mill hosts to discuss the technicalities of automating workflows, such as medical coding for hospitals. They explore the challenges and opportunities of integrating AI and human intelligence to optimize things at the limit, and conclude by speculating how business could change when automation is fully integrated into every step of the process.GUESTS AND HOSTSArya Bolurfrushan, founder and CEO, AppliedAIPhillip Kingston, member of the technical staff, AppliedAI, and Visiting Professor at State University Kyiv Aviation Institute, Kyiv, UkraineAjay Agrawal, co-founder and partner, Intrepid Growth PartnersRichard Sutton, senior advisor, Intrepid Growth Partners, 2024 Turing Award recipient, pioneer of reinforcement learning and professor, University of AlbertaSendhil Mullainathan, senior advisor, Intrepid Growth Partners, MacArthur Genius grant recipient and professor, MITNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsLINKSAppliedAI’s Series A press releaseAppliedAI websiteArya Bolurfrushan on McKinsey’s Faces of DisruptionPhillip Kingston’s personal webpageRich Sutton’s home page. Follow Rich on XSendhil Mullainathan’s website. Follow Sendhil on XBe sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts // SubstackThumbnail image is a detail from a mural by Diego Rivera, Man at the CrossroadsDISCUSSION POINTS00:00 Cold open and introductions01:10 Business productivity workflows and Applied AI02:37 How most workflows are 80% similar06:39 An example from the healthcare industry10:21 AppliedAI’s commercial approach12:50 Niamh asks Philip to get technical on their process16:32 What is "supervised automation"?25:21 Sendhil’s take32:56 Rich’s take40:15 How AppliedAI may change things at the limitNUGGETSHow Will AI Algorithms Change Human Workflows? (1501)MIT Economist Sendhil Mullainathan asks, if we knew there was an AI algorithm underneath most business processes, would the entire workflow be different?Fewer Human Hours Per Case (1502)AppliedAI’s Phillip Kingston describes how the company chooses which workflows to automate.Human Auditors, Not Processors (1503)AppliedAI’s Arya Bolurfrushan explains why the cost of auditing AI workflows may increase over time.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