Name: This New AI is Made of Living HUMAN BRAIN Cells (Synthetic Biological Intelligence)
Uploaded: 2025-03-13T01:53:30.000Z
Duration: 8 min 7 s
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Scientists just built a computer powered by living human brain cells, and it learns faster than any AI chip out there.

It doesn't even need a traditional computer to run.

This isn't sci-fi, it's real, it's on the market, and the craziest part, you can actually buy one.

All right, now, I know biological computer sounds pretty wild.

We're talking about a computer made partly out of living human brain cells, actual living neurons, plus silicon hardware, working together to form what they're calling synthetic biological intelligence.

This new form of AI, or SBI for short, is not just some sci-fi concept, it's real, and it's been officially launched.

Vertical Labs revealed the CL1 at an event in Barcelona on March 2nd, 2025, and they say it's going to revolutionize everything from drug discovery to disease modeling to how we might build future robotics and automation systems.

The idea is that these neurons, which are grown in the lab from induced pluripotent stem cells, or iPSCs, can be placed on something like a silicon chip that has electrodes laid out in a grid.

In the CL1 setup, there are 59 electrodes, forming a sort of playground for these neurons to grow and form connections.

It has its own life support system so the cells can thrive, filtration, pumps, temperature control, gas mixing, basically an entire environment to keep the neurons healthy.

This is then connected to software that reads and writes signals to the neurons in real time.

Because these brain cells thrive on predictable signals, they're basically searching for energy-efficient ways to respond, the system can reward them for doing something right and punish them for doing something wrong.

Cortical's earlier research, published in the journal Neuron, showed that, with the right stimulus, these cultured neurons learned how to play the classic arcade game Pong.

The researchers would send electrical signals to tell the cells where the paddle was and the cells would respond.

If the virtual ball was missed, a random, chaotic signal was sent back, which the cells didn't like.

If they hit the ball, the signal was more predictable, so over time, the neurons got better at Pong.

That first version was called Dishbrain, and it made headlines because it was basically the beginning of this idea that you could have a self-learning, living network on a chip.

Dishbrain was neat, but the new CL1 is way beyond that.

Cortical Labs has reworked the technology to be more stable, more energy-efficient, and easier to program.

The CL1 has planar electrode arrays, basically glass and metal, which simplify the process of balancing out any electrical charge that builds up.

They've also introduced something called the Minimal Viable Brain concept, the notion that they can figure out just which types of cells and how many are needed to create something that can, in effect, learn and adapt in more advanced ways.

If that wasn't cool enough, the CL1 only draws about 850 to 1,000 watts of power for a full rack of 30 units.

A single CL1 box, about $35,000 for the hardware alone, doesn't even require an external computer to function.

It's all self-contained, with a touchscreen interface to help researchers monitor the data and keep track of experiments.

The plan is to produce racks that each house 30 CL1 units, forming a huge biological neural network server.

Cortical Labs is aiming to have four of these racks online and available by the end of 2025.

They're calling it Wetware as a Service, which basically means you can buy time on these biological computers from anywhere in the world via the cloud.

You don't need to own or maintain the actual hardware if you don't want to, you can just log in and start running experiments.

Well, for one thing, drug discovery and disease modeling, traditional systems for studying neurological diseases like epilepsy and Alzheimer's, rely on either animal models or 2D cell cultures that aren't quite as dynamic as a living network.

And that leads to a lot of drugs failing clinical trials.

Cortical Labs thinks these biological computers will open up new avenues to test therapeutics, replace some animal studies, and hopefully speed up finding treatments for diseases of the brain.

It might also give us new ways to fine-tune personalized medicine.

Because you can grow neurons from someone's own cells, you could see exactly how that specific individual's neurons respond to a certain drug.

Essentially, you could wire a neural network like the CL1 into a robot and have the robot learn in more human-like ways.

Instead of just feeding it zillions of lines of code or letting it chew on huge datasets, the robot's brain might figure things out with more flexibility and energy efficiency, kind of like how humans do.

And about that energy efficiency, keep in mind that large-language models like ChatGPT run on massive arrays of GPUs or specialized silicon, which can burn through a lot of power.

SBI technology, on the other hand, is using living neurons, which are extremely energy-efficient.

Think about how your own brain uses around 20 watts to keep you up and running.

It's a fraction of what a big data center might use for an equivalent level of machine intelligence, though equivalent is obviously tricky to define.

Cortical Labs claims that a single CL1 rack only uses a bit less than 1 kilowatt, which is like running a small microwave.

Now you might be wondering, is this system conscious?

According to Cortical Labs, we're not dealing with anything that's aware of its existence.

It's more of a specialized computing substrate, where the neurons are grown in a carefully controlled environment that's specifically designed to harness their computational power.

Ethically, of course, there are a lot of questions.

Cortical Labs has said that they're following regulations from health agencies, bioethics committees, and government organizations, and they're open about the debate, especially around using human brain cells.

But they argue that these are induced pluripotent stem cells, meaning they can become just about any cell type, and they're not forming full brains with consciousness.

Instead, they're partial networks that happen to be fantastic at learning tasks.

For those of you who are super technical, the CL1 is basically a fully programmable system with a bi-directional stimulation and read interface, meaning you can send signals in and measure signals out in real time.

There's also a Python API for folks who want to integrate it into their own applications.

It's a dream for researchers who want to build custom experiments or tailor the neural network to test new theories about learning, memory, or disease.

Cortical Labs has been working on this for almost six years now.

Their founder and CEO, Dr. Han-Weng Chong, and Chief Scientific Officer Dr. Brett Kagan have led the charge on bridging biology and silicon.

The team made waves when they embedded their cell cultures in that Pong simulation, but that was just scratching the surface.

Now they've got the manufacturing, the racks, the cloud platform, and a roadmap for turning this into something any big-thinking researcher or innovator can hop onto.

So will this lead to the next big leap in AI?

Synthetic biological intelligence could be the turning point, where computers get way more natural in how they learn and adapt.

We're already seeing how large language models have revolutionized the way we interact with AI, but if you throw actual human neurons into the mix, the possibilities might multiply.

The CL1 is here, and it's not just a concept, it's happening.

It'll be interesting to see how researchers and innovators put it to use.

Mind-blowing tech, or a little unsettling?

And if you enjoyed this breakdown, don't forget to like, subscribe, and share.

Thanks for watching, and I'll catch you in the next one.