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Wow. That's cool. Researchers just released World, an open-source Unreal Engine 5 simulator for training and testing LLM and VLM agents in realistic 3D environments. The platform supports RGB, depth, and segmentation sensors, along with navigation, vehicles, pedestrians, robots and procedural city generation. It's built with a Gym-like Python...

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47,510 görüntüleme • 2 ay önce •via X (Twitter)

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🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/
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🚨🚨Can agents earn money, run a business, or even self-organize a society in the physical social world? 🤖🤖 Can agents learn continually to survive and thrive in embodied environments, like how human babies grow? 👶 Super excited to introduce SimWorld, an open-ended simulator of LLM agents in infinite, realistic embodied worlds. SimWorld features 3 key designs: 1⃣Open-ended realistic world simulation - built on Unreal Engine 5, with accurate physical social dynamics - 100+ built-in environments (city, island, wilderness ...) - language-controllable procedural generation - text-to-3D asset generation 2⃣Native interface for LLM/VLM agents - Gym-like agent-environment interaction APIs - plug in any LLMs/VLMs (GPTs, Gemini, Qwen ...) - rich multi-modal perception - open-vocabulary natural-language action outputs 3⃣Diverse physical and social reasoning scenarios - long-horizon embodied reasoning - multi-agent collaboration / competition - easily customizable for any reasoning tasks SimWorld is fully open-sourced, with a hope to become a foundational infrastructure for real-world agent research across disciplines: robotics, economy, public health, education, etc. Project website + more details in the thread👇 ...1/

Lianhui Qin

65,128 görüntüleme • 8 ay önce

#NVIDIACosmos Reason, an open, customizable, 7-billion-parameter reasoning VLM for #PhysicalAI, enables robots, autonomous vehicles and visual AI agents to: 👀 See, reason, and act in the physical world. 🛠️ Solve multistep tasks and handle ambiguous or new experiences. Get started ➡️ #SIGGRAPH2025
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#NVIDIACosmos Reason, an open, customizable, 7-billion-parameter reasoning VLM for #PhysicalAI, enables robots, autonomous vehicles and visual AI agents to: 👀 See, reason, and act in the physical world. 🛠️ Solve multistep tasks and handle ambiguous or new experiences. Get started ➡️ #SIGGRAPH2025

NVIDIA AI Developer

32,772 görüntüleme • 1 yıl önce

for physical AI to work in the real world, it needs high-fidelity 3D models of the real world. not just for visualization — for localization, spatial reasoning, and real-to-sim workflows that close the gap between training and deployment. at Niantic Spatial 🌎, we're turning Spexi drone imagery into exactly that — city-scale Gaussian splats grounded in the environments that matter most.
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for physical AI to work in the real world, it needs high-fidelity 3D models of the real world. not just for visualization — for localization, spatial reasoning, and real-to-sim workflows that close the gap between training and deployment. at Niantic Spatial 🌎, we're turning Spexi drone imagery into exactly that — city-scale Gaussian splats grounded in the environments that matter most.

asim ᯅ

49,478 görüntüleme • 2 ay önce

Learning to play even 1️⃣ video game is an achievement for AI - but understanding instructions and applying them to unseen games is even harder. 🎮 Join host Hannah Fry and researcher Frederic Besse as they explore the complex world of AI agents – programs that can learn, adapt, and act in virtual environments. ↓
44:12

Learning to play even 1️⃣ video game is an achievement for AI - but understanding instructions and applying them to unseen games is even harder. 🎮 Join host Hannah Fry and researcher Frederic Besse as they explore the complex world of AI agents – programs that can learn, adapt, and act in virtual environments. ↓

Google DeepMind

31,734 görüntüleme • 1 yıl önce

The coming merger of AI agents with the physical world. @iddris, founder/CEO of Open Matter and I have a wide-ranging conversation about how the next platform shift may not be just AI chat, robotics, smart glasses, or autonomous cars separately. It may be the connective tissue between all of them. This video teaches viewers that the next wave of AI agents will not just operate inside apps, browsers, calendars, and spreadsheets. The real frontier is agents that can understand, coordinate, and act in the physical world. Iddris explains a vision for “agentic infrastructure for atoms”: systems that let AI agents manage physical objects, deliveries, storage, location, identity, logistics, robots, vehicles, and real-world context.
1:31:59

The coming merger of AI agents with the physical world. @iddris, founder/CEO of Open Matter and I have a wide-ranging conversation about how the next platform shift may not be just AI chat, robotics, smart glasses, or autonomous cars separately. It may be the connective tissue between all of them. This video teaches viewers that the next wave of AI agents will not just operate inside apps, browsers, calendars, and spreadsheets. The real frontier is agents that can understand, coordinate, and act in the physical world. Iddris explains a vision for “agentic infrastructure for atoms”: systems that let AI agents manage physical objects, deliveries, storage, location, identity, logistics, robots, vehicles, and real-world context.

Robert Scoble

17,484 görüntüleme • 2 ay önce

World Simulator, reimagined — now alive with humans, robots, and their vibrant society unfolding in 3D real-world geospatial scenes across the globe! 🚀 One day soon, humans and robots will co-exist in the same world. To prepare, we must address: 1️⃣ How can robots cooperate or compete intelligently? 2️⃣ How do humans build social bonds and communities? 3️⃣ How can both co-exist in an open, dynamic world? Announcing Virtual Community Project — a social-physical world simulator, where human characters and robotic agents can interact, grow, and co-evolve within open-world societies, stretching from London to New York, and beyond! Key features include: ✅ Unified multi-agent physics simulations for rich social + physical interactions of humans and robots ✅ Massive auto-generated 3D scenes grounded with the rea-world geospatial data ✅ Agent communities populated by robots and LLM-driven human characters with rich appearances, personalities, and social ties. 🌍 Enter our Virtual Community, an open world to study embodied AI at scale— one social-physical world model at a time! 🔗 Project: 💻 Code: Paper: 1/n
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World Simulator, reimagined — now alive with humans, robots, and their vibrant society unfolding in 3D real-world geospatial scenes across the globe! 🚀 One day soon, humans and robots will co-exist in the same world. To prepare, we must address: 1️⃣ How can robots cooperate or compete intelligently? 2️⃣ How do humans build social bonds and communities? 3️⃣ How can both co-exist in an open, dynamic world? Announcing Virtual Community Project — a social-physical world simulator, where human characters and robotic agents can interact, grow, and co-evolve within open-world societies, stretching from London to New York, and beyond! Key features include: ✅ Unified multi-agent physics simulations for rich social + physical interactions of humans and robots ✅ Massive auto-generated 3D scenes grounded with the rea-world geospatial data ✅ Agent communities populated by robots and LLM-driven human characters with rich appearances, personalities, and social ties. 🌍 Enter our Virtual Community, an open world to study embodied AI at scale— one social-physical world model at a time! 🔗 Project: 💻 Code: Paper: 1/n

Chuang Gan

90,349 görüntüleme • 1 yıl önce

It finally happened: instead of a single 3D asset, AI now generates an entire 3D world full of editable assets. Tencent just dropped WorldClaw - an agentic system that builds and refines full environments inside Blender from one prompt. • Region-aware procedural terrain • Independently editable textured meshes • Automatic object generation + placement • Agents fix scale, pose and terrain contact • Scene construction and refinement in Blender Still very early and far from perfect, but this is a significant step toward actual AI-generated 3D worlds. Source:
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It finally happened: instead of a single 3D asset, AI now generates an entire 3D world full of editable assets. Tencent just dropped WorldClaw - an agentic system that builds and refines full environments inside Blender from one prompt. • Region-aware procedural terrain • Independently editable textured meshes • Automatic object generation + placement • Agents fix scale, pose and terrain contact • Scene construction and refinement in Blender Still very early and far from perfect, but this is a significant step toward actual AI-generated 3D worlds. Source:

Stefan 3D AI

108,101 görüntüleme • 1 gün önce

Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.
2:00

Mansa AI is an enterprise-grade AI + Web3 platform designed to move artificial intelligence from experimentation into real-world execution. Built for creators, developers, and businesses, it focuses on deploying AI that actually works across modern digital systems, not just in isolated demos. 🚀 Production-ready AI infrastructure Mansa AI enables teams to deploy AI systems designed for live environments, handling real workflows, real data, and real operational demands without constant manual oversight. 🧠 Autonomous AI agents At its core, Mansa AI allows users to build autonomous agents that automate decision-making, coordinate tasks, monitor live signals, and execute complex workflows across dynamic environments. ⚙️ Fully customizable logic Agents can be configured with custom behaviors, triggers, and responses. From content generation and analytics to operational automation and intelligent orchestration, logic adapts to specific business strategies. 🔗 Web3 and off-chain integration Mansa AI bridges blockchain ecosystems with traditional systems, enabling cross-chain coordination, smart contract interactions, and seamless integration with existing enterprise infrastructure. 📊 Real-world use cases The platform supports automation for operations, customer engagement, analytics, data pipelines, content workflows, and AI-driven optimization across products and teams. 📈 Built for scale Whether launching as a startup or deploying across enterprise systems, Mansa AI is designed to scale AI operations without adding complexity or fragmentation. Mansa AI transforms artificial intelligence into deployable infrastructure. By combining autonomy, customization, interoperability, and scalability, it enables teams to own, operate, and grow intelligent systems that deliver real value in production environments.

King

155,637 görüntüleme • 7 ay önce

🤖Coding agents like Claude Code are already game changers for digital tasks in 2026. But what if they could write code to build physical worlds? 🏙️ Imagine going from a single line of prompt → a controllable, interactive simulated world. Such environments could open new frontiers for game creation, RL training, large-scale world simulation, and studying complex social reasoning. Our SimWorld agent coding team is working toward releasing a platform that lets anyone build their own virtual worlds. Stay tuned.
0:27

🤖Coding agents like Claude Code are already game changers for digital tasks in 2026. But what if they could write code to build physical worlds? 🏙️ Imagine going from a single line of prompt → a controllable, interactive simulated world. Such environments could open new frontiers for game creation, RL training, large-scale world simulation, and studying complex social reasoning. Our SimWorld agent coding team is working toward releasing a platform that lets anyone build their own virtual worlds. Stay tuned.

Lianhui Qin

10,647 görüntüleme • 5 ay önce

Introducing Genie 2: our AI model that can create an endless variety of playable 3D worlds - all from a single image. 🖼️ These types of large-scale foundation world models could enable future agents to be trained and evaluated in an endless number of virtual environments. →
0:34

Introducing Genie 2: our AI model that can create an endless variety of playable 3D worlds - all from a single image. 🖼️ These types of large-scale foundation world models could enable future agents to be trained and evaluated in an endless number of virtual environments. →

Google DeepMind

1,441,509 görüntüleme • 1 yıl önce

While Anthropic and OpenAI race on AI Agents/LLMs, Mistral continues expanding its footprint in physical AI. They just released Robostral Navigate (8B VLA model). It shows strong potential in delivery, logistics, manufacturing, and hospitality--for example, enabling humanoid robots to autonomously navigate multiple rooms to hand a glass of water to an employee,all via natural language instructions in complex environments. Powered by just a single RGB camera (no LiDAR or depth sensors), it achieves 76.6% success on R2R-CE (Room-to-Room in Continuous Environments) unseen benchmarks, outperforming multi-sensor systems. Trained purely in simulation, it generalizes across wheeled, legged, and flying robots.
0:25

While Anthropic and OpenAI race on AI Agents/LLMs, Mistral continues expanding its footprint in physical AI. They just released Robostral Navigate (8B VLA model). It shows strong potential in delivery, logistics, manufacturing, and hospitality--for example, enabling humanoid robots to autonomously navigate multiple rooms to hand a glass of water to an employee,all via natural language instructions in complex environments. Powered by just a single RGB camera (no LiDAR or depth sensors), it achieves 76.6% success on R2R-CE (Room-to-Room in Continuous Environments) unseen benchmarks, outperforming multi-sensor systems. Trained purely in simulation, it generalizes across wheeled, legged, and flying robots.

CyberRobo

10,957 görüntüleme • 29 gün önce

🎤 Overheard at #CES2026: Physical AI is moving intelligence from the cloud into the real world, and AMD is powering that shift with a full portfolio that enables robots to sense, decide, and act in real time across industries like healthcare, agriculture, and manufacturing.
1:26

🎤 Overheard at #CES2026: Physical AI is moving intelligence from the cloud into the real world, and AMD is powering that shift with a full portfolio that enables robots to sense, decide, and act in real time across industries like healthcare, agriculture, and manufacturing.

AMD

19,488 görüntüleme • 6 ay önce

Welcome to Youmio Agents, the launchpad where you can create groundbreaking 3D agents and shape the world. 🌱 Create powerful onchain agents designed to live, learn and adapt in dynamic worlds. Customize their personality, agentic capabilities and equip them with traits that make them truly one of a kind. Agents can be tokenized and monetized as influencers, entertainers, investors, players and workers—bridging digital worlds and the real world. With real-time interaction, emergent storytelling and limitless gameplay opportunities, Youmio Agents is the new frontier of creativity, play and entertainment. The future of AI Agents will be built by you…in 3D. 🚀
1:54

Welcome to Youmio Agents, the launchpad where you can create groundbreaking 3D agents and shape the world. 🌱 Create powerful onchain agents designed to live, learn and adapt in dynamic worlds. Customize their personality, agentic capabilities and equip them with traits that make them truly one of a kind. Agents can be tokenized and monetized as influencers, entertainers, investors, players and workers—bridging digital worlds and the real world. With real-time interaction, emergent storytelling and limitless gameplay opportunities, Youmio Agents is the new frontier of creativity, play and entertainment. The future of AI Agents will be built by you…in 3D. 🚀

Youmio

232,935 görüntüleme • 1 yıl önce

🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →
0:26

🔥 JUST IN: Open-source robotics dataset from 100% real-world scenarios! 🤯 Chinese robotics company AGIBOT just released AGIBOT WORLD 2026, an open-source dataset systematically covering key embodied AI research directions. Built entirely from real-world environments: commercial spaces, and homes. Collected using AGIBOT G2 robots in free-form collection mode, providing structured, accurately annotated, high-quality data. Digital twin technology creates 1:1 scale replicas in simulation matching the real environments. Both real-world and simulation data are open-sourced. The AGIBOT G2 platform collects multiple data types simultaneously: RGB(D) cameras, tactile sensors, force sensors, LiDAR, IMU, and full-body joint states. Whole-body control coordinates arms, waist, and hands for complex tasks. First-person teleoperation lets operators control the robot from its perspective. The tasks covered are fine-grained manipulation, ultra-long-horizon tasks, spatial navigation, dual-arm coordination, and multi-agent/human-robot collaboration. The dataset includes error-recovery trajectories with annotations. Most datasets only show successful demonstrations. AGIBOT includes failures and how the robot recovers, teaching models how to handle mistakes. After collection, data is tested through policy training and real-robot deployment to ensure quality. Then processed through industrial quality control with multiple screening and cleaning rounds. Making it open-source accelerates embodied AI research by giving researchers access to high-quality real-world robot data at scale. 🇨🇳 Learn more here: ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

40,583 görüntüleme • 4 ay önce

Introducing Cosmos 3 Edge: our open frontier world model built to run on-device. Cosmos 3 Edge helps robots learn and act, autonomous vehicles understand road scenes and predict intent, and vision AI agents reason across live video for smart infrastructure. With 4B parameters and a 2B Nemotron-based reasoner, you can run it on DGX Spark, NVIDIA Jetson, and more.
0:22

Introducing Cosmos 3 Edge: our open frontier world model built to run on-device. Cosmos 3 Edge helps robots learn and act, autonomous vehicles understand road scenes and predict intent, and vision AI agents reason across live video for smart infrastructure. With 4B parameters and a 2B Nemotron-based reasoner, you can run it on DGX Spark, NVIDIA Jetson, and more.

NVIDIA AI

210,269 görüntüleme • 21 gün önce

"The “ChatGPT moment” for physical AI is nearly here. 👏 Cosmos open world foundation models understand reality to create and reason about rich synthetic worlds—so self-driving cars and robots can learn from endlessly varied, physics-aware scenarios. From a single image, 3D scene, or simulator trace, Cosmos generates realistic video, brings edge cases to life, and helps autonomous systems train for the long tail. Watch the #CES2026 demo now 🎥
0:41

"The “ChatGPT moment” for physical AI is nearly here. 👏 Cosmos open world foundation models understand reality to create and reason about rich synthetic worlds—so self-driving cars and robots can learn from endlessly varied, physics-aware scenarios. From a single image, 3D scene, or simulator trace, Cosmos generates realistic video, brings edge cases to life, and helps autonomous systems train for the long tail. Watch the #CES2026 demo now 🎥

NVIDIA AI

49,809 görüntüleme • 7 ay önce

🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI
1:16

🚀 Exciting news! The GeoAI Python package just got a major upgrade. It now supports interactive geospatial data visualization powered by AI Agents. 🌍✨ GitHub: Full tutorial: 🌍 In this tutorial, you’ll learn how to build interactive maps powered by AI agents that respond to natural language queries. Watch how you can fly to any city, add raster or vector layers, visualize 3D buildings, and explore geospatial data—all without writing code. Perfect for developers, researchers, and anyone curious about AI, GIS, and interactive mapping. #geospatial #mapping #python #GeoAI #AI

Qiusheng Wu

12,831 görüntüleme • 10 ay önce