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VPS or visual positioning system... this is how AR glasses and robots will understand where they are in the real world and know where to go. It’s also how you can spatially annotate reality with cm level accuracy - all using a machine readable model of the world.

Bilawal Sidhu

119,821 subscribers

28,085 просмотров • 11 месяцев назад •via X (Twitter)

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Комментарии: 12

Фото профиля Bilawal Sidhu

Bilawal Sidhu11 месяцев назад

Workflow: @XGRIDS2023 (capture) —> @multiset_ai (VPS)

Фото профиля David Raz

David Raz11 месяцев назад

@grok what is the current SOTA VPS? Compare it to SOTA visual SLAM in terms of performance, efficiency and reliability.

Фото профиля ⚡️Boltbet⚡️

⚡️Boltbet⚡️11 месяцев назад

⚡️⚡️

Фото профиля Sriram K

Sriram K11 месяцев назад

The real challenge is keeping that 'machine readable model of the world' up to date at scale. The world doesn't sit still. The data and infra problem is massive.

Фото профиля Bilawal Sidhu

Bilawal Sidhu11 месяцев назад

Ah yes the elusive life long mapping problem. Conveniently we are proliferating the world with all sorts of sensors. Still a very hard problem.

Фото профиля ZIAISTAN

ZIAISTAN11 месяцев назад

cm level positioning will change everything good work amazing future ahead

Фото профиля Jan Verwoerd

Jan Verwoerd11 месяцев назад

I might have a cool usecase already. Is it ready to spawn a scene based on the VPS? We already have the portalcam

Фото профиля Bilawal Sidhu

Bilawal Sidhu11 месяцев назад

Yup, you can place everything relative to the map space object and it’ll all show up correctly after localization in @multiset_ai

Фото профиля NextPlay

NextPlay11 месяцев назад

cm accuracy cute

Фото профиля Faysal Bakziz

Faysal Bakziz9 месяцев назад

Organizations implement SEO effectively by aligning initiatives with strategic goals.

Фото профиля Torsten Jacobi

Torsten Jacobi11 месяцев назад

If that does not look like Terminator what does ?

Фото профиля Zara Techie

Zara Techie11 месяцев назад

Exciting future tech advancements! Can't wait to see it in action.

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You've probably heard about GPS. But have you heard about VPS? It's the visual positioning tech that gives robots and AR glasses centimeter-level accuracy where GPS fails. Here's how it works: 0:00 - Intro 0:19 - How GPS Actually Works 1:28 - The Problem with GPS for AR & Robotics 2:06 - What is VPS? (Visual Positioning System) 2:38 - Use Cases: Delivery Robots & Drones 3:17 - VPS in Action: Apple Vision Pro & Meta Quest 3:53 - Scanning Your World with an iPhone (Multiset AI) 4:31 - Key Takeaways 4:48 - The Future: Spatial Intelligence

You've probably heard about GPS. But have you heard about VPS? It's the visual positioning tech that gives robots and AR glasses centimeter-level accuracy where GPS fails. Here's how it works: 0:00 - Intro 0:19 - How GPS Actually Works 1:28 - The Problem with GPS for AR & Robotics 2:06 - What is VPS? (Visual Positioning System) 2:38 - Use Cases: Delivery Robots & Drones 3:17 - VPS in Action: Apple Vision Pro & Meta Quest 3:53 - Scanning Your World with an iPhone (Multiset AI) 4:31 - Key Takeaways 4:48 - The Future: Spatial Intelligence

Bilawal Sidhu

14,757 просмотров • 9 месяцев назад

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 🌐

32,085 просмотров • 5 месяцев назад

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 🌐

347,424 просмотров • 5 месяцев назад

Niantic and Snap partnership: AR devs will be able to use Niantic VPS to place content at millions of real-world locations with centimeter-level accuracy

Niantic and Snap partnership: AR devs will be able to use Niantic VPS to place content at millions of real-world locations with centimeter-level accuracy

Chubby♨️

41,250 просмотров • 1 год назад

imagine a world where geospatial AI, VPS, and AR glasses meet. we’re actively exploring the magic of what that looks like with Dots as spatially intelligent agents for navigation. cc: Spectacles Peridot Niantic Spatial 🌎 ICYMI, we also announced our multi-year strategic partnership, including an investment from Snap Inc., to build the next-gen AI-powered map of the real world.

imagine a world where geospatial AI, VPS, and AR glasses meet. we’re actively exploring the magic of what that looks like with Dots as spatially intelligent agents for navigation. cc: Spectacles Peridot Niantic Spatial 🌎 ICYMI, we also announced our multi-year strategic partnership, including an investment from Snap Inc., to build the next-gen AI-powered map of the real world.

asim ᯅ

51,901 просмотров • 1 год назад

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

27,541 просмотров • 11 месяцев назад

With Scaniverse, every space can be captured, digitized, and transformed into a living, machine-readable twin. At Super Bowl LX Innovation Summit, we turned the venue into a live digital twin in minutes. Powered by Visual Positioning System, robots and phones shared the same spatial understanding — unlocking a true shared reality. Read more: #NianticSpatial #SuperBowl #Scaniverse #DigitalTwin #GaussianSplat #VPS #AI

With Scaniverse, every space can be captured, digitized, and transformed into a living, machine-readable twin. At Super Bowl LX Innovation Summit, we turned the venue into a live digital twin in minutes. Powered by Visual Positioning System, robots and phones shared the same spatial understanding — unlocking a true shared reality. Read more: #NianticSpatial #SuperBowl #Scaniverse #DigitalTwin #GaussianSplat #VPS #AI

Niantic Spatial 🌎

11,594 просмотров • 8 месяцев назад

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 🌐

16,816 просмотров • 3 месяцев назад

Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact:

Building a machine learning model isn’t just about finding the right algorithm—it’s about the right process. In Machine Learning in Production, Andrew Ng breaks down the iterative loop of model development: training, error analysis, refining hyperparameters, and improving data. Getting to a high test set accuracy is one thing, but aligning your model with real-world business metrics? That’s where the real challenge begins. Learn how to bridge the gap between models and impact:

DeepLearning.AI

45,348 просмотров • 1 год назад

VPS 2.0 Outperforms GPS Alone. Niantic Spatial’s Visual Positioning System (VPS) matches live camera data to a spatial model for precise 6DoF localization—indoors, outdoors, and in complex environments where GPS fails. 🔹 ~10-15cm accuracy in mapped areas 🔹 Works in GPS-denied environments 🔹 Persistent spatial anchors Explore this deep dive to learn how VPS works: #NianticSpatial #Scaniverse #VPS #GIS #GeospatialAI #GEOINT #PhysicalAI #AI #Robotics

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Niantic Spatial 🌎

19,782 просмотров • 6 месяцев назад

First demo of our new aerial Visual-Inertial Positioning System (VIO+VPS): 40m positioning accuracy (CEP) in a 50 kilometer flight using a camera, consumer-grade IMU and a barometer! No GPS

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Otto Seiskari

101,767 просмотров • 2 лет назад

They say the SpaceX IPO will be a rocket. We couldn't wait. So we launched one in the middle of Udine. Thanks to Over the Reality's city-scale 3D mapping and VPS technology, anyone can place and experience massive AR content anchored to the real world with centimeter-level precision. The future isn't on a screen. It's in the world around you.

They say the SpaceX IPO will be a rocket. We couldn't wait. So we launched one in the middle of Udine. Thanks to Over the Reality's city-scale 3D mapping and VPS technology, anyone can place and experience massive AR content anchored to the real world with centimeter-level precision. The future isn't on a screen. It's in the world around you.

Over the Reality 🌐

20,208 просмотров • 4 месяцев назад

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”

Elon just dropped a MAJOR nugget on how Tesla is going to be training Optimus to do real world tasks. They are building an Optimus Academy, which is a large scale, dedicated real-world training facility to accelerate the development of Optimus. The Academy will deploy thousands of Optimus units, potentially 10,000 to 30,000 robots, in a controlled realistic environment where they perform self-play, experiment with tasks, iterate on behaviors, and continuously generate training data through trial and error. The Tesla bots will also run millions of simulations in Tesla’s high-fidelity physics-accurate engine, allowing Optimus to close the “sim-to-real gap” by using these real-world observations to refine and validate the simulations! “You’re actually highlighting an important limitation and difference from cars. We’ll soon have 10 million cars on the road. It’s hard to duplicate that massive training flywheel. For the robot, what we’re going to need to do is build a lot of robots and put them in kind of an Optimus Academy so they can do self-play in reality. We’re actually building that out. We can have at least 10,000 Optimus robots, maybe 20-30,000, that are doing self-play and testing different tasks. Tesla has quite a good reality generator, a physics-accurate reality generator, that we made for the cars. We’ll do the same thing for the robots. We actually have done that for the robots. So you have a few tens of thousands of humanoid robots doing different tasks. You can do millions of simulated robots in the simulated world. You use the tens of thousands of robots in the real world to close the simulation to reality gap. Close the sim-to-real gap.”

Teslaconomics

42,563 просмотров • 8 месяцев назад

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1,204,483 просмотров • 5 месяцев назад

Train the AI behind real-world robots We’re hiring Data Labelers to annotate images and videos to train Optimus & autonomous systems. You’ll work with real production data & directly impact how these systems learn and operate in the real world Come join!

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Tesla Recruiting

667,732 просмотров • 5 месяцев назад

What is physical AI? MIT CSAIL explores how it's already helping robots understand the real world — & where it's heading next:

What is physical AI? MIT CSAIL explores how it's already helping robots understand the real world — & where it's heading next:

MIT CSAIL

19,918 просмотров • 1 месяц назад

#WATCH | Delhi: Chief Election Commissioner Gyanesh Kumar says, "The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019." "We have to understand the difference between a machine-readable voter list and a searchable voter list. You can search the voter list available on the Election Commission website by entering the EPIC number. You can also download it. This is not called machine-readable. Regarding machine-readable, in 2019, the Supreme Court also studied this subject in depth and found that giving a machine-readable electoral roll can violate the privacy of the voter... The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019..."

#WATCH | Delhi: Chief Election Commissioner Gyanesh Kumar says, "The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019." "We have to understand the difference between a machine-readable voter list and a searchable voter list. You can search the voter list available on the Election Commission website by entering the EPIC number. You can also download it. This is not called machine-readable. Regarding machine-readable, in 2019, the Supreme Court also studied this subject in depth and found that giving a machine-readable electoral roll can violate the privacy of the voter... The machine-readable voter list is prohibited. This decision of the Election Commission is after the judgment of the Supreme Court and is from 2019..."

ANI

281,884 просмотров • 1 год назад

Yesterday Odyssey launched a new AI model called Odyssey 3. From what I understand, the idea is that todays AI is great with text and images, but still pretty bad at real world experience. Robots and machines need to practice how things actually move, bump into each other, break or react and doing all of that only in the real world is slow and expensive. This kind of model tries to simulate those experiences so robots can train with way less real data. They even showed examples of driving and controlling robots after relatively few hours of practice. I filmed a normal street in Madrid today because that is the messy reality these systems still have to deal with. Making it work outside, with people, traffic and surprises, is hard. Not sure yet how big this is (well yeah im sure), but it feels like one of the missing pieces if we want AI that can actually act in the physical world, not just talk about it. LLM + WM = SuperIntelligence

Yesterday Odyssey launched a new AI model called Odyssey 3. From what I understand, the idea is that todays AI is great with text and images, but still pretty bad at real world experience. Robots and machines need to practice how things actually move, bump into each other, break or react and doing all of that only in the real world is slow and expensive. This kind of model tries to simulate those experiences so robots can train with way less real data. They even showed examples of driving and controlling robots after relatively few hours of practice. I filmed a normal street in Madrid today because that is the messy reality these systems still have to deal with. Making it work outside, with people, traffic and surprises, is hard. Not sure yet how big this is (well yeah im sure), but it feels like one of the missing pieces if we want AI that can actually act in the physical world, not just talk about it. LLM + WM = SuperIntelligence

Joaquin Tenes

10,268 просмотров • 22 дней назад