World models

"We Made a Dream Machine That Runs on Your Gaming PC"

"We Made a Dream Machine That Runs on Your Gaming PC"

Shahbuland Matiana and Andrew Lapp from Overworld Labs introduce Waypoint 1, a 2 billion-parameter open-source world simulation model designed to run on consumer hardware at 60 FPS. They discuss its novel architecture, which combines a causal language model with an image diffusion model to denoise frames in real-time based on user prompts and controller inputs, emphasizing low-latency interaction and the importance of local execution for user privacy.

Code World Model: Building World Models for Computation – Jacob Kahn, FAIR Meta

Code World Model: Building World Models for Computation – Jacob Kahn, FAIR Meta

Jacob Kahn from FAIR, Meta, introduces the Code World Model (CWM), a new paradigm for AI models that learn from program execution rather than just code syntax. By training on detailed execution traces, CWM builds an internal world model of computation, enabling it to predict a program's behavior. This talk explores CWM's architecture, its highly scalable and asynchronous reinforcement learning setup, and groundbreaking applications like a 'neural debugger' that understands user intent from code structure and the potential to approximate undecidable problems like the halting problem.

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

The future of intelligence | Demis Hassabis (Co-founder and CEO of DeepMind)

Google DeepMind CEO Demis Hassabis discusses the path to AGI, focusing on the scientific frontiers of the next decade. He covers the importance of solving 'root node' problems like fusion energy, the challenge of 'jagged intelligence' in current models, and the promise of world models and simulations like Genie and SimA. The conversation also explores the balance between scientific rigor and commercial competition, and the profound societal and philosophical questions AGI will force us to confront.

How End-to-End Learning Created Autonomous Driving 2.0: Wayve CEO Alex Kendall

How End-to-End Learning Created Autonomous Driving 2.0: Wayve CEO Alex Kendall

Alex Kendall, CEO of Wayve, discusses the architectural shift from AV 1.0's hand-engineered robotics to AV 2.0's end-to-end deep learning. He explains how Wayve's generalization-first approach, powered by world models and diverse data, allows them to scale across hundreds of cities and multiple automotive OEMs, creating a path toward a general-purpose embodied AI foundation model.

The Godmother of AI on jobs, robots & why world models are next | Dr. Fei-Fei Li

The Godmother of AI on jobs, robots & why world models are next | Dr. Fei-Fei Li

Dr. Fei-Fei Li discusses the history of AI, from the creation of ImageNet that sparked the deep learning revolution to the future of AI with spatial intelligence and world models. She introduces 'Marble', the first large world model, and explains its potential to unlock new frontiers in robotics, virtual production, and scientific discovery, all while emphasizing a human-centered approach to technological advancement.

Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI

Building the "App Store" for Robots: Hugging Face's Thomas Wolf on Physical AI

Thomas Wolf, co-founder of Hugging Face, details the LeRobot project, aiming to replicate the success of Transformers in the robotics domain. He discusses the vision of creating a massive open-source community, tackling data scarcity, and the future of physical AI hardware, arguing that we are at a key inflection point for robotics similar to where LLMs were years ago.