Generative Bionics to launch Physical AI Data Factory in Italy
AMD Corp. — the first Data Factory hub is set to become one of Europe’s largest physical AI training facilities for humanoid robots. | The company said the new 5,000-sq.-m (53,819.5-sq.-ft.) hub will help move humanoid robotics from laboratory demonstrations to reliable industrial deployment.
In addition, Generative Bionics said it hopes to advance European humanoid sovereignty, ensuring that the data, models, and know-how behind Europe’s industrial humanoids are generated, trained and validated on the continent. “The value that Europe has right now is within its industry, and we have to extract physical AI data in order to train our own models,” Daniele Pucci, the CEO of Generative Bionics, told The Robot Report. “This is a competitive advantage that Europe right now has, because of the automation that we have been putting in place over the last 40 years.” Generative Bionics said the new facility will be operational by the fourth quarter of 2027. The Genoa, Italy-based company plans to eventually open a second facility elsewhere in Europe and a third serving global markets. Together, the three facilities will reproduce real industrial environments, generate high-fidelity physical data, and connect that data with large-scale simulation. Building on their strategic technology collaboration, Advanced Micro Devices Inc. will be Generative Bionics’ AI infrastructure partner, and the Physical AI Data Factory network will be powered by AMD Helios. Its rack-scale architecture will provide the compute foundation to process physical and synthetic data, train physical AI models, and run thousands of digital-twin scenario variations in parallel. Data Factory to test GENE.01 in a range of industries The Physical AI Data Factory will connect real-world robot operations, simulation and AI development in a continuous real-to-sim-to-real cycle, said Generative Bionics. The company said this will allow it to configure and validate its GENE.01 humanoid robot for specific industrial environments before customer deployment, then feed data from deployed fleets into future training cycles. Industrial humanoids must learn from the conditions they will encounter at work, noted the Generative Bionics. This requires data that captures contact, force, motion, proximity, temperature, task constraints, and human interaction in realistic operating settings. For GENE.01, the dataset will include vision and motion data as well as signals captured through its full-body multimodal skin. “A robot is not only vision and is not only language,” said Pucci. “It is position, velocity, acceleration, temperature, and contact forces, so there is a large variety of data that you have to take into account.” The Data Factory will reproduce environments selected with industrial partners and allow fleets of GENE.01 robots to perform tasks continuously in real-world conditions.
