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Uncovering the AI, brain science link demands bridging a divide
By Simone Castello  |  Apr 03, 2024
Uncovering the AI, brain science link demands bridging a divide
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The human brain, a three-pound spongy mass of fat, protein, and neurons, is an enigma. Its ability to generate consciousness, process information, and learn captivates philosophers and scientists alike. To get the most out of AI, one must first understand this complex organ.

CAMBRIDGE, UK - The history of artificial intelligence (AI) discloses connections between brain science and AI, per an article in ScienceDirect in March 2020 titled From Brain Science to Artificial Intelligence by Dr Jingtao Fan and others from China’s prestigious Tsinghua University. 

Its authors noted that pioneering AI researchers Alan Turing, Marvin Minsky, Seymour Papert, John McCarthy, and Geoffrey Hinton were all interested in brain science and that “the neural connections in the human brain that were discovered using microscopes inspired the artificial neural network and deep learning.” Brain science - or neuroscience - contributed to the attention mechanism, a technique used in machine learning (ML) to boost model performance by focusing on suitable information and develop the memory module, which enables a network to store and utilize knowledge gained from past tasks. 

Synergies between the AI community and brain science should be fostered to develop intelligent machines able to assume tasks previously done by humans, the authors concluded. As neuroscience is the scientific study of the means via which the brain processes information, makes decisions, and interacts with the environment, further insights into it are also likely to inspire innovative deep learning (DL) technologies.

Dr Chellammal Surianarayanan of India’s Bharathidasan University and her collaborators later explained how neuroscience validates existing AI-based models in an article titled Convergence of Artificial Intelligence and Neuroscience Towards the Diagnosis of Neurological Disorders-A Scoping Review. 

Reinforcement learning in humans and animals has also led computer scientists to create algorithms for reinforcement learning in artificial systems, enabling these to learn strategies without explicit instructions.

Neuroscience blends sundry disciplines - physiology, anatomy, molecular biology, cytolog

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It's becoming clear that with all the brain and consciousness theories out there, the proof will be in the pudding. By this I mean, can any particular theory be used to create a human adult level conscious machine. My bet is on the late Gerald Edelman's Extended Theory of Neuronal Group Selection. The lead group in robotics based on this theory is the Neurorobotics Lab at UC at Irvine. Dr. Edelman distinguished between primary consciousness, which came first in evolution, and that humans share with other conscious animals, and higher order consciousness, which came to only humans with the acquisition of language. A machine with only primary consciousness will probably have to come first. What I find special about the TNGS is the Darwin series of automata created at the Neurosciences Institute by Dr. Edelman and his colleagues in the 1990's and 2000's. These machines perform in the real world, not in a restricted simulated world, and display convincing physical behavior indicative of higher psychological functions necessary for consciousness, such as perceptual categorization, memory, and learning. They are based on realistic models of the parts of the biological brain that the theory claims subserve these functions. The extended TNGS allows for the emergence of consciousness based only on further evolutionary development of the brain areas responsible for these functions, in a parsimonious way. No other research I've encountered is anywhere near as convincing. I post because on almost every video and article about the brain and consciousness that I encounter, the attitude seems to be that we still know next to nothing about how the brain and consciousness work; that there's lots of data but no unifying theory. I believe the extended TNGS is that theory. My motivation is to keep that theory in front of the public. And obviously, I consider it the route to a truly conscious machine, primary and higher-order. My advice to people who want to create a conscious machine is to seriously ground themselves in the extended TNGS and the Darwin automata first, and proceed from there, by applying to Jeff Krichmar's lab at UC Irvine, possibly. Dr. Edelman's roadmap to a conscious machine is at