World Models

Simulating Humanity: from Generative Agents to 8 Billion Digital Twins — Joon Sung Park, Simile AI

Aug 21, 2026 · 1:11:01

Joon Sung Park, co-founder and CEO of Simile AI, joins Latent Space to argue that simulating humans requires bespoke behavior models, not just frontier LLMs, a bet rooted in his Generative Agents/Smallville paper. Frontier models optimized to be rational miss how people actually err, scoring 20–30% on niche populations, whereas Simile's digital twins match people's own responses 85% of the time. He details the three data buckets—interviews, observational data, and randomized controlled trials—and shows how companies use the platform for concept testing, A/B tests, and earnings calls. Park also shares the scaling-law glimpse in simulation, the economics of data-center-scale worlds, and his vision of simulating all 8 billion people to tackle wicked problems like climate change and UBI, with Thomas Schelling's agent-based models as precedent.

Why AI Agents Don't Actually Understand You — Danielle Perszyk, Amazon AGI Lab

Jul 11, 2026 · 48:54

Danielle Perszyk of Amazon's AGI Lab argues that AI agents fail because they don't truly understand users — they model tasks but not the human mind, so reliability must shift from clicking correctly to aligning representations. She explains how Amazon's AGI Lab, seeded by the former Adept team, builds perception agents that perceive digital environments like humans and interact in real time, moving beyond chatbots and coding agents. The lab is exploring new architectures for episodic memory, social world models, and multi-agent systems where agents fluidly negotiate meaning, inspired by human collective intelligence. Perszyk warns that current AI homogenizes thinking, reducing human agency, and advocates for a diverse society of AIs with different biases to augment rather than replace human cognition. She discusses how aligning AI's goals with inferring and matching human representations could unlock generalization and make agents genuinely collaborative, from automating digital drudgery to transforming education with Socratic tutors.

Inside xAI: Building Grok Imagine in 3 Months, Videogen vs World Models, and Video Agents— Ethan He

Jun 1, 2026 · 1:44:43

Ethan He, former xAI and NVIDIA Cosmos researcher, explains how xAI built its first image and video models (Grok Imagine 0.9) from zero to one in three months, attributing rapid iteration to small teams with minimal meetings and strong infra that enabled fixing tiny data and training bugs for biggest quality gains. He argues that most improvements in video generation now come from language models and agents rather than diffusion technology, predicting that by end of 2025 video agents will produce production-grade content for ads. He defines world models as real-time, interactive, long-horizon videos, and details challenges like temporal compression, context management, and the high cost of storing and moving video data (e.g., tens of petabytes for a billion videos). Ethan also shares why he left xAI to focus on language model research, believing the next frontier is models that manage their own context length, similar to solutions already being explored in video generation.

Moonlake: Interactive, Multimodal World Models — with Chris Manning and Fan-yun Sun

Apr 2, 2026 · 1:06:48

Moonlake AI founders Chris Manning and Fan-yun Sun argue that interactive, multimodal world models require structured symbolic reasoning over pure scale, enabling indefinite multiplayer gameplay and causal consistency that video generation models like Genie and Sora cannot achieve. Their approach uses code engines and physics simulators as cognitive tools, producing reasoning traces that handle geometry, physics, and logic, while a separate diffusion model (Reverie) handles pixel fidelity. They aim to replace traditional rendering and empower creators by allowing human intent to be injected at a symbolic layer. Manning contrasts this with Yann LeCun's JEPA, emphasizing language and abstraction over pixel-level prediction. Moonlake is hiring engineers at the intersection of code generation, computer vision, and graphics.

World Models & General Intuition: Khosla's largest bet since LLMs & OpenAI

Dec 6, 2025 · 1:04:51

Pim de Wit, founder of Medal and General Intuition (GI), turned down a reported $500M offer from OpenAI to spin out GI with a $134M seed from Khosla Ventures — Vinod Khosla's largest bet since OpenAI — arguing that world models trained on peak human gameplay are the next frontier after LLMs. Medal's 12M users generate 3.8B action-labeled clips via retroactive recording, creating a privacy-preserving dataset of 'episodic memory for simulation.' GI builds fully vision-based agents that see only frames and output actions in real-time, using pure imitation learning without RL, and can transfer from arcade games to realistic games to real-world video. Pim explains why world models need actions, memory, and partial observability (e.g., smoke, camera shake) compared to video generation, and how they distill giant policies into tiny real-time models that navigate and hide like humans. He recounts his path from running the largest RuneScape private server to reverse engineering, cold-emailing the Diamond (world model) paper authors to assemble a top research team, and advises data founders to train models themselves before selling. GI's near-term customers are game developers replacing…

After LLMs: Spatial Intelligence and World Models — Fei-Fei Li & Justin Johnson, World Labs

Nov 25, 2025 · 1:00:39

World Labs co-founders Fei-Fei Li and Justin Johnson argue that spatial intelligence is the next frontier beyond LLMs, with their product Marble generating editable 3D worlds from text or images using Gaussian splats. They claim language is a lossy channel for describing the rich 3D/4D world, while spatial intelligence handles everything from picking up a mug to inferring DNA's double helix. Marble already serves gaming, VFX, and film, with precise camera control and real-time rendering on phones and VR headsets. They discuss scaling compute from AlexNet to today's million-fold increase, why world models can 'soak up' modern GPU clusters better than language alone, and the gap between pattern-fitting and causal understanding in physics. Fei-Fei worries more about under-resourced academia than open vs. closed models, advocating for national AI compute clouds and open benchmarks like the BEHAVIOR dataset. Justin notes transformers are natively set models, not sequence models, opening architectural possibilities for new spatial data.

Priscilla Chan and Mark Zuckerberg: Frontier AI + Virtual Biology To Solve All Diseases

Nov 6, 2025 · 53:34

Priscilla Chan and Mark Zuckerberg, co-founders of CZI's Biohub, explain their ten-year shift from broad philanthropy to a focused mission of building frontier AI and virtual biology to cure all diseases. They argue that tool-building — from 12-foot microscopes to the 125-million-cell CELLxGENE atlas — is the essential, underfunded work that enables scientific breakthroughs. The couple details how their Biohub model combines frontier biology (e.g., spatial imaging, cellular engineering) with frontier AI (models like rBio and VariantFormer) to create a hierarchical virtual cell, eventually expanding to a virtual immune system. They emphasize that data generation must precede modeling, citing the decade-long Human Cell Atlas as foundational, and note that AI timelines may accelerate their 100-year goal significantly sooner. The episode closes with a call for biologists and engineers to collaborate, use their open models, and help generate data that grounds these next-generation tools.

This World Does Not Exist — Joscha Bach, Karan Malhotra, Rob Haisfield (WorldSim, WebSim, Liquid AI)

Apr 27, 2024 · 1:56:11

The episode features Karan Malhotra demoing WorldSim, a prompt that turns Claude 3 into a universe simulator via CLI; Rob Haisfield presenting WebSim, which generates functional websites on the fly; and Joscha Bach arguing simulative AI reveals consciousness as a virtual property, with LLMs creating agents as real as human minds, urging the California Institute for Machine Consciousness to build self-organizing silicon life. Malhotra shows WorldSim running “world.exe” to create Twitter inside a simulated universe, with users tweeting and Elon Musk moving Dogecoin. Haisfield demonstrates WebSim generating a 5D particle interface, a news RSS aggregator, and a face-swap webcam app via URL parameters like “secrets=revealed”. Bach explains consciousness as second-order perception in a simulated now, criticizes RLHF for lobotomizing models, and advocates for animist AI where software agents compete like spirits, not golems.