Topic
Compute Economics
Google's AI Brain Drain, SpaceX's Huge Quarter, Airtable's 90% Collapse, US Data Fuels China AI
The episode centers on three big AI/infrastructure stories: Google’s AI leadership shakeup, SpaceX’s blockbuster quarter, and what Airtable’s sale says about SaaS under AI pressure. The panel also debates whether U.S. data-labeling firms are accelerating China’s AI catch-up.
Stanford 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.