Sep 30, 2026

AI, Infrastructure, and the Next Investment Cycle

David George, Sarah Wang, Alex Immerman, and Santiago Rodriguez from a16z walk through 25 charts from their State of Markets presentation, covering why markets are rising on earnings rather than multiple expansion, the roughly $780B hyperscaler capex race, the new age of atoms in physical infrastructure, enterprise AI adoption gaps, agent economics and falling inference costs, consumer AI and marketplace disruption, the bifurcation of SaaS, the rise of mega private companies, and the sectors they are most excited about next.

Sep 25, 2026

Runway’s Bet Beyond Video: World Models, Robotics, and the Neural OS — Anastasis Germanidis

Anastasis Germanidis, co-founder of Runway, discusses the company's journey from early generative creative tools to frontier video models, emphasizing their pivot towards general-purpose world simulation. He details the evolution of Gen-1, Gen-2, and Gen-3 (scaling 10x after Sora's release), highlighting the importance of controllability and the inevitability of real-time generation. The conversation delves into cutting-edge applications like Interface World Models (a fully neural operating system) and World Models for Robotics, where third-person video data and robust simulation are key to training intelligent agents.

Sep 24, 2026

Robot Demos Are Easy. Reliability Is Hard — Jason Ma, Dyna Robotics

Jason Ma, CTO of Dyna Robotics, discusses overcoming the 80-90% success rate ceiling in generalist robots for commercial viability. He details how Dyna-1 achieved a 99.4% success rate in napkin folding through a novel reward model for progress scoring, enabling scalable supervision and a human-in-the-loop active learning cycle for targeted error recovery, alongside their extensive pre-training data pyramid and robust model architecture.

Sep 24, 2026

World Models Need Causality, Not Pretty Pixels — Christopher Manning, Moonlake AI

Christopher Manning, Stanford professor and now at Moonlake AI, traces AI history from Dartmouth in 1956 and Shakey the robot through the rise of large language models. He then argues for embodied intelligence built on action-conditioned simulation, and shows how Moonlake turns a photo into a manipulable, code-based world that can close the sim-to-real gap.

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 22, 2026

Debating RSI, the US-China Gap, and Jaggedness of Frontier AI

Jean-Stanislas Denain of Epoch AI and Nathan Lambert debate the nuanced trajectory of AI. They discuss the current state of RSI, the US-China AI capabilities gap (estimated 6-8 months), and the role of distillation and compute in closing it. The conversation also covers the challenges and differing paces of AI in robotics, insights from Chinese AI job postings, and the complex trade-offs between open and closed models regarding safety and misuse. They touch on Epoch AI's research philosophy and speculate on the intricate, evolving post-training recipes at frontier AI labs.