Nearly all the neural networks that power modern artificial intelligence tools such as ChatGPT are based on a 1960s-era computational model of a living neuron. A new model developed at the Flatiron Institute's Center for Computational Neuroscience (CCN) suggests that this decades-old approximation doesn't capture all the computational abilities that real neurons possess and that this older model is potentially holding back AI development.

The new model developed at CCN posits that exert more control over their surroundings than previously thought. The updated neuron model could ultimately lead to more powerful that better capture the powers of our brains, the model developers say.

The researchers present the model in a paper published in the journal Proceedings of the National Academy of Sciences.

"Neuroscience has advanced quite a bit in these past 60 years, and we now recognize that previous models of neurons are rather rudimentary," says Dmitri Chklovskii, a group leader at the CCN and senior author of the new paper. "A neuron is a much more complex device—and much smarter—than this overly simplified model."

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