An ambitious new endeavor called the Thousand Brains Project aims to develop a new AI framework that its founder says will operate on the same principles as the human brain—yet will be fundamentally different from the principles underlying the deep neural networks that dominate artificial intelligence today. With funding from the Gates Foundation, the open-source initiative aims to partner with electronics companies, government agencies, and university researchers to explore potential applications for its new platform.
In today’s artificial neural networks, components dubbed neurons are fed data and cooperate to solve a problem, such as recognizing images or predicting the next word in a sequence. Neural nets are called “deep” if they possess multiple layers of neurons.
Deep neural networks currently match or beat human performance on many tests, such as identifying skin cancer and playing complex games, However, they are plagued by a host of problems. For example, as they grow in size and power, they become more energy hungry—to train OpenAI’s GPT-3, a 2022 Nature study suggested the company spent US $4.6 million to run 9,200 GPUs for two weeks. Neural networks also often prove unstable, with slight alterations in the data they receive leading to wild changes in outcomes. For instance, previous research found that changing a single pixel on an image can make an AI think a horse is a frog.
To overcome these challenges, the Thousand Brains Project aims to develop a new AI platform by reverse engineering the neocortex, which accounts for about 80 percent of the human brain’s mass.
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