Jason Droege, CEO of Scale AI, discusses the evolution of AI training from simple labeling to complex, expert-driven tasks. He shares insights on the future of AI agents, the reality of enterprise AI adoption, and crucial business lessons learned from building Uber Eats from zero to a multi-billion dollar business.
Edwin Chen, founder and CEO of Surge AI, shares the company's origin story, its rapid, bootstrapped growth, and its research-driven philosophy on data. He critiques traditional data labeling, explains why metrics like inter-annotator agreement fail for complex tasks, and offers a sharp analysis of benchmark hacking. Chen also details the future of data, from multimodal and agentic reasoning in rich RL environments to the need for hyper-specialized expertise for scientific discovery.
Garrett Lord, CEO of Handshake, details the company's extraordinary pivot from a college career network to a dominant AI data provider. He explains how they leveraged their proprietary network of 500,000 PhDs and 3 million advanced degree holders to build a business on track to surpass $100 million ARR in its first year by providing high-quality, expert-generated data for training frontier AI models.
Edwin Chen, CEO of Surge AI, discusses the critical role of high-quality human data in training frontier models, the flaws in current evaluation benchmarks like LMSys and IF-Eval, the future of complex RL environments, and why he bootstrapped Surge to over $1 billion in revenue.