In a story ripped from the opening scenes of a sci-fi horror movie, scientists have bridged a critical gap between the biological and electronic. The study, published in Nature Electronics (summarized in Nature), details a “hybrid biocomputer” combining lab-grown human brain tissue with conventional circuits and AI. Dubbed Brainoware, the system learned to identify voices with 78 percent accuracy. It could one day lead to silicon microchips fused with neurons.

Brainoware combines brain organoids — stem-cell-derived clusters of human cells morphed into neuron-filled “mini-brains” — with conventional electronic circuits. To make it, researchers placed “a single organoid onto a plate containing thousands of electrodes to connect the brain to electric circuits.” The circuits, speaking to the brain organoid, “translate the information they want to input into a pattern of electric pulses.”

The brain tissue then learns and communicates with the technology. A sensor in the electronic array detects the mini-brain’s response, which a trained machine-learning algorithm decodes. In other words, with the help of AI, the neurons and electronics merge into a single (extremely basic, for now) problem-solving biomachine.

The researchers taught the computer-brain system to recognize human voices. They trained Brainoware on 240 recordings of eight people speaking, “translating the audio into electric to deliver to the organoid.” The organic part reacted differently to each voice while generating a pattern of neural activity AI learned to understand. Brainoware learned to identify the voices with 78 percent accuracy.

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