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Captaining IMO Gold, Deep Think, On-Policy RL, Feeling the AGI in Singapore — Yi Tay

Jan 23, 2026 · 1:32:05

Yi Tay, who leads Google DeepMind's Reasoning and AGI team in Singapore, explains how Gemini Deep Think achieved IMO Gold by abandoning symbolic AlphaProof for an end-to-end RL-trained model. He details the on-policy RL philosophy—models learn from their own generated outputs rather than imitating others—and the critical role of self-consistency through parallel sampling and internal verification. Tay describes the IMO effort: four co-captains in different time zones, a one-week training sprint, a live competition in Australia where researchers punched in problems as they were released, and the tension of waiting for human scores to determine the gold threshold. He discusses why the team believes one model must subsume everything for AGI, the data efficiency gap compared to humans, and his hiring focus on raw talent and research taste. Tay also shares his personal fitness transformation—losing 23 kilos and improving HRV—as integral to research productivity.

Truly Serverless Infra for AI Engineers - with Erik Bernhardsson of Modal

Feb 19, 2024 · 1:08:58

Erik Bernhardsson, creator of Annoy and Luigi, founded Modal to build a 'postmodern data stack' with a self-revisioning runtime that eliminates container cold starts and lets developers attach GPUs with a Python decorator. His serverless platform can fan out to thousands of GPUs within seconds, becoming a natural fit for GenAI workloads like Stable Diffusion and fine-tuning (e.g., RAMP fine-tuning 100 models in parallel). Modal differentiates from Replicate by targeting custom models and workflows, and from Modular by offering a managed cloud service rather than licensed software. Erik argues that buying hardware is inefficient for startups and that infrastructure founders must be willing to spend years on load balancing, page faults, and DNS. He shares how his IOI Gold Medal background shapes Modal's talent culture, hiring competitive programmers for complex scheduling and bin-packing problems.