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  1. Dwarkesh Patel2h 37m

    What rebuilding AlphaGo teaches us about self-play, RL, and future of LLMs - Eric Jang

    Eric Jang, Ron Minsky, Dan Pontecorvo

    Eric Zhang reconstructs AlphaGo to demonstrate how modern computing, including LLM-assisted coding and efficient neural architectures, reduces training costs from millions to thousands of dollars while solving Go's NP-hard complexity through Monte Carlo Tree Search. The presentation details the evolution from human-supervised data to tabula rasa self-play, highlighting how MCTS provides low-variance supervision that stabilizes value function learning for mid-game states. This framework validates Go as a scalable sandbox for testing automated AI research, offering transferable insights for robotics and drug discovery via verifiable performance loops.

  2. Jane Street52 min

    Effective ML 2011 Harvard CS51 Part 1

    Ron Minsky

    Ron Minsky, a technical leader at Jane Street Capital, presented a comprehensive case for prioritizing code correctness and maintainability through strict OCaml design principles that leverage the type system to enforce data invariants and ensure pattern match exhaustiveness. The lecture outlined specific architectural strategies, including mandatory interfaces, uniform naming conventions, and a "reader-over-writer" philosophy, which collectively minimize cognitive load and prevent silent failures in high-stakes financial systems. Additionally, the speaker addressed immediate course logistics by extending the Moogle project description deadline and recommending simple list-based implementations to avoid unnecessary debugging complexity.

  3. Jane Street1h 13m

    Caml Trading

    Carl Curry, Ron Minsky

    Jane Street Capital, a proprietary trading firm operating in four global cities, transitioned its primary development stack to the functional programming language OCaml to satisfy critical demands for absolute correctness, high performance, and code maintainability. This adoption enables the firm's 35 core developers to leverage OCaml's powerful type system and algebraic data types for static exhaustiveness checks, ensuring the rigorous standards required to process billions of dollars in daily equity trades without error. While the language presents challenges in ecosystem maturity, the firm has actively mitigated these gaps through its Jane Street Summer Project and achieved superior hiring outcomes by attracting engineers skilled in functional paradigms.