An Australian startup called Cortical Labs announced that it managed to train around 200,000 human brain cells grown without a laboratory to interact with a classic video game Doom, originally released in 1993, these neurons were grown on an array of microelectrodes, forming a hybrid system between biology and electronics.

The heart of the experiment is a chip called CL1, capable of converting digital data into electrical signals that neurons can interpret, the system translates the game environment into electrical stimuli, the cells receive those stimuli, respond with neural activity and the system converts that activity back into digital commands that control the character within the game.

The result is a completely new type of computing where biological circuits become part of the processing. This is not the first experiment of this type. In 2021, the same company had already managed to train neurons grown in the laboratory to play Pong, the classic Arcade game. On that occasion, more than 800,000 neurons were used and the training took more than a year.

Now the progress was even more impressive, with a new software interface it took just a week for an independent developer to teach the neurons to navigate the three-dimensional environment of Doom, during the tests, the cells managed to move the character, aim and fire weapons within the game.

It is still far from the performance of a human player, but the experiment revealed something important, these biological systems demonstrated adaptive learning in real time, reacting to the environment and adjusting their responses as the game evolved and this may have much larger implications than video games.

Researchers believe that hybrid biological computers could in the future help control robotic prostheses, interpret complex signals from the human body or solve problems that require adaptive capacity.

Experiments like this show that the border between biology and technology is becoming increasingly blurred, but while some scientists are trying to transform neurons into computers, others are doing the opposite, trying to transform machines into something increasingly like human workers.