Solving algorithm 'amnesia' reveals clues to how we learn

Solving algorithm 'amnesia' reveals clues to how we learn

2 years ago
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https://www.sciencedaily.com/releases/2022/07/220706153056.htm

The scientists focused on artificial neural networks, known as ANNs, which are algorithms designed to emulate the behavior of brain neurons. Like human minds, ANNs can absorb and classify vast quantities of information. Unlike our brains, however, ANNs tend to forget what they already know when fresh knowledge is introduced too fast, a phenomenon known as catastrophic forgetting.

Researchers have long theorized that our ability to learn new concepts stems from the interplay between the brain's hippocampus and the neocortex. The hippocampus captures fresh information and replays it during rest and sleep. The neocortex grabs the new material and reviews its existing knowledge so it can interleave, or layer, the fresh material into similar categories developed from the past.

Solving algorithm 'amnesia' reveals clues to how we learn

Jul 6, 2022, 8:43pm UTC
https://www.sciencedaily.com/releases/2022/07/220706153056.htm > The scientists focused on artificial neural networks, known as ANNs, which are algorithms designed to emulate the behavior of brain neurons. Like human minds, ANNs can absorb and classify vast quantities of information. Unlike our brains, however, ANNs tend to forget what they already know when fresh knowledge is introduced too fast, a phenomenon known as catastrophic forgetting. > Researchers have long theorized that our ability to learn new concepts stems from the interplay between the brain's hippocampus and the neocortex. The hippocampus captures fresh information and replays it during rest and sleep. The neocortex grabs the new material and reviews its existing knowledge so it can interleave, or layer, the fresh material into similar categories developed from the past.