Building the GitHub for RL Environments: Prime Intellect's Will Brown & Johannes Hagemann
Will Brown and Johannes Hagemann of Prime Intellect discuss the shift from static prompting to "environment-based" AI development, and their Environments Hub, a platform designed to democratize frontier-level training.
The conversation highlights a major shift: AI progress is moving toward Recursive Language Models that manage their own context and agentic RL that scales through trial and error. Will and Johannes describe their vision for the future in which every company will become an AI research lab. By leveraging institutional knowledge as training data, businesses can build models with decades of experience that far outperform generic, off-the-shelf systems.
Hosted by Sonya Huang, Sequoia Capital
[AIEWF Preview] Multi-Turn RL for Multi-Hour Agents — with Will Brown, Prime Intellect
In an otherwise heavy week packed with Microsoft Build, Google I/O, and OpenAI io, the worst kept secret in biglab land was the launch of Claude 4, particularly the triumphant return of Opus, which many had been clamoring for. We will leave the specific Claude 4 recap to AINews, however we think that both Gemini’s progress on Deep Think this week and Claude 4 represent the next frontier of progress on inference time compute/reasoning (at last until GPT5 ships this summer).
Will Brown’s talk at AIE NYC and open source work on verifiers have made him one of the most prominent voices able to publicly discuss (aka without the vaguepoasting LoRA they put on you when you join a biglab) the current state of the art in reasoning models and where current SOTA research directions lead. We discussed his latest paper on Reinforcing Multi-Turn Reasoning in LLM Agents via Turn-Level Credit Assignment and he has previewed his AIEWF talk on Agentic RL for those with the temerity to power thru bad meetup audio.
Full Video Episode
Timestamps
00:00 Introduction to the Podcast and Guests01:00 Discussion on Claude 4 and AI Models03:07 Extended Thinking and Tool Use in AI06:47 Technical Highlights and Model Trustworthiness10:31 Thinking Budgets and Their Implications13:38 Controversy Surrounding Opus and AI Ethics18:49 Reflections on AI Tools and Their Limitations21:58 The Chaos of Predictive Systems22:56 Marketing and Safety in AI Models24:30 Evaluating AI Companies and Their Strategies25:53 The Role of Academia in AI Evaluations27:43 Teaching Taste in Research28:41 Making Educated Bets in AI Research30:12 Recent Developments in Multi-Turn Tool Use32:50 Incentivizing Tool Use in AI Models34:45 The Future of Reward Models in AI39:10 Exploring Flexible Reward Systems
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Distributed Training, Decentralized AI: Prime Intellect's Master Plan to Make AI Too Cheap to Meter
Vincent Weisser and Johannes Hagemann, founders of Prime Intellect, join a conversation on the Cognitive Revolution to delve into distributed training, decentralized AI, and their vision for a future where compute and intelligence are widely accessible. They discuss the technical challenges and advantages of distributed training, emphasizing how such systems can democratize AI technology and create a more equitable future. The founders also describe their broader goal of creating a public utility for compute and intelligence and touch on their collaborative work in biosafety and scientific research to illustrate the practical applications of their vision for decentralized AI.
SPONSORS:
Oracle Cloud Infrastructure (OCI): Oracle's next-generation cloud platform delivers blazing-fast AI and ML performance with 50% less for compute and 80% less for outbound networking compared to other cloud providers. OCI powers industry leaders like Vodafone and Thomson Reuters with secure infrastructure and application development capabilities. New U.S. customers can get their cloud bill cut in half by switching to OCI before March 31, 2024 at https://oracle.com/cognitive
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CHAPTERS:
(00:00) Teaser
(01:02) About the Episode
(05:43) Welcome to the Cognitive Revolution
(05:55) Exploring Decentralized AI
(06:46) A Positive Vision for the Future
(08:19) The Risks and Rewards of AI
(08:56) Superintelligence and Its Implications
(13:22) The Future of Work in an AI-Driven World
(17:09) The Role of Billionaires in an AI Future (Part 1)
(20:41) Sponsors: Oracle Cloud Infrastructure (OCI) | NetSuite
(23:21) The Role of Billionaires in an AI Future (Part 2)
(30:20) The Compute Market Landscape (Part 1)
(35:10) Sponsors: Shopify
(36:30) The Compute Market Landscape (Part 2)
(47:49) Decentralized Compute Fabrics
(51:25) Regulatory Challenges in Europe and the US
(53:28) Policy Regrets and the EU AI Act
(54:30) The Impact of Overregulation on AI
(57:00) Frontier AI Labs and Safety Plans
(01:00:02) Open Source vs. Closed Models
(01:06:19) Scientific Progress with AI
(01:14:56) Distributed Training in AI
(01:35:29) Challenges in Model Interpretability
(01:40:06) Supervised Fine-Tuning and Reinforcement Learning
(01:45:19) Future of Compute and Infrastructure
(02:01:02) NVIDIA's Market Dominance and Competition
(02:05:22) Decentralized Training and Open Source Collaboration
(02:09:58) Governance and Incentives in Decentralized AI
(02:14:19) Conclusion and Call for Collaboration