Vertical Labs built CL1, a biological computer made of living human neurons grown from stem cells and paired with electrode arrays. The system costs about $35,000 per unit, uses 59 electrodes to read and stimulate the cells, and the company plans to launch it March 2, 2025 in Barcelona.
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. Let's talk about it. Alright. 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 2, 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. So how does it work exactly? 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. Cortical Labs calls it a body in a box. 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 Paul 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 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. Portico 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. So what are the main applications? Well, for one thing.
