About Matthias Neumann
Matthias Neumann brings more than 30 years of experience in the semiconductor and technology industry, spanning embedded software, semiconductor design, application engineering, marketing and business development.
At Socionext, he focuses on radar sensing, custom System-on-Chip architectures, chiplet architectures and AI platforms for industrial robotics, collaborative robots, autonomous systems and emerging Physical AI applications.
At the Advanced Humanoid Forum, he contributes the semiconductor perspective to the question of how humanoid robots can move from prototypes into real-world applications. His focus: What computing architecture will allow Physical AI to operate efficiently, reliably and at scale?
Keynote at Advanced Humanoid Forum 2027
Topic: "Beyond GPUs: Custom SoCs and Chiplet Architectures for Physical AI at Scale"
January 20, 2027 · Morning · Main Stage
Exact time will be updated in the coming weeks.
Humanoid robots are moving from controlled demonstrations towards real-world applications. This requires more than capable AI models and advanced mechanics. The computing architecture inside the robot must process sensor data, AI workloads and real-time control within strict limits on latency, power consumption, thermal performance, system size and cost.
The key question is therefore not simply how much computing power a robot needs, but: What computing architecture is appropriate for deploying Physical AI at scale?
Matthias Neumann will discuss the role of custom System-on-Chip architectures and chiplet-based approaches in developing efficient, application-specific compute platforms for humanoid robots and other Physical AI systems. The keynote will address how specialised computing can complement general-purpose AI processing and help connect perception, decision-making and physical control in deployable robotic systems.
Areas of Expertise
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