This $35,000 Computer Runs on Human Brain Cells. Scientists Say It’s Not Conscious—Yet.

Here’s what you’ll learn about when you read this story:

The blending of biological and artificial “computing” is a topic that stretches back to the 1940s and 50s.
Now, Cortical Labs has successfully developed a brain-on-a-chip computer primarily designed to aid scientists and researchers studying diseases, therapies, and treatments.
The new computer—called CL-1—will be widely available in late 2025 for around $35,000.

Two very different types of “computers” dominate the world today. The first is the type you’re likely reading this article on—machines powered by transistors and silicon that make our modern society possible. Then, there’s the biological type of computer that’s been a couple billion years in the making—the human brain, which has neurons and a cerebral cortex instead of transistors and a motherboard.

These are two wildly different architectures with totally different capabilities—the human brain somehow achieves a level of consciousness unseen elsewhere in nature (or the observable universe, for that matter), but computers can do calculating tasks many times faster than our minds could ever fathom. So, it should come as no surprise that since the very origins of computing, scientists and engineers have pondered whether these two disparate “computers” could one day merge together.

Well, apparently, that time is now. Cortical Labs, an Australia-based company, announced earlier this year that it had successfully developed the world’s first “biological computer,” which it calls the CL-1. Fusing human brain cells with silicon hardware, Cortical Labs says the CL-1 is an ideal tool for science and medical research, meaning that this thing isn’t going to be siding onto your desktop and delivering a 120 frames-per-second gaming experience. Instead, this $35,000 computer—which will be widely available later this year—could make medical testing and other scientific trials easier, as scientists can essentially test would-be drugs on this ‘body in a box’ biological computer.

“The large majority of drugs for neurological and psychiatric diseases that enter clinical trial testing fail, because there’s so much more nuance when it comes to the brain—but you can actually see that nuance when you test with these tools,” Brett Kagan, Cortical Labs’ Chief Scientific Officer, told New Atlas back in March. “Our hope is that we’re able to replace significant areas of animal testing with this. Animal testing is unfortunately still necessary, but I think there are a lot of cases where it can be replaced and that’s an ethically good thing.”

Kagan was directly involved in the development of CL-1’s predecessor, DishBrain, which grabbed headlines back in 2022 for successfully playing a game of Pong (the results of which were published in the journal Neuron). As Kagan explained at the time, DishBrain played Pong quite unlike a human brain, and instead described the neurons as sort of experiencing its surroundings as if it was the Pong paddle itself.

However, this dawning era of neurons-on-a-chip computing brings up a sticky question: Could we be possibly subjecting a type of sentience to a “life” of abject misery or, at the very least, boredom? Back in 2022, Kagan said that his team was working closely with bioethicists to answer this question, and clearly came to the conclusion that this wasn’t a concern—at least, not yet.

Speaking with Live Science, a stem cell research unaffiliated with Cortical Labs came to a similar conclusion, and Suhas Kumar from Sandia National Laboratories also told Popular Mechanics back in 2022 that the simplicity of this setup means the neurons are simply responding to a stimulus. However, seeing as this is just a first step into the broader world of neuromorphic computing, the relative simplicity of CL-1 could get dizzyingly complex pretty quick.

The Cortical Labs team argues that Synthetic Biological Intelligence, or SBI, is “inherently more natural than AI” because it uses materials more akin to the human brain. As the technology progresses, this could produce results similar to that of a human mind, blurring the lines between the world’s two greatest computers even further.

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