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Neuralink implanted its first brain-computer interface (BCI) inside Noland Arbaugh in January. The patient, who showed “promising neuron spike detection”, had a chip with over a thousand conductors threaded into his cerebral cortex that uses Bluetooth to communicate information. While at its infancy, experts suggest that this technology’s path is unpredictable and could have large-scale effects.
A recent study had optogenetically engineered worms guided by an AI agent that could see their location and orientation towards specific points on a petri dish. The worms were found to be collaborating with the AI, rather than taking orders from or rejecting it, such that the worm listened to but could override the AI guidance.
A Chinese company revealed a homegrown brain-computer interface (BCI) that led to talks about China catching up with the US in terms of neurotechnology, highlighting the country’s new ethical guidelines which include “cognitive enhancement of healthy people” as a goal of BCI research.
We know that artificial neural networks are inspired from their biological counterparts, but how close are they to the real thing? A 2021 study attempted to model a biological neuron using a deep neural network, and found that it takes 5-8 layers of complexity to model it to 99% accuracy, with researchers suggesting that the neuron may be even more complex.
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