LingBot World Infinity, Real-Time Exploration of Infinite Worlds
Summary
LingBot World Infinity enables real-time exploration of infinite virtual worlds, likely powered by an AI bot assistant.
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This paper introduces LingBot-World 2.0, an advanced world modeling system with unbounded interaction horizons, real-time 720p 60fps video generation, diverse interactive elements (e.g., attacking, spell-casting), and novel multi-agent behavior control via pilot and director agents, along with a shared multi-player interface.
@FinanceYF5: 1/ Most AI "world models" suffer from visual collapse and scene drift after just a few minutes of running. @robbyant_brain just open-sourced LingBot-World 2.0 (Infinity): supports hour-level real-time generation, no quality degradation over long runs, stable 720p/60fps output. This is...
LingBot-World 2.0 (Infinity) has just been open-sourced, supporting hour-level real-time generation with no quality degradation over long runs and stable 720p/60fps output. It's a key step for robots to learn to predict the world.
@aigclink: Robbyant, Ant Group's embodied AI company, open-sourced the world model LingBot-World 2.0—capable of running continuously for over an hour with no noticeable degradation in image quality, and equipped with a brain-cerebellum-like agentic harness that allows the world to unfold persistently in response to user actions. The previous world…
Robbyant under Ant Group open-sourced the world model LingBot-World 2.0, supporting continuous operation for over an hour with no quality degradation, featuring a brain-cerebellum-like agentic harness, multiplayer support, and multiple interaction actions. Weights and code are open-sourced.
Project Genie: Experimenting with infinite, interactive worlds
Google has launched Project Genie, an experimental prototype for Google AI Ultra subscribers that allows users to create, explore, and remix infinite interactive worlds using Genie 3.
robbyant/lingbot-map
LingBot-Map is a feed-forward 3D foundation model for streaming 3D reconstruction that uses a Geometric Context Transformer architecture, achieving state-of-the-art performance with efficient ~20 FPS inference on long sequences exceeding 10,000 frames.