Podcast
Stanford MS&E 435
Stanford MS&E 435 sessions on technology strategy, entrepreneurship, and management science.
Original sourceStanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Infrastructure, Capstone Case
OpenAI’s compute lead is becoming an industrial-scale infrastructure problem spanning chips, power, cooling, land, and supply-chain coordination. The episode argues that agentic AI is shifting workloads toward inference, latency, and heterogeneous hardware, while long-term value may move from infra toward platforms and apps.
Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge
Yash Patel argues that AI progress has moved from pretraining and scaling laws into a post-training era dominated by RL, verifiable rewards, and enterprise-specific specialization. He says the next frontier is continual learning from production feedback, while compute scarcity, chip economics, and data access will shape which companies can keep improving.