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KAIST Launches Deep-Tech Scale-up Valley, Unveils Execution Strategies for Physical AI < Progress Report Meeting of the Deep-Tech Scale-up Valley Project > KAIST announced on February 27th that it held the "Deep-Tech Scale-up Valley Project Progress Report Meeting" at its main campus in Daejeon on the 26th. During the meeting, the university unveiled its Physical AI strategies and execution structures, currently being developed with a focus on robotics. The Deep-Tech Scale-up Valley Promotion Project is a joint initiative by the Ministry of Science and ICT, Daejeon Metropolitan City, and KAIST. KAIST has secured a total budget of 13.65 billion KRW for a period of three years and six months, starting from 2025. The project aims to commercialize KAIST's deep-tech capabilities in robotics to build a robust robot innovation ecosystem. A "Robot Alliance" has been formed, led by KAIST (headed by Professor Jung Kim) and including KAIST Holdings, Daejeon Techno Park, Daejeon Center for Creative Economy & Innovation, Angel Robotics, and Eurobotics. The project seeks to foster a virtuous cycle ecosystem and nurture future "Unicorn" companies based on a three-pillar framework: Technology Commercialization, Deep-Tech R&D, and Commercialization Scale-up. In its first year (2025), the project achieved 230 billion KRW in technology transfers and investment attraction through Physical AI lectures, startup pitching sessions, and investment networking. Physical AI refers to technology that combines robotics with artificial intelligence, allowing machines to make autonomous decisions and act in the real world. While it is gaining traction as a core field of next-generation industry—with increasing government R&D, corporate investment, and startup activity—critics have noted that successful business models applicable to actual industrial sites remain limited. This report meeting is significant in that it redefined Physical AI not merely as a competition of AI technology, but as a matter of "industrial structure." It emphasized that commercialization is difficult unless R&D, industrial sites, and the investment ecosystem are organically linked. Specifically, the report stated that for Physical AI to be applied to industrial sites, "meaningful data" generated from real-world operations is required, going beyond virtual environments. The strategy involves collaborating with skilled experts in manufacturing processes to accumulate data reflecting physical sensations and judgment, and establishing an execution system where robots can continuously cooperate with humans without obstructing their tasks. Professor Kyoungchul Kong of the KAIST Department of Mechanical Engineering stated, "It is now crucial to clarify the mixed concepts of Physical AI and create a concrete platform that anyone can utilize." He added, "For AI learned in virtual environments to function properly with actual robots in the real world, we must not only improve the accuracy of virtual technologies but also ensure that physical variables in the real world are predictable and stably managed." In simpler terms, technology is needed to ensure that a robot's performance in a simulation translates seamlessly to the real world. Professor Hyun Myung of the KAIST School of Electrical Engineering highlighted, "In the field of AI, research on Physics-Informed Neural Networks (PINN), which incorporate physical laws into the learning process, is actively underway." He emphasized, "The completion of Physical AI is possible only when hardware researchers, who understand actual physical systems, and AI researchers, who implement these into learning structures, are organically integrated. We need AI that understands physical principles, going beyond simply learning massive amounts of data." Based on this execution structure, KAIST plans to establish a clear Value Chain connecting researchers, industrial experts, and corporations. The strategy is to expand Physical AI from lab-scale demonstrations to technologies that solve real-world industrial problems. Jung Kim, Head of the KAIST Department of Mechanical Engineering, stated, "We have moved past the era of competing on data volume; now is the time to contemplate how to execute AI in the physical world. Based on KAIST's specific preparations and execution strategies, we will support startups and companies to succeed in the commercialization of Physical AI." Meanwhile, the Deep-Tech Scale-up Valley Project plans to step-by-step promote the establishment of a Physical AI platform, startup discovery and investment expansion, the creation of verification testbeds, and the expansion of cooperation networks with global robotics companies.
2026.02.27 View 1978