Simulating Humanity: from Generative Agents to 8 Billion Digital Twins — Joon Sung Park, Simile AI
Joon Sung Park, co-founder and CEO of Simile AI and lead author of the landmark Generative Agents ('Smallville') paper, details his journey from artist to Stanford PhD researcher building foundation models of human behavior. He explains how Simile creates digital twins using deep interviews, observational transaction data, and randomized controlled trials to simulate human decision-making and social physics at 85% fidelity. The conversation covers the difference between predicting and shaping the future, why frontier LLMs fail at behavioral nuance, and the long-term vision of simulating all 8 billion people to address complex societal coordination challenges like climate change.
- Frontier models like GPT-4 drop as low as 20% to 30% accuracy when simulating real human behavior in niche sub-populations because they are optimized for hyper-rational reasoning. Read →
- Joon Sung Park and co-founder Percy Liang, who coined the term foundation model at Stanford, argue that public web data cannot accurately simulate real human behavior. Read →
- Static persona prompts fail because frontier models collapse into stereotypes rather than reflecting actual human choices. Read →
- Simile AI is mapping early scaling laws in agent simulation: pouring in more behavioral data and compute produces predictable, repeatable accuracy gains. Read →
- Thomas Schelling won the Nobel Prize by showing that mild individual preferences, not just overt racism, cause total neighborhood segregation. Read →