Cortical Labs has trained human brain cells on a chip to play Doom — and it took roughly a week.
The Australian company first demonstrated neuron-powered chips in 2021, when it used them to play Pong. That project required years of work by specialist researchers. The Doom demonstration was built by an independent developer, Sean Cole, who had limited prior biology experience.
The chip used in the Doom test contained roughly a quarter as many neurons as the Pong chip — which itself used more than 800,000 living brain cells grown on microelectrode arrays capable of both sending and receiving electrical signals.
What Changed
Cortical Labs developed a new interface that allows these biological chips to be programmed in Python. That shift in accessibility is what made the week-long timeline possible.
“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.
The chip’s performance fell well below skilled human players but beat a randomly firing baseline. According to the announcement, it also learned faster than traditional silicon-based machine learning systems.
Kagan cautions against framing this as brain simulation. “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,” he said.
Why Doom Matters
Andrew Adamatzky at the University of the West of England called the game a meaningful step up in complexity. “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,” he said.
Steve Furber at the University of Manchester acknowledged the leap from Pong but noted significant gaps remain — including how the neurons understand what is expected of them, or how they effectively “see” a screen without eyes.
Yoshikatsu Hayashi at the University of Reading sees a direct line from this work to practical use. His team is attempting to control a robotic arm using a similar computer built from jelly-like hydrogel. Playing Doom, he says, “is like a simpler version of controlling a whole arm.”
Adamatzky puts the broader significance plainly: “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. That’s much closer to the kinds of challenges future biological or hybrid computers will need to handle.”
Photo by A Chosen Soul on Unsplash
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