WCCI2024 Panel: Can AI Craft AI Inspired by the Brain?: Insights from the Fathers

Educational Projects

Can AI Craft AI Inspired by the Brain?: Insights from the Fathers
This panel will be held at The IEEE World Congress on Computational Intelligence on July 3rd, 2024.  

Panel Abstract

Recent developments in neural network research have shown remarkable progress, especially with Transformer-based models. There are differing perspectives on potential paths to Artificial General Intelligence (AGI) and superintelligence: some argue that expanding computational resources and data may be sufficient. In contrast, others contend that fundamental technological elements are still missing. The acceleration of AI development raises the possibility of an intelligence explosion through AI conducting AI research. Dr. Shiro Takagi is invited as an expert in this field. The panel discussion aims to gain insights from pioneers in neural network research, with Dr. Kunihiko Fukushima and Dr. Shun’ichi Amari invited to participate. The panel aims to engage in a comprehensive discussion on the future of AI, including the evolving role of human researchers in AI development.


  • 14:20-14:30 Opening & Introduction: Hiroshi Yamakawa
  • 14:30-15:30 Presentations
    • 14:30-14:50 Kunihiko Fukushima:    Deep CNN for Artificial Vision   — Learn from Biological Brain —
    • 14:50-15:10 Shiro Takagi: Tentative: Possibilities of AI research conducted by AI
    • 15:10-15:30 Shun-ichi Amari: Artificial Intelligence vs Natural Intelligence
  • 15:30-16:00 Panel Discussion
    • Panelists: Kunihiko Fukushima, Shunichi Amari,  Shiro Takagi
    • Moderator: Hiroshi Yamakawa
  • 16:00-16:10 Summary and Closing


Kunihiko Fukushima (Fuzzy Logic Systems Institute, Japan)

A graduate of Kyoto University (1958) and a former NHK researcher. They have held professorships at Osaka University (1989-1999), University of Electro-Communications (1999-2001), and Tokyo University of Technology (2001-). With a Ph.D. in Engineering, they are a trailblazer in the field of neural network models, having pioneered the Neocognitron (1979), a precursor to modern deep CNNs for visual pattern recognition. His research is focused on brain information processing, especially on visual systems, memory, and learning. Currently a Senior Research Scientist at Fuzzy Logic Systems Institute. He continues to push the boundaries of the field from Machida, Tokyo.

Shun’ichi Amari (Teikyo University, Japan)

Japanese researcher and neuroscientist specializing in mathematical engineering. Recipient of the Order of Culture. Ph.D. in Engineering from the University of Tokyo (1963). Professor Emeritus at the University of Tokyo and Honorary Scientist at RIKEN. Person of Cultural Merit. Pioneered mathematical neuroscience, establishing foundations in learning theory, self-organization, associative memory, statistical neurodynamics, and neural field theory. Founded information geometry, applying differential geometry to information science. Worked at Kyushu University, the University of Tokyo, and RIKEN.

Shiro Takagi (AutoRes, Japan)

A rising star in the field of AI research. Their current focus is on developing AI for long-term autonomous research, with a particular interest in language-capable AI and symbolic concept representation. They are currently analyzing the impact of pre-trained language models on offline reinforcement learning and investigating systematic generalization in neural networks. Their previous work includes collaborations on out-of-distribution generalization and topological data analysis. Their graduate studies involved neural network learning dynamics and meta-learning algorithms, and their undergraduate work combined neuroaesthetics research with a thesis on Japan-US alliance public goods theory.

Chair & Moderator

Hiroshi Yamakawa (The Whole Brain Architecture Initiative, Japan)

Hiroshi Yamakawa is the chairperson of The Whole Brain Architecture Initiative (WBAI), a non-profit organization, a principal researcher at the Graduate School of Engineering of The University of Tokyo, and the AI alignment network(ALIGN) director. He is an AI researcher interested in the brain. His specialty includes brain-inspired artificial general intelligence, concept formation, neurocomputing, and opinion aggregation technology. He is a former Chief Editor of the Japanese Society for Artificial Intelligence. He received an MS in physics and a PhD in engineering from the University of Tokyo in 1989 and 1992, respectively. He joined Fujitsu Laboratories Ltd. in 1992. He founded Dwango AI Laboratory in 2014 and was a director until March 2019.