World models

The Next Medium: Why Real-Time Interactive Video Changes Everything — Ahmed Ahres, Reactor

The Next Medium: Why Real-Time Interactive Video Changes Everything — Ahmed Ahres, Reactor

Ahmed Ahres argues that real-time interaction fundamentally changes the medium, not just its speed, especially in generative AI. He defines "world models" as interactive, effectively infinite, and steerable video, drawing parallels with GPS and camera viewfinders. This paradigm shift unlocks new forms of control, intelligent advertising, programmable worlds for robotics and education, and advanced live avatars. He highlights the critical infrastructure challenges of streaming pixels, managing stateful sessions, and achieving global sub-100ms latency, emphasizing that batch infrastructure is unsuitable for real-time applications. Evaluation of consistency for these models remains an unsolved problem.

Waymo Co-CEO Dmitri Dolgov: The Demo Is Only 1% Of The Work

Waymo Co-CEO Dmitri Dolgov: The Demo Is Only 1% Of The Work

Waymo co-CEO Dmitri Dolgov outlines seven crucial lessons from fifteen years of developing and scaling the Waymo Driver, the world's most advanced physical AI. He details the unique challenges of physical AI compared to digital, emphasizing the critical role of reliability, strategic technology choices, continuous innovation through foundation models, structure-augmented learning, high-fidelity simulation, AI flywheels, and robust evaluation frameworks to achieve superhuman safety and build trust in real-world autonomous systems.

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

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.

What Big Tech Missed And How Startups Can Still Win

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.

Coding Agents Are Secretly General Agents

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.

Why Physical AI Is the Next Frontier | The a16z Show

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.