Latest Interviews
Showing 1–3 of 3 transcripts.
Clear all filters- Jane Street1h 35m
The Network as a Program with Nate Foster
Nate Foster, a professor at EPFL and visiting researcher at Jane Street, bridges programming languages and networking by advocating for treating networks as verifiable programs through formal methods and Domain Specific Languages like Netcat and P4. His work has evolved from foundational theories on bidirectional data conversion to practical industrial applications, including the Butane system which compiles high-level latency policies into safe, distributed BGP configurations to replace error-prone manual router management. Foster's approach combines algebraic analysis of routing semantics with a software engineering culture that prioritizes rigorous testing and visualization, enabling complex network modifications while challenging traditional end-to-end principles in favor of in-network computing for specialized workloads.
- 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.
- Jane Street1h 48m
Why Testing Is Hard and How to Fix It with Will Wilson
Antithesis CEO Will Wilson founded the company to solve the non-determinism and state-space explosion challenges that plague traditional testing in complex distributed systems. The platform utilizes hypervisor-level emulation to create deterministic simulations of unmodified software, enabling exhaustive state-space exploration without the need for extensive manual test definitions. This approach has attracted major institutional users like Jane Street, which serves as both a customer and a Series A investor to validate the tool's efficacy in finding critical concurrency bugs and accelerating AI-driven development cycles.