Park explains that Simile's inspiration came from a 2023 simulation of a small town, which demonstrated how AI agents could exhibit realistic human behaviors through memory and reflection. He argues that behavioral data is more valuable than web data, and Simile's strategy involves sourcing representative individuals to build a flexible simulation platform. The company's data flywheel improves predictions by comparing simulated outcomes with real-world results, similar to AlphaGo's learning process. Park emphasizes the importance of clear reward functions and fast feedback loops, which helped Simile secure Fortune 500 clients quickly. He predicts synthetic panels will surpass human panels within three years, offering faster and more cost-effective insights. Regarding prediction markets, Park clarifies that Simile focuses on understanding causality, not just forecasting, and could potentially disrupt stock markets by providing evidence-based simulations. He shares lessons on team building, hiring adaptable people, and the high cost of top AI talent, stressing that vision and impact drive retention. Finally, Park discusses the $200M Series B, the challenges of moving from proof of concept to production, and his vision of AI simulations becoming the 'GPU of intelligence,' enabling scalable representation of individuals and new applications like hedge funds.