March 6, 2020
The Conversation | Neuroscience and AI can help improve each other
Because the brain and machine learning systems use fundamentally different algorithms, each excels in ways the other fails miserably.
“Despite their names, artificial intelligence technologies and their component systems, such as artificial neural networks, don’t have much to do with real brain science. I’m a professor of bioengineering and neurosciences interested in understanding how the brain works as a system – and how we can use that knowledge to design and engineer new machine learning models.
In recent decades, brain researchers have learned a huge amount about the physical connections in the brain and about how the nervous system routes information and processes it. But there is still a vast amount yet to be discovered.
At the same time, computer algorithms, software and hardware advances have brought machine learning to previously unimagined levels of achievement. I and other researchers in the field, including a number of its leaders, have a growing sense that finding out more about how the brain processes information could help programmers translate the concepts of thinking from the wet and squishy world of biology into all-new forms of machine learning in the digital world.”
Read the full article on The Conversation. Written by Gabriel A. Silva, Professor of Bioengineering and Neurosciences; Founding Director, Center for Engineered Natural Intelligence, University of California San Diego
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