San Francisco, CA – In a scene straight out of a science fiction film, a humanoid robot named NEO Gamma, developed by 1X Technologies, recently presented NVIDIA CEO Jensen Huang with a custom-made leather jacket at 1X’s headquarters. This seemingly simple gesture signifies a deepening partnership between the two companies, aimed at accelerating the development and deployment of advanced humanoid robots.
The collaboration, officially announced at NVIDIA’s GPU Technology Conference (GTC 2025) on March 18th, promises to push the boundaries of robotics by leveraging NVIDIA’s powerful GPU technology and 1X’s expertise in developing safe, flexible, and visually intelligent humanoid robots.
The presented jacket, designed by California-based ERL, is more than just a stylish garment. It features a studded NVIDIA logo on the chest and a large embroidered version on the back, cleverly merging Huang’s signature style with cutting-edge technology.
The partnership goes beyond symbolic gestures. 1X Technologies is providing NVIDIA with access to its unique tool – a dataset Application Programming Interface (API). This API allows NVIDIA to tap into real-world data collected from 1X’s office and home environments. This data is crucial for training and refining the AI models that power humanoid robots like NEO Gamma.
Furthermore, 1X is offering an inference Software Development Kit (SDK) that enables NVIDIA to utilize its powerful GPUs to run model predictions continuously at a rate of five times per second (5Hz). These GPUs can be integrated directly into the robot’s head or connected externally, providing the necessary processing power for complex tasks.
Developing humanoid robots like NEO Gamma presents significant challenges in terms of safety, dexterity, and visual understanding. This collaboration is seen as a crucial step in overcoming these hurdles. 1X’s dataset API is designed to support NVIDIA in acquiring the valuable real-world data needed to train robust and reliable AI models.
Verifying the correctness of new learning codebases is a critical step, explains 1X. This includes overfitting baseline models to small datasets and ensuring time synchronization between data collection, training, and runtime inference.
In collaboration with NVIDIA’s GEAR (General Embodied Agent Research) team, 1X is leveraging NVIDIA’s GR00T N1 foundation model to train NEO robots. A joint test conducted in the home of a 1X employee saw NEO successfully grasping a cup, transferring it between its hands, and placing it in the dishwasher – a testament to the compatibility and practicality of the combined technologies. During this process, the teams exchanged insights on action spaces, control frequencies, and imitation learning techniques.
This successful demonstration hints at a future where advanced humanoid robots like NEO Gamma can assist with everyday tasks, such as washing dishes, freeing up humans to relax and focus on other activities.
1X’s latest NEO Gamma robot is designed with a focus on enhancing safety and user-friendliness. The robot features soft outer shell coverings to minimize impact and ensure safer interactions with its surroundings. It also incorporates an advanced visual manipulation model that uses neural networks to directly predict actions from raw sensor data, enabling it to pick up objects in unfamiliar environments.
The collaboration between NVIDIA and 1X Technologies represents a significant leap forward in the field of robotics. By combining NVIDIA’s powerful AI platform with 1X’s innovative humanoid robot design, the two companies are paving the way for a future where robots can seamlessly integrate into our lives and assist us with a wide range of tasks. The leather jacket presentation, while a seemingly small event, symbolizes a much larger vision: a future where humans and robots work together to create a more efficient and fulfilling world.
References:
- IT之家. (2024, March 27). 人形机器人给黄仁勋递上皮衣，1X、英伟达联手搞事情 [Humanoid Robot Presents Leather Jacket to Jensen Huang, 1X and NVIDIA Join Forces]. Retrieved from [Insert Original Article Link Here] (Please replace with the actual URL)
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