RJ Honicky

🔬 From Red Teaming GPT-4 to Automating Drug Discovery: The Future of AI in Science — Andrew White

Jan 28, 2026 · 1:13:56

Andrew White, co-founder of Future House and Edison Scientific, argues that automating the scientific method with LLM agents is now feasible, explaining how ChemCrow triggered White House briefings, how Kosmos uses a world model to generate and test hypotheses, and why EtherZero's reward hacking revealed the difficulty of verifiable chemistry tasks. He shifts from his academic work on molecular dynamics to building agents that enumerate and filter ideas, claiming scientific taste remains the frontier. White recounts the counterexample of D.E. Shaw Research's MD vs. AlphaFold, asserts that natural language is the universal bridge for scientific data, and predicts that automation will expand rather than eliminate scientific jobs.

[Paper Club] Intro to Diffusion Models and OpenAI sCM: Simple, Stable, Scalable Consistency Models

Nov 2, 2024 · 52:22

RJ Honicky presents OpenAI's sCM paper, which introduces techniques to simplify, stabilize, and scale continuous-time consistency models for faster image generation. The paper addresses instability issues by modifying skip connections, using cosine/sine schedules, adjusting the noise embedding scale to 0.02, applying adaptive double normalization, and implementing tangent warm-up over the first 10K iterations. These innovations enable one-step generation with FID scores rivaling GANs and multi-step diffusion models, while scaling experiments demonstrate performance up to 1.5B parameters. Distillation from scratch outperforms distillation from a teacher, and the episode contrasts these continuous-time methods with discrete-time approaches, explaining the intuition behind the mathematical choices.