Ep 69: Co-Founder of Databricks & LMArena on Current Eval Limitations, Why China is Winning Open Source and Future of AI Infrastructure
Ion Stoica helped define the modern data stack. Now he’s coming for AI evaluation. From co-founding Databricks and Anyscale to launching LMArena, Ion has shaped the infrastructure underlying some of the biggest shifts in computing. In this conversation, he unpacks what most people get wrong about model evaluation, the infrastructure challenges ahead for agents and heterogeneous compute, and why he believes the U.S. is structurally disadvantaged in open-source AI compared to China. (0:00) Intro(0:49) Launching a New Startup: LMArena(1:01) The Origin of the Vicuna Model(1:54) Challenges in Model Evaluation(6:33) Becoming a Company(7:47) Expanding Evaluation Capabilities(13:48) The Importance of Human-Based Evaluations(18:56) Open Source vs. Proprietary Models(23:05) Infrastructure and Collaboration Challenges(28:22) China's Strategic Advantages in Technology(29:54) Opportunities in AI Infrastructure(31:50) Challenges in AI Model Optimization(35:49) The Role of Data in AI Enterprises(39:31) Reflections on AI Progress and Predictions(50:40) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
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54:57
Ep 68: CEO of Mercor Brendan Foody on Evals Replacing Knowledge Work, AI x Hiring Today & the Future of Data Labeling
Brendan Foody is the co-founder and CEO of Mercor, a company building the infrastructure for AI-native labor markets. Mercor’s platform is already used by top AI labs to label data, evaluate human and AI candidates, and make performance-driven hiring decisions. They’re operating at the intersection of recruiting, evals, and foundation model development—helping companies shift from intuition to measurable prediction. Brendan and his team recently raised $100M and are working with some of the most advanced players in the AI ecosystem today. (0:00) Intro(1:17) State of AI in Talent Evaluation(1:54) Improvements in AI Models(4:07) Mercor Background and Mission(5:09) AI Use Cases in Hiring(13:43) Data Labeling Landscape(16:48) Expanding Beyond Coding(18:39) Company Vision and Market Strategy(21:11) Meeting with xAI(23:47) Does Mercor Use Their Own Product?(25:41) Exploring Multimodal Capabilities(28:03) Skills for the Future: Embracing AI(29:29) The Demand for Software Engineers(34:55) Foundation Model Landscape(38:42) AI Regulations(39:57) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
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44:03
Ep 67: Max Junestrand (CEO, Legora) on Differentiating and Pricing AI Apps & How the Legal Industry Will Evolve
Jacob and Logan sit down with Max Junestrand, founder and CEO of Legora - a rapidly growing legal AI platform (and Redpoint portfolio company). After announcing their Series B last week, Max joined the show to discuss why law is uniquely suited for AI, what it takes to scale an enterprise-ready product across global markets, and a few crazy moments from Legora’s journey so far. They dig into product strategy, lessons on evolving alongside foundational models, and how AI is reshaping the future of law firms. Whether you're building in AI or just curious how it’s being applied in complex industries, this one’s packed with practical insights. (0:00) Intro(1:30) The Evolution of AI in Law(2:43) AI's Impact on Legal Processes(8:28) Advantages Over Other Players in the AI Law Space(12:19) Challenges in Educating Users(17:28) The Hardest Part of Building Legora(18:46) Pricing Models and Cost Management(25:42) YC Experience and Commercial Focus(28:11) Being Patient When Releasing Products(30:58) Maintaining a Fast-Paced Work Culture(33:24) Rapid Growth and Market Penetration(36:59) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
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44:09
Ep 66: Member of Technical Staff at Anthropic Sholto Douglas on Claude 4, Next Phase for AI Coding, and the Path to AI Coworkers
Sholto Douglas, a Member of Technical Staff at Anthropic, joined Unsupervised Learning to break down why coding is the clearest early signal of model progress, how AI agents are already accelerating research, and what it’ll take to unlock real-world breakthroughs in fields like biology and robotics. (0:00) Intro(0:48) Claude 4(1:30) Capabilities and Improvements(2:29) Practical Applications and Advice(3:04) Future of AI in Coding(4:38) Managing Multiple AI Models(11:20) The Barrier to Agents is Reliability(16:35) Agents Conducting Research(19:54) Impact of Models on World GDP(25:14) Most Important Metrics in Model Improvement(29:53) Stories of Model Creativity(32:45) How Often Will New Models Be Shipped in the Future?(39:51) Day-to-Day Work of AI Researchers(46:46) The Future of AI and Society(51:26) Quickfire With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
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57:45
Ep 65: Co-Authors of AI-2027 Daniel Kokotajlo and Thomas Larsen On Their Detailed AI Predictions for the Coming Years
The recent AI 2027 report sparked widespread discussion with its stark warnings about the near-term risks of unaligned AI.Authors @Daniel Kokotajlo (former OpenAI researcher now focused full-time on alignment through his nonprofit, @AI Futures, and one of TIME’s 100 most influential people in AI) and @Thomas Larsen joined the show to unpack their findings.We talk through the key takeaways from the report, its policy implications, and what they believe it will take to build safer, more aligned models. (0:00) Intro(1:15) Overview of AI 2027(2:32) AI Development Timeline(4:10) Race and Slowdown Branches(12:52) US vs China(18:09) Potential AI Misalignment(31:06) Getting Serious About the Threat of AI(47:23) Predictions for AI Development by 2027(48:33) Public and Government Reactions to AI Concerns(49:27) Policy Recommendations for AI Safety(52:22) Diverging Views on AI Alignment Timelines(1:01:30) The Role of Public Awareness in AI Safety(1:02:38) Reflections on Insider vs. Outsider Strategies(1:10:53) Future Research and Scenario Planning(1:14:01) Best and Worst Case Outcomes for AI(1:17:02) Final Thoughts and Hopes for the Future With your co-hosts: @jacobeffron - Partner at Redpoint, Former PM Flatiron Health @patrickachase - Partner at Redpoint, Former ML Engineer LinkedIn @ericabrescia - Former COO Github, Founder Bitnami (acq’d by VMWare) @jordan_segall - Partner at Redpoint
On Unsupervised Learning we probe the sharpest minds in AI in search for the truth about what’s real today, what will be real in the future and what it all means for businesses and the world. If you’re a builder, researcher or investor navigating the AI world, this podcast will help you deconstruct and understand the most important breakthroughs and see a clearer picture of reality. Follow this show and consider enabling notifications to stay up to date on our latest episodes.
Unsupervised Learning is a podcast by Redpoint Ventures, an early-stage venture capital fund that has invested in companies like Snowflake, Stripe, and Mistral.
Cohosted by Redpoint investors Jacob Effron, Patrick Chase, Jordan Segall and Erica Brescia.
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