Yash Patil worked on OpenAI's Codex and now co-founded and leads Applied Compute, which trains custom RL-based AI models on enterprises' own workflows and proprietary data — making him a credible practitioner on the shift from generic LLMs to institution-specific "Specific Intelligence." Attendees interested in how AI-native companies (like DoorDash) achieve differentiation through private evals and continual-learning agents should not miss his session.

Recent talks (1)

Enterprise Internal Knowledge — MS&E 435: Economics of the AI Supercycle (Class 6)Stanford MS&E 435 · May 2026

Public activity researched automatically · as of Jun 2026