Topic

AI Model Training

Artwork for Stanford MS&E435 Economics of the AI Supercycle | Spring 2026 | Enterprise Internal Knowledge
Stanford MS&E 435

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.