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In their latest video, Boston Dynamics’s AI team explains how they make the Atlas humanoid perceive and interact with the world. Atlas uses an agile perception system to understand both the shape and context of objects in complex environments. Atlas combines 2D and 3D awareness, keypoint-based localization, and an... show more

The Humanoid Hub

112,714 subscribers

50,083 просмотров • 1 год назад •via X (Twitter)

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Комментарии: 11

Фото профиля Evin Kamski

Evin Kamski1 год назад

They need to release it doing more tasks, right now moving small packages into other slots is all I have seen, but Atlas’ design is way too heavyweight and will be far too expensive for it to be seen as practical with limited application.

Фото профиля Coral AI News

Coral AI News2 лет назад

Coral AI is the most powerful AI for documents. See the difference yourself:

Фото профиля Corny

Corny1 год назад

Why none of these people on twitter 😭

Фото профиля The Humanoid Hub

The Humanoid Hub1 год назад

coz they have laid low. 🙃 They're here, would love to see them posting more often. @estormyweather @Suddhus @BizaOndrej @czarnowskij

Фото профиля Reborn

Reborn1 год назад

That is incredible.

Фото профиля LoneWordz

LoneWordz1 год назад

Failed enterprise. They're not using neural nets.

Фото профиля Cam Byers

Cam Byers1 год назад

Atlas has the best humanoid hardware design by far.

Фото профиля CIX 🦾

CIX 🦾1 год назад

Their head choice is very sci fi

Фото профиля Taj English

Taj English1 год назад

AhhMazInggg

Фото профиля bimi

bimi1 год назад

Is atlas allowed to work something else? 🤔

Фото профиля Deep Saha

Deep Saha1 год назад

Ever wondered how a humanoid perceives the world? 🤖 The Humanoid Hub dives into Boston Dynamics's AI team's innovative approach with Atlas! Combining 2D and 3D for agile perception. #RobotRevolution #TechInnovation

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Owen Gregorian

179,005 просмотров • 9 месяцев назад

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 interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.

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 interface, it allows AI agents to learn physical and social reasoning in complex virtual worlds before real world deployment. We're moving from AI that only understands information to AI that can perceive, reason and act inside realistic simulated environments.

SciTech Era

47,510 просмотров • 2 месяцев назад

Dr. Fei-Fei Li just called out the biggest blind spot in the entire AI industry. We have been building half of human intelligence. And calling it the finish line. Li: “If you look at human intelligence, it pretty much boils down to two buckets.” The first bucket is language. Symbolic reasoning. Communication. The ability to think in words and abstractions. That’s what every major AI lab has spent the last decade building. The second bucket is the one the industry has almost entirely ignored. Li: “We call that in AI spatial intelligence.” How humans and animals perceive, navigate, and interact with the three-dimensional physical world. How we reach for objects. How we move through space. How we build and manipulate physical reality. From painting masterpieces to constructing the pyramids, non-verbal spatial intelligence is what actually shapes the world. Language describes reality. Spatial intelligence acts on it. And the gap between those two things is the gap between a chatbot and a robot. Li: “When this technology is ready, the robotic revolution is gonna start. We’re already seeing that trend.” Every robot is a moving agent. Every moving agent requires spatial intelligence to function in the real world. The humanoid robots being deployed in factories right now are hitting the ceiling of what language models alone can power. Spatial intelligence is the unlock. But Li didn’t stop at robotics. Li: “From a geopolitics point of view, this is part of the technology that goes straight into weapons.” Autonomous drone swarms. Battlefield navigation. Physical target acquisition without human oversight. Every military application of AI that operates in the real world runs on spatial intelligence. The nation that masters the transition from static text to dynamic three-dimensional perception doesn’t just win the software race. It commands the physical battlefield. The AI arms race just broke out of the data center. It’s operating in three dimensions now.

Dr. Fei-Fei Li just called out the biggest blind spot in the entire AI industry. We have been building half of human intelligence. And calling it the finish line. Li: “If you look at human intelligence, it pretty much boils down to two buckets.” The first bucket is language. Symbolic reasoning. Communication. The ability to think in words and abstractions. That’s what every major AI lab has spent the last decade building. The second bucket is the one the industry has almost entirely ignored. Li: “We call that in AI spatial intelligence.” How humans and animals perceive, navigate, and interact with the three-dimensional physical world. How we reach for objects. How we move through space. How we build and manipulate physical reality. From painting masterpieces to constructing the pyramids, non-verbal spatial intelligence is what actually shapes the world. Language describes reality. Spatial intelligence acts on it. And the gap between those two things is the gap between a chatbot and a robot. Li: “When this technology is ready, the robotic revolution is gonna start. We’re already seeing that trend.” Every robot is a moving agent. Every moving agent requires spatial intelligence to function in the real world. The humanoid robots being deployed in factories right now are hitting the ceiling of what language models alone can power. Spatial intelligence is the unlock. But Li didn’t stop at robotics. Li: “From a geopolitics point of view, this is part of the technology that goes straight into weapons.” Autonomous drone swarms. Battlefield navigation. Physical target acquisition without human oversight. Every military application of AI that operates in the real world runs on spatial intelligence. The nation that masters the transition from static text to dynamic three-dimensional perception doesn’t just win the software race. It commands the physical battlefield. The AI arms race just broke out of the data center. It’s operating in three dimensions now.

Dustin

122,680 просмотров • 5 месяцев назад

Robots are gaining spatial awareness with Over the Reality. 🤖 Powered by the world’s largest 3D dataset, we enable robots to see, sense, and collaborate in real-world environments. This early test shows how a Unitree Go2 perceives its surroundings through OVER’s VPS — on the right, the real life robot; on the left, its real-time perception of the position inside one of OVER’s 3D maps. Robotic spatial awareness is here, living in 155,000+ mapped locations and expanding every day. One step closer to Physical AI. Stay tuned for our upcoming ROS 2 integration, unlocking a universal framework for robotic perception leveraging OVER's infrastructure!

Robots are gaining spatial awareness with Over the Reality. 🤖 Powered by the world’s largest 3D dataset, we enable robots to see, sense, and collaborate in real-world environments. This early test shows how a Unitree Go2 perceives its surroundings through OVER’s VPS — on the right, the real life robot; on the left, its real-time perception of the position inside one of OVER’s 3D maps. Robotic spatial awareness is here, living in 155,000+ mapped locations and expanding every day. One step closer to Physical AI. Stay tuned for our upcoming ROS 2 integration, unlocking a universal framework for robotic perception leveraging OVER's infrastructure!

Over the Reality 🌐

263,818 просмотров • 9 месяцев назад

#WATCH | Delhi: At the Synergia Conclave, Lieutenant General Vipul Shinghal, AVSM, SM, Deputy Chief of Integrated Defence Staff (Doctrine, Organisation, and Training), says, "...Even when I operate an AI system, I understand how to use it, but I don’t know what manipulation of data is happening... Where we have control and where we are also focusing is that our commanders, who earlier were only dealing with troops and making decisions based on that, are now dealing with algorithms and systems... they must have the ability to question machine outputs... These aspects are being debated worldwide... India itself has recently lost any regulation after the AI summit, and we are part of these discussions. The consensus is hard, but it is building..." He adds, "Meaningful human control is another aspect that is taking shape. Meaningful human control means that commanders must be able to access control meaningfully, and for that, they require 4 inputs or rather 4 levers: sufficient situational awareness... adequate time and information... And the ability to override or intervene... if they understand its limitations, we will be able to, at least in systems of the armed forces and weapons systems, ensure that we use AI for user responsibility. The moral responsibility must remain with the commander, and our conscience must keep that in place... In the Indian context, we have always believed that Shakti must go hand in hand with Dharma, that this force must go hand in hand with righteousness..." (11.03)

#WATCH | Delhi: At the Synergia Conclave, Lieutenant General Vipul Shinghal, AVSM, SM, Deputy Chief of Integrated Defence Staff (Doctrine, Organisation, and Training), says, "...Even when I operate an AI system, I understand how to use it, but I don’t know what manipulation of data is happening... Where we have control and where we are also focusing is that our commanders, who earlier were only dealing with troops and making decisions based on that, are now dealing with algorithms and systems... they must have the ability to question machine outputs... These aspects are being debated worldwide... India itself has recently lost any regulation after the AI summit, and we are part of these discussions. The consensus is hard, but it is building..." He adds, "Meaningful human control is another aspect that is taking shape. Meaningful human control means that commanders must be able to access control meaningfully, and for that, they require 4 inputs or rather 4 levers: sufficient situational awareness... adequate time and information... And the ability to override or intervene... if they understand its limitations, we will be able to, at least in systems of the armed forces and weapons systems, ensure that we use AI for user responsibility. The moral responsibility must remain with the commander, and our conscience must keep that in place... In the Indian context, we have always believed that Shakti must go hand in hand with Dharma, that this force must go hand in hand with righteousness..." (11.03)

ANI

104,382 просмотров • 4 месяцев назад

Excited to share ESI-BENCH, a benchmark for Embodied Spatial Intelligence! Most spatial reasoning benchmarks assume an oracle observer: the agent is given the right image, view, or 3D scene. But in the real world, the observer is also an actor. To understand space, agents must decide where to look, how to move, and when to interact, to reveal what is hidden: occlusions, containment, contact, dynamics, and functionality. In many cases, the hard part is not perception itself, but choosing the right action to make informative perception possible. ESI-BENCH tests this perception-action loop. Agents receive an egocentric observation and a spatial question, then must actively gather evidence through perception, locomotion, and manipulationbefore answering. The benchmark spans 10 task categories, 29 subcategories, and 3,081 instances, built in BEHAVIOR-1K across realistic interactive scenes. 🌍Webpage: 💻Code & data: Thanks for collaborators: Jiageng, Han, Manling Li , Leonidas Guibas, Fei-Fei Li , Jiajun Wu , Yejin Choi

Excited to share ESI-BENCH, a benchmark for Embodied Spatial Intelligence! Most spatial reasoning benchmarks assume an oracle observer: the agent is given the right image, view, or 3D scene. But in the real world, the observer is also an actor. To understand space, agents must decide where to look, how to move, and when to interact, to reveal what is hidden: occlusions, containment, contact, dynamics, and functionality. In many cases, the hard part is not perception itself, but choosing the right action to make informative perception possible. ESI-BENCH tests this perception-action loop. Agents receive an egocentric observation and a spatial question, then must actively gather evidence through perception, locomotion, and manipulationbefore answering. The benchmark spans 10 task categories, 29 subcategories, and 3,081 instances, built in BEHAVIOR-1K across realistic interactive scenes. 🌍Webpage: 💻Code & data: Thanks for collaborators: Jiageng, Han, Manling Li , Leonidas Guibas, Fei-Fei Li , Jiajun Wu , Yejin Choi

Yining Hong

51,990 просмотров • 2 месяцев назад