1X and OpenAI Bet on Neo Gamma for Real-World Humanoid Robot Trials

Article Highlights
Off On

Norwegian startup 1X, supported by OpenAI, is set to initiate real-world home trials of their humanoid robot, Neo Gamma. Launched at Nvidia’s GTC event, the tests aim to collect critical data for refining the robot’s functionalities, marking a significant step towards commonplace household humanoid assistants.

1X’s CEO Bernt Børnich announced plans to place several hundred to a few thousand Neo Gamma units in homes by the end of the year. Early adopters will host the robots to gather data on how Neo Gamma interacts with people in real-world settings, rather than in controlled lab environments. Although Neo Gamma can perform basic tasks like walking and balancing through AI, it still needs human teleoperators for complex movements. This teleoperation helps gather essential data to enhance its future autonomous capabilities.

The trials will be vital for 1X’s internal AI model development, despite their collaborations with OpenAI and Nvidia. To address privacy concerns, 1X ensures users can control human operator access to the robot’s visual and auditory data. The growing interest in domestic humanoid robots is apparent, with competitors like Figure AI planning similar trials. There are also rumors that OpenAI is developing its own humanoid systems, highlighting the transformative potential of these robots for household chores, despite significant challenges.

Deploying robots in homes poses challenges similar to those faced by autonomous vehicle developers. Børnich acknowledges that Neo Gamma is not yet commercially viable or fully autonomous, but the data from these trials is critical for overcoming current limitations. This initiative by 1X to introduce Neo Gamma into homes marks a significant moment in domestic robotics. Combining AI with human oversight, the company aims to gather essential real-world data, paving the way for humanoid robots to become an integral part of daily life.

Explore more

Community Project Successfully Runs macOS on iPad

The distinction between tablet and laptop hardware has practically vanished as Apple continues to ship its most powerful silicon inside the sleek chassis of the iPad Pro. While the hardware remains exceptional, users have long felt restricted by the inherent limitations of iPadOS, which often treats sophisticated multitasking as an afterthought rather than a core feature. A dedicated community of

Is Windows 11 Finally Prioritizing Speed Over AI?

The digital landscape has undergone a dramatic transformation where the initial fascination with integrated artificial intelligence is finally yielding to the undeniable demand for raw system performance. For a considerable period, users found themselves navigating an operating system that seemed more preoccupied with processing generative tasks than executing basic commands with the necessary fluidity. This “AI-first” ideology frequently resulted in

Can ZSvirt Disrupt the Proprietary Virtualization Market?

The landscape of enterprise data centers is undergoing a seismic shift as the traditional reliance on expensive proprietary virtualization suites gives way to a demand for greater transparency and cost-effectiveness. When ZStack announced the transition of its enterprise-grade platform, ZSvirt, to a fully open-source model under the GPL 3.0 license on August 12, 2026, it signaled a potential end to

Mastering Prompt Engineering Optimizes CRM Performance

Recent industry analysis indicates that organizations effectively utilizing generative artificial intelligence within their customer management systems have achieved a forty percent reduction in response times compared to those relying on traditional manual workflows. While the integration of Artificial Intelligence into major platforms like Salesforce, HubSpot, and Zoho has fundamentally altered how businesses manage sales and service cycles, the actual value

What Can RPA Teach Us About Generative AI Success?

The rapid proliferation of generative artificial intelligence and autonomous agents across global enterprises has created a complex landscape where the sheer speed of technological deployment often outpaces the actual realization of tangible business value. While the current fascination with large language models and multi-agent systems suggests a clean break from the past, the reality is that many organizations are stumbling