Scientists Unveil the World’s First Hybrid Biological Computer, CL1!
A groundbreaking innovation has recently emerged from Melbourne-based startup Cortical Labs, which has developed the world’s first hybrid biological computer, named CL1. This revolutionary system is built by integrating living neurons with silicon chips, bridging the gap between organic life and machine intelligence.
On March 2, 2025, the “Cortical Labs” company officially unveiled CL1, marking a significant milestone in the field of bio-computing technology. For the first time, living brain cells can interact with machines in real-time, unlocking an entirely new ear in artificial intelligence and neuroscience.
At the core of CL1 lies a futuristic computing platform powered by approximately 80,000 live neurons, specially cultured in lab-grown petri dishes. These neurons are trained using electrical impulses, much like the way AI models are taught via data input. The result is a living-silicon synergy that enables the system to perceive, learn, and adapt to stimuli—going far beyond what conventional digital computers can achieve.
CL1 is the commercial successor to Cortical Labs’ earlier prototype DishBrain, which gained global attention for its ability to learn and respond to simple tasks. In a striking demonstration, CL1 has already learned to play the classic video game Pong—not just reacting to commands but gradually mastering the gameplay through trial and error.
Researchers refer to this pioneering field as “Wetware AI” or “Organoid Intelligence”—a bold step that challenges the traditional boundaries of hardware and software by utilizing living cells to emulate human cognitive behavior. These neurons receive inputs via electrical signals and generate outputs through adaptive neural responses, making CL1 a part of what scientists call a "wetware system."
One of the most remarkable features of this technology is its energy efficiency. According to researchers, neuron-based systems like CL1 can perform similar tasks to modern AI models while using up to 1,000 times less power. Depending on the experiment, scientists use mouse neurons or lab-grown human neurons derived from stem cells to construct the neural networks.
Cortical Labs CEO Thomas Oxley explains, “This isn’t just a computer—it’s a bionic cognitive system that learns, remembers, and adapts like a living entity.” He believes that CL1 could revolutionize fields such as neuroscience, AI, brain disease treatment, and cognitive computing.
The innovation has already attracted the attention of world top class institutions including MIT and Harvard University, which are exploring collaborative research opportunities. Experts believe this hybrid technology could form a crucial link between artificial intelligence and biotechnology, setting the stage for a new generation of bio-intelligent systems.
According to the report, Cortical Labs has raised around $11 million in funding, with backing from major investors like Horizons Ventures, Blackbird Ventures, LifeX Ventures, Radar Ventures, and the CIA-backed In-Q-Tel. Each CL1 unit may cost around $35,000, and the company expects to bring it to market by late 2025.
CL1 functions as a standalone system, requiring no external computer, and consumes between 850 to 1,000 watts of power. Cortical Labs is planning to launch a 30-unit biological neural network server stack, aiming to commercially release four units by the end of 2025, primarily via cloud-based access.
Sources: Live Science, New Atlas, Data Center Dynamics.
Author Profile:
Sherazur Rahman, Teacher & Science Writer, Singra, Natore, Bangladesh. Email: sherazbd@gmail.com
“This article was written and edited with support from AI tools to ensure clarity and global readability.”
Links:
(1) https://www.livescience.com/technology/computing/worlds-1st-computer-that-combines-human-brain-with-silicon-now-available
(2) https://newatlas.com/brain/cortical-bioengineered-intelligence/
(3) https://www.datacenterdynamics.com/en/news/australian-startup-cortical-labs-unveils-worlds-first-commercial-biological-computer/
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