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The Derby Mill Series

Intrepid Growth Partners
The Derby Mill Series
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  • Data Privacy (The Derby Mill Series ep 13)
    Headquartered in Toronto, Private AI detects and removes personally identifiable information (PII) from data using large language models (LLMs), all without compromising individual or institutional privacy. In this episode, Private AI co-founder and CEO Patricia Thaine offers a behind-the-scenes look at the company’s technical strategy, including the scalability challenge inherent in protecting confidential company information, and the growing threat of re-identification. With more than 30,000 hours invested in building their PII detection system, Private AI now operates in seven countries and partners with organizations such as the Business Development Bank of Canada, MaRS, and the University of Toronto.This episode features the Intrepid team exploring such questions as:* How can organizations effectively protect personally identifiable information (PII) and confidential company information in large language models?* What are the risks of re-identification, even after attempting to anonymize data?* How can companies balance data utility with privacy preservation?* How can privacy protection be approached as a dynamic, evolving challenge rather than a static solution?* What role can technology play in helping organizations understand and control their data privacy?GUESTS AND HOSTSPatricia Thaine, co-founder & CEO, Private AIAjay 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 PlatformsLINKSPrivate AI website, explainer videoPrivate AI demo, PrivateGPTRead the NYT article, A Face Is Exposed for AOL Searcher No. 4417749Pymetrics, a company that pioneered the use of AI and behavioural science to improve workforce decisions, was acquired by Harver.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 Introduction01:22 Meet Patricia Thaine of Private AI01:41 About Private AI02:54 How Private AI redacts and protects data04:18 What would scalability look like for confidential company info?08:14 Deconstructing NYT’s article: A Face is Exposed for AOL Searcher No. 441774910:12 Can your digital footprint be an identifier?15:35 Solving the synthetic data problem19:15 How data minimization can help with privacy21:24 Mapping out the future of data privacy25:56 What would a reward function look like?27:12 Final commentsNUGGETSNugget 1 - The Challenge of De-Identification Concerning Data PrivacyPrivate AI CEO and co-founder Patricia Thaine describes the challenge of data privacy and de-identification.Nugget 2 - Consumer Market Demand and RegulationIntrepid’s Sendhil Mullainathan explores the challenge of creating a start-up in the “personally identifiable information” space. Nugget 3 - Different Types of CII and PIIPrivate AI’s Patricia Thaine discusses the nuances of removing personally identifiable information, as even a piece of jewellery in an X-ray can compromise anonymity. 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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  • Hospital Care (The Derby Mill Series ep 12)
    Hospitals in jurisdictions around the world face tight budgets and staff shortages. Artisight offers an AI-powered suite of software services designed to help hospitals do more with the limited resources they have available. Based in Chicago and led by a medical doctor who also has an MBA, Dr. Andrew Gostine, Artisight’s mission is to improve quality metrics and financial outcomes with the help of computer vision, IoT sensors and vital-sign monitoring. For example, one hospital system that used Artisight’s technology, Northwestern Medicine, saw a 52% reduction in nursing overtime and a 76% reduction in nursing turnover alongside improved nursing and patient satisfaction scores. At the start of 2024, Artisight announced that it raised US$42 million in a funding round that was oversubscribed by 2.4x and included NVIDIA as an investor.On the agenda in today’s discussion: What’s the potential for AI-enabled healthcare administration? How can AI be of assistance to the healthcare industry? What can be done to increase efficiency in the near term, and where does the technology go at the limit? The Derby Mill team talks to Artisight CEO and co-founder Dr. Andrew Gostine, and chief science officer and co-founder Tim Koby, to discuss the future of healthcare.GUESTS AND HOSTSDr. Andrew Gostine, Co-Founder & Chief Executive Officer, ArtisightTim Koby, Co-Founder & Chief Science Officer, ArtisightAjay Agrawal, co-founder and partner, Intrepid Growth PartnersNiamh Gavin, senior advisor, Intrepid Growth Partners, Applied AI scientist, CEO, Emergent PlatformsLINKSDerby Mill show websiteArtisight’s website, explainer videoLearn more about Artisight’s Series B funding roundBe sure to catch every episode of The Derby Mill Series by subscribing on the following platforms:YouTube // Spotify // Apple Podcasts DISCUSSION POINTS00:00 Introduction01:07 Meet the Artisight team02:00 Core value of Artisight03:44 Sensor suite: What data is collected05:42 Artisight’s top 3 AI predictions09:39 Why fall prevention matters most16:12 AI in hospital care—why now?24:05 Raising the ceiling in healthcare25:47 Improving models without moving data30:19 Smarter AI vs. smartest doctor?40:14 Are there limits to trusting AI?44:54 Numbers that prove AI trust51:01 Next big AI-driven interventions55:05 Rewards for in-hospital problem-solving59:57 AI vs. human default in hospital care01:09:35 Final remarksNUGGETSNugget 1 - Using AI to Maximize Hospital CareAI can now recognize procedures like IV insertions without staff saying a word, thanks to AI using voices as a timestamp and training computer vision with synthetic images.Nugget 2 - "Why now?" How Real-World Problems Held AI Back Until TodayFor years, AI has promised to transform healthcare. So why is it only working now? Emergent Platform CEO Niamh Gavin uses her healthcare expertise to describe the real-world hurdles that held earlier AI solutions back. Artisight CEO and co-founder, Dr. Andrew Gostine, explains the innovation that was needed to reach the quality of AI and get it to where it is today.Nugget 3 - Stopping Sepsis Before It StartsAI could predict sepsis up to 18 hours before it strikes—early enough that patients may never meet the clinical criteria at all. Artisight CEO and co-founder Dr. Andrew Gostine explains how predictive intelligence is transforming preventative care, and why fall prevention was just the beginning.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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  • Digital Advertising (The Derby Mill Series ep 11)
    StackAdapt is an advertising platform that leverages AI to optimize digital ad campaigns across multiple channels, including display, video, native, and connected TV. With an auction system, it evaluates millions of ad opportunities each second using predictive analytics to maximize ROI and enhance audience targeting. By integrating customer data and providing privacy-conscious, scalable solutions, StackAdapt provides advertisers with data-driven insights and automated ad placement. So how can AI enhance discovery and shape awareness of digital advertising solutions that people may not yet realize they need? And what reward systems might be most effective for RL in optimising ad campaigns? The Derby Mill team talks to StackAdapt CTO and co-founder Yang Han to discuss potential answers. GUESTS AND HOSTSYang Han, CTO and co-founder, StackAdaptAjay 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 PlatformsLINKSDerby Mill show websiteStackAdapt’s website and explainer videoRead Rich Sutton’s latest paper Welcome to the Era of ExperienceRich 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 POINTS 00:00 Introduction02:00 Welcome, Yang Han, CTO and Co-Founder of StackAdapt02:45 How advertising on StackAdapt works09:10 How StackAdapt thinks about ROI11:30 Yang on ad competition and who gets the credit.13:55 Niamh on what StackAdapt will look like at the limit.18:23 Sendhil on how we can surface decision-making in advertising.24:20 Rich on the advantages of assistance-based shopping.29:13 Becoming customer-focused with the rise of AI31:53 What executives lack when perfecting the matching problem.26:47 What’s one thing investors should pay attention to in this industry? Nugget 01 - Alternative Customer-First Business ModelNugget 02 - Educating Customers with Personalized AdsNugget 03 - Disrupting the Ad Market with Agent DiscoveryDISCLAIMERIntrepid GP is an investor in StackAdapt. 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. 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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  • Welcome to the Era of Experience (The Derby Mill Series ep 10)
    Derby Mill co-host Richard Sutton and his former student, David Silver, recently published a paper about the future of artificial intelligence, called Welcome to the Era of Experience. So in this episode the show’s other hosts—Ajay Agrawal, Sendhil Mullainathan and Niamh Gavin—take their chance to interview Rich about the essay, and provide their take on its implications.Today’s large language models (LLMs) are trained on human-generated data. So far, this has led to the development of incredible capabilities, such as mastering complex games like backgammon or chess, or absorbing content created by humans and creating fascinating new iterations of art.While the evolution of LLMs—from AlphaZero (2017) to ChatGPT (2022) to DeepSeek (2025) and beyond—can make it seem as though their possibilities are endless, the agents remain constrained by the scope of the data they are given. In the paper, Silver and Sutton write that “in key domains such as mathematics, coding, and science, the knowledge extracted from human data is rapidly approaching a limit.” Consequently, AI agents will have to be trained on other data, such as their own experiences, which could lead to rapid innovation and superhuman capabilities—a time period which Silver and Sutton refer to as the “age of experience.”This episode, a roundtable discussion, focuses on the following quotes pulled from the paper:* Why now? "This will become possible, as outlined above, when agents are able to autonomously act and observe in streams of real-world experience, and where the rewards may be flexibly connected to any of an abundance of grounded, real-world signals."* Why science? "Perhaps most transformative will be the acceleration of scientific discovery."* Human-like vs superhuman AIs. "This era of experience will likely be characterised by agents and environments that, in addition to learning from vast quantities of experiential data, will break through the limitations of human-centric AI systems... Furthermore, the pursuit of this agenda by the AI community will spur new innovations in these directions that rapidly progress AI towards truly superhuman agents.”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 PlatformsLINKSDerby Mill show websiteRead Rich Sutton’s latest paper Welcome to the Era of ExperienceRich Sutton’s 2019 paper The Bitter LessonCo-founder of OpenAI, Ilya Sutskever, says AI reasoning power will become less predictableListen to our previous episode about DeepSeekCheck out co-author David Silver’s websiteRich 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 Introduction01:34 Context about the paper02:56 Chronology of AI paradigms03:10 Why now?06:09 Niamh’s chronology of AI development14:10 Why science?20:36 Sendhil on scientific research and AI27:07 Grounded vs. ungrounded rewards29:21 Rich on RL temporal difference errors31:10 Human-like vs. superhuman AIs36:40 Final commentsNugget 01 - AI for Scientific DiscoveryNugget 02 - Is Science like RL?Nugget 03 - The Value of ExperienceDISCLAIMERThe 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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  • Cancer Detection (The Derby Mill Series ep 09)
    Skin Analytics is a UK company using AI to automate the diagnosis of serious skin conditions, starting with skin cancer. Its core product, DERM, is the only Class III CE mark AI medical device for autonomous dermatology in the UK’s health system. Used on more than 150,000 real-world patients, DERM achieves 99.8% negative predictive value, outperforming dermatologists. The company is expanding into general dermatology and launching in the EU and US.In the future, Skin Analytics intends to create a dermatology AI platform that is able to diagnose and treat a broader range of conditions. Based on a diverse sampling of low-cost data, the company intends its platform to transition from self-supervised to unsupervised learning, enabling ubiquitous, low-friction health monitoring.This episode features the Intrepid team exploring such questions as:* What would it take to build healthcare around AI abundance, not human bottlenecks?* How might one frame an approach to reach 99% automation in dermatological triage?* What are the tradeoffs between sensitivity, specificity, and health system efficiency?* How could reward systems (RL or pathway-based optimization) be introduced?* What’s the potential of self-supervised learning across multiple medical modalities?GUESTS AND HOSTSNeil Daly, founder and director, Skin AnalyticsJack Greenhalgh, AI director, Skin AnalyticsAjay 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 PlatformsLINKSDerby Mill show website: insights.intrepidgp.com/podcastSkin Analytics website and explainer videoRich 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 Introduction01:24 Meet the team: Skin Analytics06:12 The lead-up to image recognition10:29 Patient drop-off post-referral14:03 Getting classification right18:47 Integrating into the healthcare system22:36 Cancer detection in the limit27:55 At-home cancer detection34:10 Making dermatology RL-able45:00 Using data as proxies for other diagnoses50:21 Early detection vs. overdiagnosis55:07 Higher rates of cancer detection advantages57:00 What took so long?59:07 Final remarksNugget 01 - Sensors Reveal Hidden Data in the SkinTraditionally, dermatology has been rate-limited by the human eye and optical sensors. So incorporating a variety of additional sensors to collect more diverse and comprehensive data can open the door to a new kind of pre-primary care, potentially revealing more information about internal conditions like hypertension or liver disease.Nugget 02 - The Economic Model Behind At-Home DiagnosesThere's a massive direct-to-consumer interest in skin health, which opens the door to a potential expansion of at-home skin-monitoring apps that could be used beyond only in primary care settings. But overdiagnoses risk overwhelming the healthcare system. In order to avoid case buildup, these apps require an economic model that leverages medical systems and consumer trust.Nugget 03 - Redesigning the Treatment DelayWhat prevents people from accessing treatment is not the diagnostic delay (which often involves a lengthy wait for results), but rather the delay in seeking help: People tend to wait for a reason to address an issue, which increases the risk of lowering the survival rate as a disease spreads.DISCLAIMERIntrepid GP is an investor in Skin Analytics. 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. 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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About The Derby Mill Series

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. insights.intrepidgp.com
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