Jul 28, 2026

The Next Frontier of AI Is Spatial Intelligence | Fei-Fei Li on a16z

Fei-Fei Li and Yunzhu Li discuss World Labs' acquisition of SceniX, focusing on building "spatial intelligence" and "large world models" to enable robots to understand and interact with the physical world. They elaborate on SceniX's "real-to-sim-to-real" pipeline, emphasizing how simulation, coupled with generative models like Marble, addresses the data bottleneck in robotics by providing consistent, scalable, and efficient training and evaluation environments. The conversation covers the role of counterfactual reasoning, the development of robotics foundation models, and the strategic focus on semi-structured environments for pragmatic, reliable robot deployment.

Jul 25, 2026

What Big Tech Missed And How Startups Can Still Win

Alexandre LeBrun, CEO of AMI Labs, discusses his career building and selling AI companies, emphasizing his strategy of tackling problems "20 years too early." He delves into AMI Labs' contrarian bet on "world models" over traditional LLMs, highlighting their ability to learn directly from real-world sensory data, unlike LLMs which learn from human-written text. LeBrun explains how this approach is critical for developing intelligent robots and avoiding the pitfalls of Vision-Language Assistants (VLAs). He also touches upon the challenges of securing talent, data, and compute for such an ambitious project, the strategic choice of location, and the importance of holding an extremely large vision while solving a narrow problem for early founders.

Jul 23, 2026

Coding Agents Are Secretly General Agents

Jay Hack, head of AI at ClickUp, discusses the evolution of AI from early computer vision to generalist coding agents, highlighting how 'positive transfer' makes coding an 'AGI-complete' domain. He delves into the brutal economics of AI startups facing foundation model giants, ClickUp's strategy for convergence and first-party data as a moat, and the challenges of verifiability and catastrophic forgetting. The conversation also explores LLMs at the scientific frontier, the 'car wash test' revealing limits of world models, and speculative future applications like LLM resorts and game integration.

Jul 21, 2026

Why Physical AI Is the Next Frontier | The a16z Show

Applied Intuition discusses the emergence of physical AI, its mission to put intelligence on a billion machines, and its latest platform, Dana, designed to democratize autonomous system development. The conversation covers the vast scope of physical AI beyond automotive, the unique challenges of real-world deployment (safety, data, hardware), the current state and future of self-driving cars and trucks, and the transformative potential of humanoids and world models. They also touch upon the geopolitical landscape of AI and the global ambitions of Applied Intuition.

Jul 17, 2026

AI Can't Learn The Way Humans Do - This Could Fix That

This discussion explores world models as a promising path to solving sample efficiency in AI and achieving AGI. It contrasts deterministic control (Newtonian physics) with stochastic environments (RL), explaining the challenges posed by large action spaces in Go, self-driving, and robotics. The episode delves into how synthetic data, video diffusion models, and latent space architectures like JEPA are making world models practical, while also highlighting remaining open problems in physics modeling, real-time adaptation, and rich sensory integration.

Jul 16, 2026

Has AI Finally Cracked Time Series Forecasting?

Ameet Talwalkar, CMU professor and Datadog's Chief Scientist, traces the journey of time series foundation models from early skepticism to their current impact. He details Datadog's Toto V1 and V2, highlighting breakthroughs in zero-shot performance, scaling, and the crucial role of data mix. The discussion extends to the vision of 'world models' for observability, integrating diverse data for self-healing software systems, and concludes with insights on open-weights models and AI's transformative effect on computer science and academic research.