Nomagic deploys AI brain in warehouse robots, halves human intervention in live operations

Nomagic puts an AI brain into live warehouse robots

Nomagic, a Warsaw-based warehouse robotics firm, says it has put a vision-language-action model into live customer operations and roughly halved the rate at which its robots stall for human help. Its new AI lab, run by a former Google DeepMind researcher, is betting on mastery before the industry's favoured "general robot brain." Nomagic, a Warsaw-based warehouse robotics firm, put a vision-language-action model into live customer operations. It says the model roughly halved the rate at which its robots stall for human help. Its new AI lab, run by a former Google DeepMind researcher, is betting on mastery before generality. A Polish robotics company has quietly done the thing most robot labs are still demoing. Nomagic says it has deployed a vision-language-action (VLA) model into live warehouses with paying customers, Fortune reports. It says the move cut robot-caused human interventions by about half. The firm claims it is among the first to run VLAs in real production, not a staged demo. Nomagic keeps its European headquarters in Warsaw and a US base in Sandy Springs, Georgia. Earlier this year it started an AI research lab. It hired Markus Wulfmeier as chief scientist. He is a former Google DeepMind researcher and a core member of the Gemini Robotics team. A VLA is a single model that can see objects, read plain-language instructions, and then act. Many labs now chase it for embodied AI. The idea is that software should move things in the real world, not just answer questions on a screen. Mastery before generality Here Nomagic breaks from the pack. Most of the field races to build one general robot brain that drops into any machine. Nomagic runs the logic backwards. It aims for models that nail one task out of the box, then builds towards a general system. "Most of our community is racing to build the most general robot brain," Wulfmeier told Fortune. "We're betting that the harder part is actual mastery and that it has to be earned in real deployments first." His reasoning rests on the long tail. The physical world throws up endless rare situations. That is the same problem that slowed self-driving cars. Training in simulation or by remote control gets a model to roughly 80 per cent accuracy. In a warehouse, 80 per cent is useless. If a robot needs a human once an hour, the economics collapse. The harness Nomagic admits its VLA is not perfect. "Our VLAs aren't at 99.9% success on their own yet," the company said, adding that no rival's deployed VLAs are either. So it wraps the model in older "classical" software. That layer catches errors and enforces safety. "The bar in the physical world is high: 99.9% isn't a marketing number, it's the cost of being allowed in the building," said co-founder and chief executive Kacper Nowicki. "So we built a harness that clears it from day one, while the AI inside keeps getting better." The firm says its edge is data. Its deployed fleet already makes millions of successful picks each month. Two million come from the fashion platform Zalando alone. Nomagic trains its VLAs on that live stream, not on simulations. Why it matters The first VLA deployment runs at Brack.Alltron, Switzerland's second-largest e-commerce platform. Founder Roland Brack said the shift was real. "Today, we are seeing robots that truly understand their environment," he said. "This intelligence allows us to run autonomous shifts through nights and Sundays." The claims are Nomagic's own. VLAs still fall short of full reliability on their own. Yet the deploy-first stance marks a real contrast with labs chasing general-purpose humanoids. It also raises the stakes in the race to automate Europe's warehouses, a busy front in European robotics. As co-founder Tristan d'Orgeval put it: "We didn't build a lab and then go hunting for a problem. The order matters. It's what separates a demo from a business."

Nomagic AI lab led by former Google DeepMind researcher claims success with 'AI brain' for robots | Fortune

"Embodied AI" and "physical intelligence" are all the rage with Silicon Valley investors these days. The idea is that AI's next frontier will be systems that don't just use software but can take action in the real world through robotic devices, from self-driving cars to humanoid robots. Many startups are chasing AI models that can serve as general-purpose "robot brains," able to be dropped into any kind of robot and told to do almost anything. This is a shift from the kinds of systems that traditionally controlled industrial and warehouse robots. This control software often required weeks or months of on-site programming to perform even one task well. Still, most of these general purpose AI models perform significantly below human-level accuracy on each task, at least right out of the box. The hope is that with just a little bit of additional on-site, task-specific training, these robots will eventually be able to master that task -- reducing the barriers to deploying robots in many sectors. Nomagic, a company with European headquarters in Warsaw, Poland, and U.S. headquarters in Sandy Springs, Georgia, is pursuing a different approach: rather than going from generality to task-specific mastery, it is creating AI robot brains that are extremely accurate at specific tasks right out of the box, and then hoping to eventually build from mastery of these individual tasks towards a general purpose system. To pursue this goal, earlier this year Nomagic created an AI research lab led by Markus Wulfmeier, a former Google DeepMind robotics researcher, who now serves as Nomagic's chief scientist. Now Nomagic has announced that it has deployed its first vision-language-action (VLA) model -- a type of AI model that can perceive objects in the world, receive and understand text-based instructions from people, and then take actions in the world -- to paying customers. The company says it is among the first companies in the world to run VLAs in a live production environment, rather than in lab experiments or staged demos. The early results, according to the company, are tangible if unglamorous: by aiming the VLA at the most common "edge cases" for its warehouse robots -- somewhat uncommon situations where a robot gets stuck and has to call for human assistance -- Nomagic says it has roughly halved the rate of these robot-caused interventions in live operations.