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Find the latest information on GENIAC briefings, seminars, community activities, and other events.
Read reports on GENIAC events and highlights from presentations and sessions.
This is a place for sharing information on Slack, holding seminars and online events with invited experts, and discussing the latest status of generative AI.
Screening and consent are required for participation.
Knowledge Sharing Among AI Developers
Promoting AI Adoption and Development Through Matching
Study Sessions and Seminars with Experts
GENIAC (Generative AI Accelerator Challenge) is a project led by the Ministry of Economy, Trade and Industry (METI) and the New Energy and Industrial Technology Development Organization (NEDO) to strengthen Japan’s AI development capabilities and accelerate real-world deployment.
Foundation Models
Generative AI Foundation Model Development – Phase 4
Robot Foundation Models
(Autonomous Driving)
R&D for Robot Foundation Models
Robot Foundation Models
(General-Purpose Robots and Other Applications)
R&D for Robot Foundation Models
AI Ecosystem
R&D for Building Data Ecosystems and Related Areas
AI-Ready
R&D for Making Manufacturing and Other Data AI-Ready
Introducing related projects and organizations that collaborate with GENIAC to advance R&D and real-world deployment in AI robotics and physical AI.
Introducing related communities that promote knowledge sharing, networking, talent development, and other activities in the field of generative AI.
We share information on generative AI, reports on events and seminars, interviews, and more through GENIAC MAGAZINE.
Stay tuned for more updates.
The Fourth Business Matching Event for GENIAC Developers and User Companies Was Held
Workshop Held to Explore Future Collaboration with the “FRONTia” Project Aimed at Developing a Domestic Multimodal Foundation Model
“International Outreach Event on Japan’s Physical AI Policy” Held
Supports the procurement of compute resources and infrastructure for domain-specific model development.
Supports the procurement of compute resources, machinery, and equipment needed to develop robot foundation models.
Supports costs associated with building datasets and data ecosystems, while promoting broader adoption of the resulting outcomes.
Supports the establishment of methods for making manufacturing and other data AI-Ready, while promoting broader adoption of the resulting outcomes.