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Gaussian splats look impressive—but robotics needs more than photorealism. Niantic Spatial generates an aligned collision mesh alongside every Gaussian splat, creating machine-readable digital twins with accurate geometry, depth, and collision awareness. Built for Spatial AI, Physical AI, and simulation in NVIDIA Robotics Isaac Sim. Learn more: #GaussianSplats #SpatialAI #PhysicalAI... show more

Niantic Spatial 🌎

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52,587 views • 5 days ago •via X (Twitter)

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Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation

Real → Sim → Robot — fast. With Gaussian splats, GRID brings physical assets into simulation tools like AirGen and NVIDIA Isaac Sim, enabling AI skills to be tested in sim and deployed to real robots in minutes. #Robotics #PhysicalAI #Simulation

General Robotics

12,257 views • 1 year ago

Niantic Spatial is working with Human Machine Collaboration Institute and the City of Rancho Cordova to build the foundation for the city’s first digital twin for physical AI. Roughly four square kilometers of the Innovation Region is already reconstructed and running in simulation. Read more: #NianticSpatial #PhysicalAI #DigitalTwins #SpatialAI #3DReconstruction #Robotics

Niantic Spatial is working with Human Machine Collaboration Institute and the City of Rancho Cordova to build the foundation for the city’s first digital twin for physical AI. Roughly four square kilometers of the Innovation Region is already reconstructed and running in simulation. Read more: #NianticSpatial #PhysicalAI #DigitalTwins #SpatialAI #3DReconstruction #Robotics

Niantic Spatial 🌎

28,834 views • 13 days ago

Physical AI needs more than maps, GPS, or pixels alone. It needs a living, geometrically accurate understanding of the real world. Niantic Spatial and Spexi are partnering to transform drone imagery into large-scale 3D intelligence for physical AI. 🔗Learn more: #NianticSpatial #Spexi #PhysicalAI #Reconstruction #GaussianSplat #DigitalTwins #Robotics #GeospatialAI #AI #GeospatialIntelligence #GEOINT #SpatialIntelligence

Physical AI needs more than maps, GPS, or pixels alone. It needs a living, geometrically accurate understanding of the real world. Niantic Spatial and Spexi are partnering to transform drone imagery into large-scale 3D intelligence for physical AI. 🔗Learn more: #NianticSpatial #Spexi #PhysicalAI #Reconstruction #GaussianSplat #DigitalTwins #Robotics #GeospatialAI #AI #GeospatialIntelligence #GEOINT #SpatialIntelligence

Niantic Spatial 🌎

27,560 views • 2 months ago

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.

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 views • 2 months ago

Another city. Another full 3D Gaussian Splat reconstruction. This entire neighborhood was captured while walking with an Insta360 X5, then processed with our GPU pipeline and transformed into a high-fidelity, machine-readable 3D environment with Over the Reality. What you’re seeing is not an isolated virtual world. It’s a 3D digital twin of a real-world location, built from structured spatial data where every building, street, and detail can become usable by AI, robotics, and XR. And it’s happening at scale, across cities in more than 180 countries every day. Have an Insta360 X5 and want to become a mapper? Apply here: Want to build a 3D Gaussian Splat from a video you already recorded? Do it for free at powered by Over the Reality.

Another city. Another full 3D Gaussian Splat reconstruction. This entire neighborhood was captured while walking with an Insta360 X5, then processed with our GPU pipeline and transformed into a high-fidelity, machine-readable 3D environment with Over the Reality. What you’re seeing is not an isolated virtual world. It’s a 3D digital twin of a real-world location, built from structured spatial data where every building, street, and detail can become usable by AI, robotics, and XR. And it’s happening at scale, across cities in more than 180 countries every day. Have an Insta360 X5 and want to become a mapper? Apply here: Want to build a 3D Gaussian Splat from a video you already recorded? Do it for free at powered by Over the Reality.

Over the Reality 🌐

400,097 views • 3 months ago

We built maps for people. Now, we’re building a new kind of map for robotics and AI. 🤖📍 Niantic Spatial CEO John Hanke shares why this foundation will be as essential to the future of AI as digital maps were for the web. 80% of the global economy operates in the physical world. For AI to truly scale, it must move beyond chatbots and synthetic worlds. It needs to navigate, understand, and safely interact with our reality. Read more: #PhysicalAI #SpatialIntelligence #NianticSpatial

We built maps for people. Now, we’re building a new kind of map for robotics and AI. 🤖📍 Niantic Spatial CEO John Hanke shares why this foundation will be as essential to the future of AI as digital maps were for the web. 80% of the global economy operates in the physical world. For AI to truly scale, it must move beyond chatbots and synthetic worlds. It needs to navigate, understand, and safely interact with our reality. Read more: #PhysicalAI #SpatialIntelligence #NianticSpatial

Niantic Spatial 🌎

83,003 views • 5 months ago

Introducing SimReadyGen. Agentic simulation generation for Physical AI. From a text prompt to physically accurate SimReady assets at scale. Robot training demands physically accurate environments at a scale traditional asset creation can't match. SimReadyGen closes that gap. Every generated asset carries measured physics, not estimates. Behind it is SimReady Foundry, our measured-physics pipeline: we measure how real objects behave — contact, friction, dynamics — and turn those measurements into ground-truth simulation parameters. Built on OpenUSD and integrated with NVIDIA Robotics Omniverse Libraries, SimReadyGen moves directly into Isaac Sim and Isaac Lab workflows. Try it today: Read the announcement: #PhysicalAI #Robotics #Simulation #OpenUSD

Introducing SimReadyGen. Agentic simulation generation for Physical AI. From a text prompt to physically accurate SimReady assets at scale. Robot training demands physically accurate environments at a scale traditional asset creation can't match. SimReadyGen closes that gap. Every generated asset carries measured physics, not estimates. Behind it is SimReady Foundry, our measured-physics pipeline: we measure how real objects behave — contact, friction, dynamics — and turn those measurements into ground-truth simulation parameters. Built on OpenUSD and integrated with NVIDIA Robotics Omniverse Libraries, SimReadyGen moves directly into Isaac Sim and Isaac Lab workflows. Try it today: Read the announcement: #PhysicalAI #Robotics #Simulation #OpenUSD

Lightwheel

11,643 views • 27 days ago

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.

Over the Reality 🌐

347,311 views • 3 months ago

America. Europe. Africa. Asia. Oceania. More than 250,000 real-world locations across 120+ countries have already been transformed into ultra high quality 3D Gaussian Splats by Over the Reality. From city centers and museums to beaches, mountains, and historical landmarks, every mapping created by our community contributes to a growing machine-readable representation of the physical world. This scene started as a simple Insta360 X5 recording and was transformed into a digital twin, where geometry, textures, and spatial structure are preserved and can be used by AI, Robotics, VPS, XR, and next-generation world models. This is what city-scale 3D mapping looks like. The link to become an Insta360 X5 mapper is in the first comment. 👇

America. Europe. Africa. Asia. Oceania. More than 250,000 real-world locations across 120+ countries have already been transformed into ultra high quality 3D Gaussian Splats by Over the Reality. From city centers and museums to beaches, mountains, and historical landmarks, every mapping created by our community contributes to a growing machine-readable representation of the physical world. This scene started as a simple Insta360 X5 recording and was transformed into a digital twin, where geometry, textures, and spatial structure are preserved and can be used by AI, Robotics, VPS, XR, and next-generation world models. This is what city-scale 3D mapping looks like. The link to become an Insta360 X5 mapper is in the first comment. 👇

Over the Reality 🌐

19,273 views • 2 months ago

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

Physics AI 🌊 Jensen just unveiled the NVIDIA Isaac GR00T Reference Humanoid Robot at GTC Taipei--the world’s first open-source humanoid robot reference design Built on Jetson Thor edge computing and the Isaac GR00T open platform, it features a Unitree H2 Plus body with Sharpa five-finger dexterous hands and 75 degrees of freedom. Even before Physical AI truly explodes, NVIDIA has built a complete end-to-end full-stack infrastructure: >chips (Jetson Thor + Blackwell), >synthetic data (GR00T-Dreams), >world models (Cosmos), >foundation models (GR00T N-series VLA), >high-fidelity simulation platforms (Isaac Sim + Isaac Lab + Omniverse). Dozens of humanoid robot companies ,including Agility Robotics, Aglie robotics,Boston Dynamics, Figure, 1X, NEURA Robotics, XPENG Robotics, and more are already running large-scale daily simulation training on this platform, rapidly iterating perception, reasoning, and actions in virtual environments, speeding up the jump from lab prototypes to real factory deployment. By providing an open reference design and full-stack tools, NVIDIA has dramatically lowered the barrier, letting every robotics team join the Physical AI wave with low cost and high efficiency.

CyberRobo

17,092 views • 2 months ago

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.

A 10-minute walk. That's all it takes to transform a real-world neighborhood into a machine-readable digital twin. Captured with an Insta360 X5 and reconstructed by Over the Reality, this environment is no longer just a place on a map. It's spatial data that can power Visual AI, Robotics localization, VPS, XR experiences, and next-generation world models. Today, the OVER community has already created more than 270,000 machine-readable locations like this, forming one of the world's largest 3D datasets for Physical AI, an increasingly valuable asset as demand for high quality real-world data continues to grow.

Over the Reality 🌐

16,642 views • 1 month ago

Your best Gaussian Splat might already be sitting in your Scaniverse account. The #SplatYourWorld Challenge is open through July 31. Submit your best capture for a chance to win a share of $4,000 USD in prizes. We're looking for standout 3D reconstructions of: 🏭 Industrial environments 🌲 Natural landscapes 🏙️ Urban infrastructure No need to create something new—just submit your best Gaussian Splat and put the prize money toward new gear, more captures, or whatever powers your workflow. 📅 Deadline: July 31, 11:59 PM PT Learn more: #NianticSpatial #3DReconstruction #DigitalTwins #PhysicalAI #GeospatialAI #AI #3DGS

Your best Gaussian Splat might already be sitting in your Scaniverse account. The #SplatYourWorld Challenge is open through July 31. Submit your best capture for a chance to win a share of $4,000 USD in prizes. We're looking for standout 3D reconstructions of: 🏭 Industrial environments 🌲 Natural landscapes 🏙️ Urban infrastructure No need to create something new—just submit your best Gaussian Splat and put the prize money toward new gear, more captures, or whatever powers your workflow. 📅 Deadline: July 31, 11:59 PM PT Learn more: #NianticSpatial #3DReconstruction #DigitalTwins #PhysicalAI #GeospatialAI #AI #3DGS

Niantic Spatial 🌎

26,956 views • 1 month ago

Trained a humanoid entirely in a 3D scan of the office. Zero real-world fine-tuning. It just walked in and worked. RL needs hundreds of thousands of attempts, and real robots can't afford to crash. A misjudged gap or a glass door collision breaks hardware and costs hours resetting. So you train in a sim. But sim policies usually train on randomized, untextured geometry; depth is easy to fake. The robot learns structure, not the real world: no materials, no lighting, no idea what anything actually is. RGB cameras carry all of that but training RGB policies in generic fake worlds won’t generalize to the real world. Niantic Spatial 🌎 Scaniverse reconstructs your scan of the real deployment site. One 360° camera walkthrough → photorealistic 3D Gaussian splat at metric scale → collision mesh pulled from the same reconstruction, so vision and physics match exactly. Drops straight into NVIDIA Isaac Sim/Lab, no manual conversion. Flexion simulation-first approach then seamlessly enables the training of RGB-only nav policies inside that reconstruction. With added domain randomization + large image encoders for robustness, this deploys straight to hardware. No real-world fine-tuning. Deployment: months of on-site adaptation → days. Tune into the NVIDIA livestream on 12 August to hear how these companies are closing the sim2real gap: NVIDIA Robotics ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Trained a humanoid entirely in a 3D scan of the office. Zero real-world fine-tuning. It just walked in and worked. RL needs hundreds of thousands of attempts, and real robots can't afford to crash. A misjudged gap or a glass door collision breaks hardware and costs hours resetting. So you train in a sim. But sim policies usually train on randomized, untextured geometry; depth is easy to fake. The robot learns structure, not the real world: no materials, no lighting, no idea what anything actually is. RGB cameras carry all of that but training RGB policies in generic fake worlds won’t generalize to the real world. Niantic Spatial 🌎 Scaniverse reconstructs your scan of the real deployment site. One 360° camera walkthrough → photorealistic 3D Gaussian splat at metric scale → collision mesh pulled from the same reconstruction, so vision and physics match exactly. Drops straight into NVIDIA Isaac Sim/Lab, no manual conversion. Flexion simulation-first approach then seamlessly enables the training of RGB-only nav policies inside that reconstruction. With added domain randomization + large image encoders for robustness, this deploys straight to hardware. No real-world fine-tuning. Deployment: months of on-site adaptation → days. Tune into the NVIDIA livestream on 12 August to hear how these companies are closing the sim2real gap: NVIDIA Robotics ~~ ♻️ Join the weekly robotics newsletter, and never miss any news →

Lukas Ziegler

118,434 views • 8 days ago

Historically, RL policies for robots have been trained in synthetic, untextured environments, limiting perceptive policies to depth images where the sim-to-real gap is manageable. RGB has always had more potential, but leveraging it to train policies in simulation remained an open problem. Partnering with Niantic Spatial 🌎 and NVIDIA Robotics, we built a pipeline that addresses exactly that. We can now scan a real deployment site with off-the-shelf hardware, reconstruct it into a photorealistic Gaussian splat, and run massively parallel RL training. The policies trained in our Gym environment then transfer zero-shot to the real robot and environments they were trained for. This enables faster deployment of more capable and robust policies for the end user. The new resulting capabilities are a big step towards solving sim-to-real and also apply well beyond navigation. Read the full technical breakdown on our blog; link in the comments. #HumanoidRobots #Flexion #NianticSpatial #NVIDIA

Historically, RL policies for robots have been trained in synthetic, untextured environments, limiting perceptive policies to depth images where the sim-to-real gap is manageable. RGB has always had more potential, but leveraging it to train policies in simulation remained an open problem. Partnering with Niantic Spatial 🌎 and NVIDIA Robotics, we built a pipeline that addresses exactly that. We can now scan a real deployment site with off-the-shelf hardware, reconstruct it into a photorealistic Gaussian splat, and run massively parallel RL training. The policies trained in our Gym environment then transfer zero-shot to the real robot and environments they were trained for. This enables faster deployment of more capable and robust policies for the end user. The new resulting capabilities are a big step towards solving sim-to-real and also apply well beyond navigation. Read the full technical breakdown on our blog; link in the comments. #HumanoidRobots #Flexion #NianticSpatial #NVIDIA

Flexion

71,572 views • 29 days ago

The first global, city-scale 3D map is taking shape, and it’s machine-readable. City-scale environments can now be reconstructed in high-fidelity, reaching a level of detail that is becoming almost indistinguishable from reality. This leap is made possible by large-scale mapping using just an Insta360 X5 and Over the Reality technology. So far, our dataset includes: - 220,000+ 3D mapped locations - 97M images - 1,000TB of spatial data Growing by more than 10,000+ newly mapped locations every week. Enabling Visual AI, Robotics, VPS, XR, and Digital twins.

The first global, city-scale 3D map is taking shape, and it’s machine-readable. City-scale environments can now be reconstructed in high-fidelity, reaching a level of detail that is becoming almost indistinguishable from reality. This leap is made possible by large-scale mapping using just an Insta360 X5 and Over the Reality technology. So far, our dataset includes: - 220,000+ 3D mapped locations - 97M images - 1,000TB of spatial data Growing by more than 10,000+ newly mapped locations every week. Enabling Visual AI, Robotics, VPS, XR, and Digital twins.

Over the Reality 🌐

69,822 views • 4 months ago

Have you ever seen a robot walk along a waterfront, understand its surroundings, and look out at the sea? 🤖 Thanks to Over the Reality, this is possible. Places like this are mapped every day by our global community of 360 mappers. Using our technology, they are transformed into high-fidelity machine-readable 3D Gaussian Splats. This data can be used to: • navigate robots through the physical world • train AI and Visual Models • power VPS localization • anchor persistent XR content to real-world locations This is just one of more than 250,000 real-world locations already mapped by the Over the Reality community. And unlike traditional datasets, these places can be explored directly through a smartphone, browser, or XR headset, allowing anyone to navigate and experience them in first person. From city streets and waterfronts to landmarks and cultural sites, we're building one of the world's largest machine-readable maps for AI, robotics, and spatial computing.

Have you ever seen a robot walk along a waterfront, understand its surroundings, and look out at the sea? 🤖 Thanks to Over the Reality, this is possible. Places like this are mapped every day by our global community of 360 mappers. Using our technology, they are transformed into high-fidelity machine-readable 3D Gaussian Splats. This data can be used to: • navigate robots through the physical world • train AI and Visual Models • power VPS localization • anchor persistent XR content to real-world locations This is just one of more than 250,000 real-world locations already mapped by the Over the Reality community. And unlike traditional datasets, these places can be explored directly through a smartphone, browser, or XR headset, allowing anyone to navigate and experience them in first person. From city streets and waterfronts to landmarks and cultural sites, we're building one of the world's largest machine-readable maps for AI, robotics, and spatial computing.

Over the Reality 🌐

31,824 views • 2 months ago

Since 1898, the San Francisco Ferry Building along the Embarcadero has been a gateway to the city, once bustling with ferry commuters as a primary travel hub. Today, it’s a lively marketplace where local artisans, food vendors, and a popular farmers market bring history and community to life. Using Scaniverse, Niantic Spatial captured the Ferry Building and surroundings in 3D with Gaussian splats—turning a mobile scan into an immersive, navigable digital twin. This opens up new possibilities: 🌍 urban planning, 🎟️ cultural storytelling, 🤖 robotics, and 🛍️ interactive retail & events. Learn more: #NianticSpatial #Scaniverse #3D #Gaussiansplat #Digitaltwins

Since 1898, the San Francisco Ferry Building along the Embarcadero has been a gateway to the city, once bustling with ferry commuters as a primary travel hub. Today, it’s a lively marketplace where local artisans, food vendors, and a popular farmers market bring history and community to life. Using Scaniverse, Niantic Spatial captured the Ferry Building and surroundings in 3D with Gaussian splats—turning a mobile scan into an immersive, navigable digital twin. This opens up new possibilities: 🌍 urban planning, 🎟️ cultural storytelling, 🤖 robotics, and 🛍️ interactive retail & events. Learn more: #NianticSpatial #Scaniverse #3D #Gaussiansplat #Digitaltwins

Niantic Spatial 🌎

11,988 views • 4 months ago

3d visual positioning experiment -- look at the alignment between the 3d mesh and the live camera view. Truly feels magical -- like x-ray vision. Workflow: 1. Scanned a street in 15 mins w/ xgrids 2. Localized against that scan at night, in real-time, while sitting in a car The xgrids scanner (w/ rgb + lidar) is perfect to build maps for humans (3d gaussian splats). Then multiset ai makes it easy to build machine-readable maps for AR and robotics to figure out exactly where they are in 3d space with cm-level accuracy.

3d visual positioning experiment -- look at the alignment between the 3d mesh and the live camera view. Truly feels magical -- like x-ray vision. Workflow: 1. Scanned a street in 15 mins w/ xgrids 2. Localized against that scan at night, in real-time, while sitting in a car The xgrids scanner (w/ rgb + lidar) is perfect to build maps for humans (3d gaussian splats). Then multiset ai makes it easy to build machine-readable maps for AR and robotics to figure out exactly where they are in 3d space with cm-level accuracy.

Bilawal Sidhu

27,278 views • 8 months ago

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.

Modern AI is confined to the digital world. At Skild AI, we are building towards AGI for the real world, unconstrained by robot type or task — a single, omni-bodied brain. Today, we are sharing our journey, starting with early milestones, with more to come in the weeks ahead. Our Mission: Artificial General Intelligence grounded in the physical world. We believe AGI that can truly understand and reason in the real world can only be built through grounding in the physical world. Our Vision: Any robot, Any task, One brain. We tackle robotics in its full generality – building a continually improving, omni-bodied brain that can control any hardware for any task. Who are we? A passionate group of scientists & engineers driven by our shared vision. We have been researching AI and robotics for more than a decade. Our team includes pioneers of self-supervised learning, curiosity-driven exploration, end-to-end sim2real for visual locomotion, dexterous manipulation, learning from human videos, robot parkour, and many more. Many of these works have won awards at top-tier AI and Robotics conferences. Our team has also built production-ready systems at Anduril, Tesla, Nvidia, Meta, Kitty Hawk, Google, Everyday Robotics, and Amazon. Join us in our mission to build the robot brains of tomorrow.

Skild AI

383,478 views • 1 year ago