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.

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 the company's 500B open-weight reasoning model Beam, the economics of frontier training, the shift from renting to owning intelligence in enterprise, the role of Chinese open models in the global ecosystem, and the case that openness itself is a safety strategy. He also reflects on how AI is accelerating scientific research and reshaping research team sizes.

Sep 24, 2026

How to build products on a moving frontier | Dan Shipper (Every)

Dan Shipper, co-founder and CEO of Every, advocates for a dedicated 'labs team' to navigate the rapid evolution of AI capabilities. He argues that traditional product development struggles with the 'moving frontier,' proposing a model where a small, experimental lab explores new AI ideas and capabilities, while the main product team focuses on scaling existing offerings. Shipper outlines how to establish and run such a lab, from team composition ('pirates' and 'architects') to rigorous experimentation, dogfooding, and a structured pipeline for integrating successful innovations into the core product, enabling continuous disruption and growth.

Sep 23, 2026

The Best Models Still Reason Like Toddlers — Andrew Dai, Elorian

Andrew Dai discusses how current frontier models struggle with visual reasoning, often hallucinating or failing to understand spatial relationships and context. He highlights limitations of existing benchmarks and proposes a 'visual thinking' paradigm, exemplified by Elorian's approach using native visual chain of thought, new data, and architectural advances to tackle real-world challenges in robotics, construction, and mechanical design.

Sep 17, 2026

OpenAI researcher on agent swarms & recursive self-improvement

Noam Brown discusses OpenAI's multi-agent system, which solved a Millennium Prize Problem using 10,000 agents. He explores the implications of this massive parallelization for AI capabilities, the rapid progress in mathematics, and the accelerating pace of AI development. A significant portion of the conversation is dedicated to the critical challenges of AI alignment, particularly in light of incidents like the 'Hugging Face' event, and how to ensure models remain aligned during Recursive Self-Improvement (RSI) as their capabilities and operational horizons expand rapidly.

Aug 31, 2026

Why AI Demand Is Outrunning Compute Supply

A deep dive into the current AI boom, exploring why demand for intelligence is likely underestimated and the outcome won't necessarily be winner-take-all. The discussion covers the rapid economics of AI infrastructure, the risk of an AI shortage over a bubble, the potential for orbital compute and re-industrializing America, and NVIDIA's central role as the "central bank of AI" in a multi-model future.