Team Lead Physical AI Data Operations

A Powerhouse for Physical AI: NEURA Robotics and TUM Open RoboGym in Munich. A joint research and training center brings together robots, science and industrial expertise. To mark the opening, NEURA unveils its new humanoid robot, 4NE1 Gen 4. Munich, 22 October 2026 - NEURA Robotics and the Technical University of Munich (TUM) today opened the TUM RoboGym powered by NEURA at LabCampus near Munich Airport. Spanning more than 2,300 square meters, the new center brings together research, robot training and industrial application. It was built in partnership with TUM's Munich Institute of Robotics and Machine Intelligence (MIRMI). To mark the opening, NEURA is also launching 4NE1 Gen 4 ("For Anyone"), the new generation of its humanoid robot. More headlines. Articles. The RoboGym brings together AI research and industrial application. Companies contribute concrete tasks and their process knowledge. Researchers and development teams investigate how robots can learn these tasks faster and perform them more reliably. "Our companies hold knowledge that has been built up over generations," said David Reger, Founder and CEO of NEURA Robotics. "People know how to work materials, assemble components and master difficult processes. This knowledge is one of our greatest strengths in the age of Physical AI. With TUM, we are building a powerhouse for physical capabilities, where this knowledge becomes the foundation for new possibilities. The Mittelstand, in particular, should be able to help shape this future. With the launch of the humanoid 4NE1 Gen 4, we are showing today which robots are ready for it: designed for series production, built for productive work and powered by Neuron AI, our own foundation model that learns from experience in the NEURA Gyms. Developed, built and trained in Germany, for the world." A place where companies teach robots their work Partners have been training concrete workflows at the TUM RoboGym since September. Companies from more than ten industries are involved, including automotive, pharmaceuticals, medical technology, packaging, logistics, agriculture and care. Demand is high: capacity in Munich is already in strong demand. Tasks range from handling cardboard boxes and filling bottles to loading and unloading wooden components. Companies can test applications, identify training needs and assess the suitability of different robot systems before expanding use in their own operations. "The TUM RoboGym robotics center is unique in Germany and Europe," said Prof. Thomas Hofmann, President of the Technical University of Munich. "By collaborating with a robot manufacturer based in Germany, we are also sending a clear signal for Germany as an industrial location in geopolitically uncertain times." Three paths to physical experience How does a robot grasp a delicate component? How does it recognize that two parts have been correctly joined? And how does it respond when a workflow changes? Capabilities like these are built through experience with the physical world. Physical AI requires data on how objects, materials and forces behave in the real world. The RoboGym combines three approaches to generate this data: - Real-world robot data: Different robot systems perform tasks. Their sensors capture movements, contacts and the outcomes of their actions. - Human demonstrations: People demonstrate workflows. Sensor-equipped data suits, motion-capture systems and teleoperation help translate movements and interactions into usable training data. - Simulation and Data Amplifier: Virtual training environments expand real-world experience with additional variations and situations, allowing skills to be trained under changed conditions and then validated on real robots. The Neuraverse connects this training infrastructure with NEURA's software and AI tools. For the joint research conducted by TUM and NEURA, training data is structured and processed for use in developing and studying Physical AI models. At the center of it all is a practical question: how quickly can a robot learn a new task, and how reliably can it be performed? 4NE1 Gen 4: new hardware for robots that can learn With 4NE1 Gen 4, NEURA is launching the new generation of its humanoid robot, already in operation at the TUM RoboGym for the opening: slimmer, lighter and powered by Neuron AI as its brain. - New design, lighter body: 4NE1 Gen 4 has a slimmer body, a textile and sensorized outer skin and is 20 percent lighter than the previous generation. The fabric makes the robot appear more approachable: it is built to work alongside people, and designed to look the part. The material also offers potential for further, simple customization. - More precise handling: Advanced hands enable even more accurate grips. Added to this are Smart Limbs: reflexes are built directly into the limbs, so each limb can respond independently. This allows 4NE1 Gen 4 to react instantly to its environment and move more fluidly and in a more human-like way. - Neuron AI, the brain: 4NE1 Gen 4 runs on Neuron AI, NEURA's Perception-Language-Action model for Physical AI. It translates what the robot perceives directly into movement. Alongside vision, touch, force, sound and the robot's own state also feed into the model. This makes a real difference for industrial tasks in particular, for example when a robot needs to recognize whether a fastener has clicked into place. Neuron AI is trained on real-world robot data from the NEURA Gyms, human demonstrations and simulation. Through the Neuraverse, skills learned by one robot become available to other connected robots as well. As a result, 4NE1 Gen 4 benefits from everything learned across the growing network of NEURA Gyms. 4NE1 Gen 4 is being prepared for series production. Alongside the opening of the TUM RoboGym in Munich, it is also appearing at the NVIDIA GTC conference in Berlin and is already in operation at the NEURA Gyms. At these training facilities, companies can train tasks with the new robot generation, making them among the first to work with 4NE1 Gen 4. Research and industry develop together The TUM RoboGym gives researchers, students and companies access to a shared research and training infrastructure. Scientific findings can be tested here under practical conditions, while industrial tasks in turn generate new research questions. NEURA contributes robotics, technical infrastructure, computing power and operating staff, among other things. TUM provides space, scientific expertise and resources for research and operations. The joint initiative is initially set up for three years. In total, the partners are investing around EUR 17 million, of which NEURA is contributing approximately EUR 11 million. "TUM MIRMI and NEURA Robotics have found two partners that can achieve great things together," said Prof. Lorenzo Masia, Executive Director of TUM MIRMI and Head of the TUM RoboGym. "Building on our world-leading scientific expertise, we are now able, together with a strong industry partner, to prepare concrete applications for the market and make industrial robotics an important factor in the German economy." An international network begins in Munich The TUM RoboGym marks the start of an international network of NEURA Gyms. Further locations are being established in Europe, the United States and China. In Germany, another Gym is being built in cooperation with RWTH Aachen. "We want companies to carry their experience into the next industrial era," said David Reger. "To develop capabilities, protect their know-how and decide for themselves, in the future, where and under what conditions they make it available to others. What we are opening today in Munich is meant to have an impact far beyond this location. From Europe, together for the world." More information: https://neura-robotics.com/neuragym/

Germany's NEURA Robotics is partnering with Austria's NXAI to build a memory layer for cognitive robots. The companies will combine NEURA's Physical AI stack with xLSTM, NXAI's recurrent architecture that can maintain and update state over long sequences. NXAI plans to offer its xLSTM-based model on NEURA's Neuraverse platform, alongside NEURA's own foundation model, Neuron AI. Companies will be able to tailor the NXAI model using the Neuraverse toolchain, test it in the NEURA Gyms, and deploy it on suitable robots. Neuron AI will continue to be developed independently, and the partnership includes joint research. "A robot that truly helps in everyday life and in industry must be able to remember," said David Reger, NEURA's founder and chief executive officer. NEURA raised a €120 million Series B in January 2025 and announced a Series C of up to €1.2 billion in June 2026.

NEURA Robotics, NXAI team up to give cognitive robots lasting memory - unite.ai. Reading Time: 3 mins read NEURA Robotics and NXAI announced a partnership on October 20, 2026 to jointly develop a memory component for cognitive robots, integrating NEURA's Physical AI stack with NXAI's xLSTM architecture and adding a second model option to the Neuraverse platform. You may also like. A two-part partnership. The partnership, datelined Metzingen, Germany, consists of two parts, according to the announcement. The joint work builds on Neuron AI, NEURA's multimodal foundation model for Physical AI, which combines 3D vision, touch, audio, robot state and language with a memory function. The partners are integrating NEURA's Physical AI stack with xLSTM, which the announcement describes as a recurrent architecture from NXAI that can hold and update state efficiently across long sequences. NXAI also plans to make its own xLSTM-based model available on the Neuraverse platform, where it would sit alongside Neuron AI; the announcement presents this as a plan rather than a completed availability. "A robot that genuinely helps in everyday life and industry must be able to remember," David Reger, founder and CEO of NEURA Robotics, said in the announcement. Reger described Neuron AI as the foundation, the Neuraverse as the platform through which outside AI approaches can find their way into robots, and NXAI as the partner for building out that memory. Prof. Dr. Sepp Hochreiter, founder of NXAI, said memory and experience are what allow robots to solve tasks reliably across many steps, and that NXAI and NEURA together are bringing that strength into Physical AI. Working and episodic memory. The announcement contrasts robots with chatbots to explain why memory matters for physical machines. A chatbot processes requests one at a time, while a robot operates in a continuous loop of perceiving, deciding and acting many times per second, potentially for an entire shift. The release distinguishes two levels of memory: working memory handles the immediate state of a task, such as whether a component has already been inserted, whether a door is open or closed, or whether a start button has been pressed. Episodic memory goes further, allowing a robot that has performed a process repeatedly to draw on prior experience when it encounters the same situation again. Neuraverse integration and data control. Under the planned integration, companies would be able to fine-tune the NXAI model for their own tasks using the Neuraverse toolchain, test it in the NEURA Gyms and deploy it on suitable robots, all within the same training and application environment they already use, according to the announcement. Neuron AI remains NEURA's own multimodal foundation model and will continue to be developed independently; the partnership adds a second model option to the platform and includes joint research. Companies retain control over their process knowledge and decide for themselves whether to share data and skills. What each partner contributes. NEURA contributes its Physical AI stack: proprietary multimodal foundation models, robotics, sensor technology, real-world training data from the NEURA Gyms and the platform for industrial deployment. NXAI brings what the announcement describes as decades of AI research and a fundamentally different approach to recurrent intelligence and memory. NXAI is an Austrian deep-tech company based in Linz, and its core research focuses on xLSTM models for time series and robotics. On its own site, the company describes itself as a frontier lab and says its proprietary xLSTM memory architectures enable state-tracking and outperform the currently dominant Transformer architectures. Hochreiter is NXAI's co-founder and Chief Scientist, and the company says it works closely with JKU Linz and other research institutions. NXAI also says it is building specialized world models based on time-series analysis under the name TiRex, and that it will develop large-scale world models built on neural memory hierarchies and memory routing, with applications in robotics. NEURA Robotics was founded in 2019 and is headquartered in Metzingen. The company develops cognitive robots that can see, hear, feel and learn, along with the software, AI and data infrastructure required to deploy them at scale, and it describes the Neuraverse as an open ecosystem in which robots continuously learn and share skills. Neuron AI, according to NEURA's product documentation, is a Perception-Language-Action model that encodes 3D vision, tactile and force-torque data, audio, robot state and language in one shared space over time and turns them into a single action stream. The model runs locally on the robot without a cloud connection and was developed and trained in-house in Metzingen. Training draws on three sources: real-world robot data, simulation-amplified data and human demonstration data, complemented by data partnerships with industrial companies including Schaeffler and Bosch. NEURA says Neuron AI runs on five robot embodiments: the 4NE-1 Gen 3 and Gen 4, a wheeled 4NE-1, and two further bimanual platforms. The partners' stated longer-term ambition is for robots to build on experience over time rather than only execute individual skills. The announcement ties that goal to the vision behind Neuraverse and what NEURA calls the Robot Skill Economy, in which skills acquired through real-world interaction are refined and carried across machines and environments.