Oct 13, 2026

Robots That Predict the Future: Dyna-2 & Physical AI — Jason Ma, Dyna Robotics

Dyna Robotics is pioneering physical AI with Dyna-2, a world-action model trained on over a million hours of human video, predicting future states and generating robot actions. Co-founder Jason Ma explains how this enables robots to learn new tasks from minimal demonstrations, tackles the robotics data bottleneck with synthetic data and self-improving models, and details their full-stack approach, including custom semi-humanoid hardware for real-world deployments at Din Tai Fung. The discussion delves into diffusion transformers, agentic harnesses for hour-long workflows, the "Bitter Lesson" of scaling data, and the distinction between world-action models and VLAs, all driven by a deployment-first research culture.

Oct 10, 2026

Why AlphaFold Didn't Solve Protein Folding — Pushmeet Kohli, Google DeepMind & Sal Candido, Biohub

A panel with Google DeepMind's Pushmeet Kohli and Biohub's Sal Candido, moderated by Brandon Anderson, examines how AI should be built for biology. Topics include scaling laws and data quality, the bitter lesson applied to data, AlphaFold's handcrafted design and its limits, protein dynamics, cryo-EM as a richer data source, trust and calibration versus interpretability, and why curing disease requires 10x breakthroughs.

Jul 01, 2026

The Benchmark With No Instructions — Tufa Labs (ARC-AGI-3)

Tim Scarfe visits Tufa Labs to explore their top-ranking ARC-AGI-3 system, a benchmark for agentic intelligence that challenges LLMs in goal discovery and action efficiency. The team delves into the complexities of fractured representations, the role of human priors, and whether LLMs truly plan or merely simulate it effectively, all while balancing the bitter lesson with AI safety concerns.

Oct 04, 2025

Some thoughts on the Sutton interview

A reflection on Richard Sutton's "Bitter Lesson," arguing that while his critique of LLMs' inefficiency and lack of continual learning is valid, imitation learning is a complementary and necessary precursor to true reinforcement learning, much like fossil fuels were to renewable energy.

Aug 06, 2025

On Engineering AI Systems that Endure The Bitter Lesson - Omar Khattab, DSPy & Databricks

Omar Khattab, creator of DSPy, reinterprets the 'Bitter Lesson' for AI engineering, arguing that the key to building robust and enduring AI systems is to move beyond brittle prompt engineering. He advocates for a declarative, modular approach that separates the fundamental program logic from the rapidly changing landscape of LLMs, optimizers, and inference techniques.