World models

How Standard Kernel uses compound AI systems to optimize code and extract maximum GPU performance

How Standard Kernel uses compound AI systems to optimize code and extract maximum GPU performance

Chris from Standard Kernel explains how the company uses two autonomous optimization systems, one for whole workloads and one for individual CUDA kernels, to speed up AI inference. He walks through a roughly 2x vLLM speedup on Qwen with a CoreWeave team, details the kernel generation search and the correctness checks needed for frontier-model-written kernels, and presents case studies including 11x faster world models, faster time-series and LLM serving, and customer-driven requirements.

AI Makes Games Worse?

AI Makes Games Worse?

Piero Molino, CEO of Studio Atelico, argues that AI should be a foundational game mechanic enabling new experiences rather than a cost-cutting shortcut. He covers on-device multimodal engines built on small fine-tuned models, the economics of cloud inference, artist rights, open source in the game stack, and what skill means in an era of coding agents.

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

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.

One Operator, Many Drones: Inside Skydio's Autonomy Stack — Suchet Bargoti, Skydio

One Operator, Many Drones: Inside Skydio's Autonomy Stack — Suchet Bargoti, Skydio

Suchet Bargoti, Skydio's Director of Inspection and Mapping, demos a fleet of docked drones orchestrated through an agentic layer, then explains how full-stack autonomy, maps as world models, edge-cloud splitting, VLM-driven tracking and the limits of end-to-end learning combine to make drones function as infrastructure.

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

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.

The Next Breakthroughs in AI with Yossi Matias | The Google Research Podcast

The Next Breakthroughs in AI with Yossi Matias | The Google Research Podcast

Yossi Matias, VP and GM of Google Research, discusses how Google prototypes the future by inventing it, emphasizing the current "Golden Age of Research." Key themes include the seamless integration of AI through ambient intelligence and adaptive Generative UI, architectural advancements that push beyond scaling laws with techniques like Speculative Decoding, and multi-agent AI systems such as AI Co-Scientist and Empirical Research Assistance for accelerating scientific discovery. He also details Google Earth AI for crisis resilience and planetary intelligence, breakthroughs in healthcare diagnostics with MedGemma and the Google Health app, and milestones in quantum computing with the Willow chip, ultimately envisioning a future where AI amplifies human ingenuity and solves humanity's biggest challenges.