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1X has unveiled NEO Gamma, a major leap toward bringing humanoid robots into daily life ⦿ Walks more naturally, can squat to pick up objects ⦿ 10x better hardware reliability, 10 dB quieter ⦿ Improved object manipulation + a custom-built LLM for natural language interaction

The Humanoid Hub

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282,936 views • 1 year ago •via X (Twitter)

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The Humanoid Hub1 year ago

NEO Gamma has four beamforming microphones with echo cancellation for clear audio. And a three-speaker system: one in the chest for AI voice and two in the pelvis for bass, providing 360-degree sound effects.

The Humanoid Hub1 year ago

1X trained a visual manipulation model capable of picking up a large variety of objects in different scenarios, including environments not seen during training. NEO Gamma leverages neural networks trained to predict teleoperated actions directly from raw sensor data.

The Humanoid Hub1 year ago

The emotive earrings provide real-time visual feedback. NEO’s knit suit and shoes are 3D-printed from soft nylon using a Japanese Shima Seiki machine. The suit utilizes a whole-garment knitting process that allows the fabric to conform to NEO without affecting performance.

The Humanoid Hub1 year ago

1X's Blog Post:

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DabidarZ1 year ago

dawg did the robot just take a seat 😭😭

R2S1 year ago

This is way less creepy than the Westwood reject one another company showed hanging in midair yesterday.

T Shirt n Jeans1 year ago

Every home needs one of these. $NVDA First time I've thought a humanoid moved like one of us. @The_AI_Investor @benitoz

SGK 🔥 🚩1 year ago

When they can shop, cook, clean then it’s game over….

Antonio Zennaro1 year ago

Impressive! The future is closer than we think.

November 🍂1 year ago

This is the only one I have seen that can give @Tesla_Optimus any competition. In 2026 they gonna be like smart phones. So I guess the only question is…you going iphone or android? 👀

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118,467 views • 1 year ago

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60,689 views • 8 months ago

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19,518 views • 4 months ago

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Grant Lee

2,355,225 views • 1 year ago

📢 Announcing one of the most exciting works from us this year on **scalable robot policy evaluation through real-to-sim transfer**, moving toward a scalable evaluation engine with structured world models that capture the appearance, geometry, and dynamics of environments involving deformable objects. 🤖 Evaluation remains one of the biggest bottlenecks in building general-purpose robots. Today, robots are still evaluated only in the real world, which is **orders of magnitude slower** than the development of language agents. We propose a new framework where simulation performance **strongly correlates** with the real world (r > 0.9), even for deformable objects. The key difference from existing work lies in the correlation between simulation and reality: if a robot model performs better in the digital world, does it also perform better in the real world? This question has long made people hesitant about simulation-based evaluation — especially for deformable objects. We are changing that. Our pipeline achieves effective real-to-sim transfer, establishing **state-of-the-art correlation** between simulation and reality for deformable object manipulation. It provides a **scalable and reproducible evaluation engine** for robot learning. 🌐

📢 Announcing one of the most exciting works from us this year on scalable robot policy evaluation through real-to-sim transfer, moving toward a scalable evaluation engine with structured world models that capture the appearance, geometry, and dynamics of environments involving deformable objects. 🤖 Evaluation remains one of the biggest bottlenecks in building general-purpose robots. Today, robots are still evaluated only in the real world, which is orders of magnitude slower than the development of language agents. We propose a new framework where simulation performance strongly correlates with the real world (r > 0.9), even for deformable objects. The key difference from existing work lies in the correlation between simulation and reality: if a robot model performs better in the digital world, does it also perform better in the real world? This question has long made people hesitant about simulation-based evaluation — especially for deformable objects. We are changing that. Our pipeline achieves effective real-to-sim transfer, establishing state-of-the-art correlation between simulation and reality for deformable object manipulation. It provides a scalable and reproducible evaluation engine for robot learning. 🌐

Yunzhu Li

39,960 views • 10 months ago

Remember the humanoid robot used for hotel cleaning? Customers are already using it. Zerith Robotics, a startup from Hefei, has deployed multiple Zerith H1 robots in shopping malls, office buildings, and supermarkets in cities like Hefei Airport, Hefei Gas Building, and Shenzhen MixC, acting as cleaners and sales assistants. The Zerith H1 can autonomously perform cleaning tasks such as cleaning toilets, mopping floors, and wiping sinks. In supermarkets, it carries a shopping basket, autonomously picks up snacks, and automatically processes orders. From experimentation to trial use and real-world deployment, Zerith has built it into a commercial humanoid robot service solution, already used in over 20 landmark locations, and plans to expand to more cities like Hangzhou and Shanghai. From a commercial service reliability perspective, wheeled humanoid robots are being prioritized by customers. It is worth mentioning that Zerith was officially established in January of this year by a young team from the Tsinghua AI Robotics Laboratory. Last year, they successively launched Zerith Z1 (bipedal) and Zerith H1 (wheeled).

Remember the humanoid robot used for hotel cleaning? Customers are already using it. Zerith Robotics, a startup from Hefei, has deployed multiple Zerith H1 robots in shopping malls, office buildings, and supermarkets in cities like Hefei Airport, Hefei Gas Building, and Shenzhen MixC, acting as cleaners and sales assistants. The Zerith H1 can autonomously perform cleaning tasks such as cleaning toilets, mopping floors, and wiping sinks. In supermarkets, it carries a shopping basket, autonomously picks up snacks, and automatically processes orders. From experimentation to trial use and real-world deployment, Zerith has built it into a commercial humanoid robot service solution, already used in over 20 landmark locations, and plans to expand to more cities like Hangzhou and Shanghai. From a commercial service reliability perspective, wheeled humanoid robots are being prioritized by customers. It is worth mentioning that Zerith was officially established in January of this year by a young team from the Tsinghua AI Robotics Laboratory. Last year, they successively launched Zerith Z1 (bipedal) and Zerith H1 (wheeled).

CyberRobo

438,035 views • 9 months ago