- InnoCORE-LLM
- Platform for Real-world Innovation in Smart Manufacturing through AI (PRISM-AI)
- AI-CRED Institute(AI Co-Research & Education for Innovative Drug)
- AI-Transformed Aerospace Research Center
- Photonic artificial Intelligence COmputing REsearch Center
- Regenerative Medical Research Institute (reMRI) for Aging-related Diseases
- T-RAX: Transformative Railway with AX
- 5D AI-RI: 5D AI Robotics Initiative
- Artificial Cell Initiative
- POwer-autonomous Subsea Engineering for Intelligent Data-center Operating Networks
- Sustainable Materials Institute for Post-AI Era
- AI Meta-Scientist
AI Meta-Scientist
KEYWORDKeyword
OBJECTIVE Objective
The AI Meta-Scientist Research Center aims to realize next-generation AI systems
that autonomously generate new knowledge through the integrated orchestration of models, reasoning, and systems.
Moving beyond single-task problem solving, we target the development of a principal investigator-level AI model
capable of designing continuous scientific advancement.
This includes generating novel knowledge beyond the training data distribution, understanding multimodal scientific information
and accumulating long-term knowledge, and accelerating innovation in AI for Science through autonomous experimentation.
Through these efforts, we aim to drive a paradigm shift in AI-driven scientific research.
INTRODUCTION Director's Message
Hello, I am Professor Tae-Kyun Kim from the School of Computing at KAIST.
The AI Meta-Scientist Research Center seeks to go beyond the limitations
of existing AI research by developing AI systems that automate knowledge generation and scientific discovery.
In particular, through a full-stack approach integrating models, reasoning,
and systems, we aim to move beyond incremental performance improvements
and realize AI that can conduct scientific research itself.
Through this vision, we seek to advance AI from a mere tool for
researchers to an active agent that creates new science.
IMPACT Impact
Technological Advancement
- Enhanced knowledge reuse through long-term literature understanding and meta-knowledge management
- Discovery of new scientific knowledge through cross-domain integration
- Development of scalable AI platforms applicable to diverse domains, including bio and medical fields
- Advancement toward core technologies for next-generation AGI
Industrial & Societal Contribution
- Acceleration of R&D through virtual research lab platforms
- Reduction in research costs and improvement in productivity
- Expansion of research automation and accessibility via autonomous scientific systems
- Mitigation of research gaps and strengthening of national knowledge infrastructure
TALENT Ideal Talent
AI leaders who drive breakthrough research beyond existing limitations, equipped with
full-stack capabilities spanning models, reasoning, and systems, and a strong sense of technical ownership.
Individuals who can bridge academia and industry,
and design and realize the next-generation AI paradigm.