Human brain cells on chip learn to play Doom in a week

An Australian company has enabled a chip with human brain cells to play the video game Doom using a simple programming interface. Developed by Cortical Labs, the technology allows for quick training and marks progress toward practical biological computing applications. Experts highlight its potential for handling complex tasks like robotic control.

Cortical Labs, an Australian firm, has advanced its neuron-powered computer chips, allowing a clump of human brain cells to play the classic first-person shooter Doom. The chip, featuring living neurons grown on microelectrode arrays, performed better than random inputs but lagged behind skilled human players. This development builds on the company's 2021 achievement, when chips with over 800,000 brain cells were trained over years to play Pong.

The new system uses an interface compatible with the Python programming language, simplifying the process. Independent developer Sean Cole trained the chip to play Doom in about a week. "Unlike the Pong work that we did a few years ago, which represented years of painstaking scientific effort, this demonstration has been done in a matter of days by someone who previously had relatively little expertise working directly with biology," said Brett Kagan of Cortical Labs. "It’s this accessibility and this flexibility that makes it truly exciting."

This latest chip employed roughly a quarter of the neurons used in the Pong setup and learned faster than traditional silicon-based machine learning models. Kagan noted that such biological systems serve as unique materials for information processing, distinct from human brains. "Yes, it’s alive, and yes, it’s biological, but really what it is being used as is a material that can process information in very special ways that we can’t recreate in silicon."

Experts praised the leap from Pong to Doom. Andrew Adamatzky of the University of the West of England in Bristol, UK, stated, "Doom is vastly more complex than earlier demonstrations, and successfully interacting with it highlights real advances in how living neural systems can be controlled and trained." Steve Furber of the University of Manchester, UK, called it a significant upgrade, though questions remain about how the neurons process visual inputs without eyes or understand game objectives.

Yoshikatsu Hayashi of the University of Reading, UK, who works on similar hydrogel-based computers for robotic arms, sees parallels. "[Playing Doom] is like a simpler version of controlling a whole arm," he said. Adamatzky added, "What’s exciting here is not just that a biological system can play Doom, but that it can cope with complexity, uncertainty, and real-time decision-making." This suggests closer alignment with future hybrid computing needs, such as robot control.

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