Artificial Intelligence has recently experienced remarkable progress, largely driven by deep learning and Big data. Systems based on Large Language Models and other foundation models have demonstrated impressive capabilities across a wide range of tasks. However, these approaches remain fundamentally limited forms of narrow intelligence, often lacking robustness, reasoning depth, long-term autonomy, and genuine understanding.
The goal of this workshop is to explore unconventional and forward-looking research directions that may contribute to the development of Strong AI or Artificial General Intelligence (AGI). We aim to create a forum for discussing ideas that go beyond current dominant paradigms and investigate alternative physical, computational, cognitive, and theoretical frameworks for machine intelligence.
The workshop welcomes contributions that challenge existing assumptions and propose novel architectures, learning principles, and interdisciplinary perspectives, including insights from physics, chemistry, neuroscience, cognitive science, and embodied intelligence. By bringing together researchers interested in bold and emerging ideas, the workshop aims to stimulate discussion on the foundations, limits, and future trajectories of AI.