It sounds like the opening of a sci-fi film, but US scientists recently uploaded a copy of the brain of a living fly into a simulation. In San Francisco, biotechnology company Eon Systems created a virtual insect that knew how to walk, fly, groom and feed in its virtual environment. Researchers in Australia, meanwhile, have taught a petri dish containing 200,000 human brain cells to play the iconic 90s shooter Doom. One experiment has pushed a brain into a computer; the other has plugged a computer into brain cells.
Both stories have been hailed as scientific breakthroughs, but have also sparked inevitable fears about the prospects of lab-grown humans and digital clones. Should we be concerned?
It was Australian startup Cortical Labs in Melbourne that taught a dish of lab-grown neurons to play Pong in 2022. Now it has built what it describes as “the world’s first code-deployable biological computer”, running on living human tissue rather than silicon chips, which is happily playing the 1993 shooter Doom.
double quotation markAt first it didn’t know how to move, aim or shoot. Then it would shoot two enemies and stop. So it’s definitely learning
“In computer-science nerd land, there’s this obsession with getting Doom to run on everything, from calculators to microwaves,” Hon Weng Chong, CEO of Cortical Labs, tells me over Zoom from Melbourne. “As soon as we managed to get Pong to work, the first thing people said was: ‘When are you going to do Doom?’”
The average human brain contains about 86bn neurons – roughly 430,000 petri dishes’ worth. But how do you harvest 200,000 brain cells without resorting to a hacksaw and an ice-cream scoop?
“They’re my brain cells, actually – at least most of them are,” Chong says proudly. “There’s no scraping or brain extraction. It’s a very cool technique that was developed by Professor Shinya Yamanaka, who won the Nobel prize in 2012.”
All you need is 10ml of blood (in this case Chong’s), from which around 100 white blood cells can be harvested. These can then be reprogrammed into induced pluripotent stem cells (iPSCs) – the body’s biological building blocks – which can then be reproduced exponentially.
Close-up of 200,000 neurons on a glass slide the size of a 50p piece. Photograph: Cortical Labs
“Essentially we reverse the biological clock back to an embryonic state, induce them into neurons, and put them on a glass chip roughly the size of a 50p piece,” explains Chong . “Because they’re on a chip – and electricity is the common language between neurons and the computer system – we can interface with them and get them to play Doom.”
Cortical Labs conducted its Pong experiment in-house, but this time it reached out to 24-year-old Singaporean Sean Cole, who has just completed an MSc in artificial intelligence at the University of Sussex, and whose dad happens to be mates with its CEO. Cole wrote the code remotely, which the team then tested on their local machines.
“I was a bit surprised it worked the first time around,” he tells me over Zoom.
So how does a petri dish of brain cells play Doom when it doesn’t have any eyes? Or fingers? “We take a snapshot of the game with information like the player’s health and the position of enemies, pass it through a neural network, convert it into numbers, and send the data,” explains Cole. “This is called encoding – essentially turning the game state into signals the neurons can understand. The neurons then fire an output – move left, move right, walk forward, shoot or not shoot – which the system decodes and converts back into actions in the game.”
“If you think about how humans operate, we have information going into our retina, which is converted into electrical signals, processed in the brain, and then an output happens,” adds Chong. “It’s really no different from that.”
If a computer full of brain cells is playing a video game and making decisions, does that mean it’s sentient? Or is it just behaving like the average Doom player? “People have different perceptions of what sentience is,” says Cole. “I definitely don’t think it’s conscious. At first it didn’t know how to move, aim or even shoot. Then it would shoot the first two enemies and stop – almost as if it was preserving itself. So it’s definitely learning. We’ve managed to control a brain to learn in a very controlled environment. The next step could be something like Neuralink, where you inject a chip into the brain to train someone to learn a language faster.”
Exactly how the cells are learning to play the game is unclear. “We can hypothesise that it might involve things like the free energy principle – the idea that living systems act to minimise free energy – or Hebbian learning, where connections between neurons strengthen when they fire together.” Could we ever use technology like this to instantly learn kung fu, as in The Matrix? “If we find a way to safely connect this technology to humans, that is kind of what the implications might be,” Cole says. “A big concern would be: what if you override someone’s memories?”
‘I don’t think it’s conscious’ … Doom encoded for the biological computer to play. Photograph: Cortical Labs
While Chong says he’d like to try getting the neurons to play Pokémon next, the real future application here lies not in getting trays of human neurons to graduate to playing Minecraft or Grand Theft Auto, but in medicine. “People are looking at it from biomedical research angles, for disease modelling,” he says. “Things like epilepsy, where drugs could be tested on neurons grown outside the body – not just to discover new drugs, but to tailor them at a personal level.”
Meanwhile, in San Francisco, where Eon Systems has scanned a fruit fly brain and recreated it as a virtual insect, the big scientific news is that the team have essentially recreated the creature’s behavioural wiring. The digital insect already knew how to behave like a fly, without any training or prompting. This challenges a central assumption of modern AI: that intelligence must be acquired. In the case of the fly, much of its behaviour appears to be built-in.
“The brain was scanned using electron microscopy. Our head of engineering led a project to emulate that brain, and now we’ve placed the emulated brain back into a body, so it can wander around a virtual world,” Michael Andregg, CEO of Eon Systems, tells me.
A fruit fly’s brain comprises around 140,000 neurons – about five petri dishes’ worth. The virtual fly has 87 joints and can do pretty much anything an actual fly can. But does it realise it’s living in a simulation?
“The fly probably knows something’s off, because we’re not simulating the environment with high fidelity,” says Andregg. “We can’t give very specific taste and smell cues – just that something smells sweet or tastes bitter, but there are no complex aromas.”
double quotation markMoravec’s paradox is well known in robotics: what humans find difficult, computers find easy, and vice versa
Brain emulation, Andregg suggests, could eventually allow humans “to flourish in a world with superintelligence. Our goal is to make the emulation and computed brain and body feel indistinguishable from the natural biochemical body and brain,” he continues. “If it feels different, we’ve done something wrong.”
But we’re still a long way from the upload-yourself-into-the-internet futures imagined in Devs or The Lawnmower Man, mainly because, in this case, the fly’s brain had to be removed from the body first. “Scanning the body was too hard,” says Andregg, which will probably reduce the waiting list for human volunteers willing to try out the technology.
The digital fly, and a map of its 140,000 neurons. Photograph: Eon Systems
Chong, meanwhile, believes biological computing could achieve things that traditional computing has struggled with. “There’s a thing called Moravec’s paradox, which is well known in robotics: what humans find very difficult, computers find easy, and what computers find difficult, humans find easy,” he says.
“Abstract reasoning, mathematics and language are relatively recent in evolutionary terms, which is partly why computers excel at them. But motor control and probabilistic decision-making are things we’ve inherited through millions of years of evolution. Robots may be very good at solving maths problems, but we’re still trying to build robots that can walk properly.” Biological systems like the fruit fly simulation, he says, might eventually power robots, drones and other machines that need to navigate the messy unpredictability of the real world.
For now, humanity’s first biological computer is busy doing what humans have always done with new technology: playing games. And somewhere in Silicon Valley, a fruit fly is living its second life inside a computer, totally unaware that it is living in the insect Matrix.
