With roots in earlier work that had these "mini-brains" mastering Pong, the leap to Doom signals rapid progress in biological computing. Critics worry this tech, backed by agendas that prioritize efficiency over ethics, might pave the way for dytopian nightmare scenarios where values of self-reliance and human dignity fall by the wayside.

The breakthrough involves roughly 800,000 to one million living human neurons clustered in a petri dish, forming what the company calls "mini-brains." These cells, stimulated by electrical signals from a computer, learn to respond in ways that control actions in the game.

Engineers at Cortical Labs translated Doom's digital environment into patterns the neurons could process. The cells' firing patterns then dictate moves like shooting or navigating.

"So we showed that biological neurons could play the game Pong," Cortical Labs chief scientific officer Brett Kagan explained in a video announcement. "This was a massive milestone because it demonstrated adaptive, real-time, goal-directed learning."

Building on that 2022 achievement, the team tackled a tougher challenge. "Doom was much more complex," Kagan added. "It's 3D. It has enemies. It needs to explore, its an environment, and it's hard."

The system, dubbed the CL1 biological computer, allows remote interaction with these living neurons via an online platform. For now, the cells perform like novices, but the learning curve is evident.

"If the neurons fire in a specific pattern, the Doom guy shoots," said Cortical Labs chief technology officer David Hogan. "If they fire in another pattern, he moves right."

Back in 2022, Cortical Labs grabbed headlines with their Pong-playing neurons, proving biological systems could adapt in real time. Now four years later, the same tech has evolved to handle Doom's demands, with reports confirming around 200,000 neurons fused with silicon chips enabling gameplay.

Other sources highlight the CL1 as a "code deployable biological computer," shipped since last year, blending human cells with traditional computing. Developers access it remotely, hinting at scalable applications.

Yet, as this tech matures, questions arise. Proponents tout potential for AI or robotics, but skeptics see echoes of transhumanist fantasies peddled by global elites at forums like Davos.