May 27, 2026

Power agents with full context of your experiments and traces with W&B MCP server

The W&B Model Context Protocol (MCP) is a hosted endpoint that enables AI agents to intelligently interact with all Weights & Biases data, including runs, traces, evaluations, and reports. It features discovery tools for smart queries, automated analysis for comparing experiments and identifying regressions, and seamless integration with IDEs, coding agents, and chat interfaces like Mistral AI for streamlined ML workflows and on-the-go reporting.

May 27, 2026

He Raised $70M to Cure Every Disease With AI

Samuel Rodriques, founder of Edison Scientific, shares his journey from physics to building an AI scientist named Kosmos. He discusses how AI agents are already making novel discoveries, including a potential cure for blindness, and are poised to revolutionize drug discovery. The conversation dives into AI's strengths in high-throughput reasoning, the critical bottlenecks in clinical trials, proposed reforms for the US medical system, and whether human scientists will still be needed in an age of hyper-intelligent AI.

May 26, 2026

Frontier AI at Home — Alex Cheema, EXO Labs

Alex Cheema from EXO Labs explores the path to a 100x improvement in the price-performance of running frontier AI models locally. The talk covers full-stack optimization strategies, including kernel fusion for a 30% performance boost, RDMA for scalable tensor parallelism, and a novel approach of splitting prefill and decode phases across heterogeneous hardware (e.g., an RTX GPU and Mac Studios) to significantly speed up large-prompt inference.

May 26, 2026

Q-learning with Flow-Matching Policies

This talk explores methods for optimizing expressive, multi-modal policies, such as those based on flow-matching, with off-policy reinforcement learning. The speaker presents two novel algorithms, FQ-RL and CAM, designed to overcome the instability of backpropagation through multi-step generative models, enabling effective online self-improvement and adaptation for robotic manipulation tasks.

May 26, 2026

Wavefunction Flows: Efficient Quantum Simulation of Continuous Flow Models

Continuous flow models map naturally to a Schrödinger equation, the fundamental equation of quantum mechanics. This discovery proves that a trained generative model can be efficiently simulated on a future quantum computer, enabling a new, more powerful type of access to its learned distribution for tasks like Monte Carlo estimation and structure discovery.

May 26, 2026

Where the Score Lives: What Wavelets Reveal About Diffusion Models

This talk explores the paradox of why diffusion models generalize rather than memorize. It introduces an analytically tractable, wavelet-based parameterization of the score function, allowing for an interpretable analysis of how architectural biases (like locality) and data statistics interact to influence denoising performance and generalization.