Oct 20, 2026

What Survives When AI Can Build Anything? (with Dr. Richard Socher)

Richard Socher, CEO of Recursive and author of The Eureka Machine, makes the case for automating the scientific method with recursively self-improving AI. He covers how AI keeps replacing hand-crafted expertise with scale, the four pillars of his approach, why hallucinations can aid discovery, why RSI still rules out an overnight takeoff, and how science may become an engineering discipline across physics, biology, and economics.

Oct 09, 2026

Beam: The Great American Open Model with ReflectionAI Co-Founder and CEO Misha Laskin

Misha Laskin, co-founder and CEO of Reflection AI, discusses building frontier open-weight models, the launch of the 500B-parameter Beam reasoning model, the economics of renting versus owning intelligence, and why he believes open models will capture most token demand. The conversation covers RL-driven scaling efficiency, Chinese open model ecosystems and their geopolitical implications, and the safety case for openness, including cybersecurity as a lens for defense and offense. He closes with optimism about AI-accelerated science and the evolving research workforce.

Sep 04, 2026

Faster Chips That Don't Melt — Anima Anandkumar & Benedikt Jenik, Accelerated Understanding

Accelerated Understanding is building a foundation model for the physical world, leveraging neural operators, resolution invariance, and physics-informed self-improvement to model diverse physical systems, aiming for universal application across domains like semiconductors and energy.

Jul 21, 2026

Causal Models Need Causal Data - Xaira’s X-Cell model (Bo Wang & Ci Chu)

Bo Wang and Ci Chu of Xaira Therapeutics introduce X-Cell, a 4.9-billion-parameter diffusion language model designed to predict cellular responses to genetic perturbations. Trained on PISCES, the largest genome-wide CRISPRi Perturb-seq dataset (25.6 million single cells across 16 contexts), X-Cell overcomes limitations of previous observational models. The discussion highlights the critical role of high-quality, causal data, X-Cell's architecture advantages, and its demonstrated ability to generalize to unseen cell types and primary cells, marking a significant step towards truly predictive virtual cell models in drug discovery.

Jul 10, 2026

General relativity from first principles – Adam Brown

Adam Brown elucidates Einstein's General Relativity, tracing its origins from the equivalence principle and curved spacetime to the mind-bending physics of black holes. He covers the striking observational evidence for black holes and the historical confirmation of GR, concluding with a speculative discussion on how AI could accelerate scientific discovery as 'superhuman explainers'.

Apr 30, 2026

I Read 9,000 AI Papers So You Don't Have To

Nick Vasiloglou, VP of Research at Relational AI, analyzes the key trends from NeurIPS 2025, highlighting the most impactful and under-the-radar developments for industry professionals. The discussion covers the rise of data markets through real-time attribution, the sophisticated engineering behind capable small language models (SLMs), the explosion of AI for science, and the shift towards post-training models with real-world tools.