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The organizers of CEATEC 2026 announced the participation of 821 exhibitors, with a strong focus on generative AI and physical AI. Among the featured technologies is the TUSS system from the Mitsubishi Electric Group, which aims to enable models to perform multiple tasks in industrial environments.
A MONOist interview with executives from AWS and STRADVISION examines the role of AWS startup programs and cloud infrastructure in developing computer vision and physical AI solutions. The company explains how it uses AWS services, including infrastructure dedicated to training and running models, to expand its applications in automotive and robotics.
Cadence explains that physical AI depends not only on inference accuracy, but also on its ability to sense, make decisions, and execute actions within strict constraints on latency, energy, heat, reliability, and data movement. The article highlights the role of edge computing, memory, interconnects, and input/output interfaces in ensuring predictable system behavior.
Crunchbase News reviews five funding deals for companies developing floating nuclear reactors, property-maintenance robots, and tools for evaluating physical AI models, in addition to solutions for construction and agriculture. The deals reveal an investment trend toward specialized applications addressing energy, fieldwork, and industrial operations.
A facility in Narashino, Japan, has begun collecting training data for physical AI using 35 humanoid robots as part of a consortium comprising five companies. The facility relies on remote control, motion recording, and labeling successful and failed states, with the goal of building models that can be used in factories and various industries.