NEURA Robotics Introduces Neuron AI: The Brain of the Physical World

Neura Robotics, expanding the skill set of robots with cognitive capabilities so that they can work with humans in existing environments without having to invest in complex and costly safety systems, led by David Reger and the team, has introduced Neuron AI, its multimodal foundation model for Physical AI.

Neuron AI combines 3D vision, touch, audio, robot state, language, and memory to help robots perceive and act beyond visual information alone. Its Perception-Language-Action (PLA) architecture connects multisensory inputs with past actions, enabling robots to retain context and translate perception into physical action.

“An intelligent robot needs a brain that brings its senses together and remembers what happened,” said David Reger, Founder and CEO of NEURA Robotics. “With Neuron AI, we are building the brain of the physical world: Physical AI that turns human expertise and physical experience into capabilities robots can learn and apply. Developed in Germany, built for the world.”

Neuron AI integrates 3D vision, touch, force, audio, robot state, and language into a unified system, enabling robots to perform tasks that require more than visual input. Multisensory perception supports actions such as verifying a lock through sound and touch, handling unseen objects, and assessing welding quality through audio. Its memory architecture also helps robots track objects and retain context about past actions, even when objects move out of view.

Neuron AI is trained on three data sources: real-world robot interactions captured in NEURA Gyms and physical environments, simulation-generated variations of tasks, and human demonstrations recorded using sensor-equipped suits. Together, these inputs support a shared foundation model trained across five NEURA robot embodiments with different grippers and hands.

NEURA Gyms support data collection, skill training, and benchmarking, with insights informing future model releases. The Neuraverse enables deployment, fleet-wide updates, and customer-specific fine-tuning while allowing skills to remain private or be shared. The focus is on reducing Time-to-Skill, how quickly robots learn and reliably execute new tasks, to accelerate industrial adoption of Physical AI.

Developed and trained in-house in Metzingen, Germany, Neuron AI integrates NEURA’s robotics, sensing, data infrastructure, and AI capabilities to connect model development with physical performance. Training combines NEURA Gyms with industrial data partnerships, including Schaeffler and Bosch, linking Physical AI development to real-world manufacturing processes and operational requirements.

At NVIDIA GTC Berlin 2026, NEURA will demonstrate its 4NE1 humanoid robot using Neuron AI to complete an eleven-minute laundry-handling sequence autonomously, from sorting and loading a washing machine to transferring laundry to a dryer. The demonstration highlights the model’s integration of planning, multisensory perception, memory, and coordinated physical action. The showcase runs October 20–22 at Station-Berlin, Hall 3, Booth #3031.