Cortical Labs Launches World's First Commercial Biological Computer, Ushering in Synthetic Intelligence
核心洞察
Cortical Labs (搜索) has cultured 800,000 living neurons from embryonic mouse cells and human stem cells that learned to play Pong within minutes, a system the company calls "synthetic biological intelligence."
In 2025, the Melbourne-based company launched the CL1 (搜索), described as the world's first commercially available biological computer, capable of sustaining up to a million neurons for six months.
The company aims to use DishBrain platforms to study how neurons respond to alcohol and pharmaceutical compounds, validating biological computing as a tool for drug discovery and personalized medicine.
In a Melbourne laboratory, scientists have grown 800,000 living neurons from embryonic mouse cells and human stem cells, cultured them into a thumbnail-sized network, and connected them to a computer. Within minutes, the neurons learned to play Pong, improving their performance by responding to electrical signals that conveyed the ball's position and generating signals to move the paddle. The experiment, developed by Cortical Labs (搜索), led to what the company calls "synthetic biological intelligence" and, in 2025, the launch of what it describes as the world's first commercially available biological computer.
Scientists remain cautious about defining what is happening inside the dish. Cortical Labs (搜索)' chief scientific officer Brett Kagan describes it as "something that resembles intelligence," not human thought or consciousness. Yet he argues that it marks the beginning of a new frontier in understanding intelligence—one known as Synthetic Intelligence.
From DishBrain to the CL1
The DishBrain experiment in Melbourne possesses what neuromorphic chip announcements lack: strangeness. Researchers believe that synthetic intelligence involves what neuroscientist Karl Friston called the free-energy principle: biological neural networks are, at their most fundamental level, prediction machines built to minimise surprise. The DishBrain neurons, once embedded in the feedback loop of the Pong game, behaved exactly as the theory predicts. When the game did not give them feedback of whether they were succeeding or not, the scientists learned nothing.
In 2025, the company moved beyond research. The CL1 (搜索), Cortical Labs (搜索)' first commercial product and the world's first biological computer, is on the market. Each CL1 is the size of an elongated toaster and boasts an onboard life-support system capable of keeping a culture of up to a million neurons alive for six months. With the CL1, Cortical Labs is aiming to become the Nvidia of neural computing, providing hardware and "neurons as a service" with a sub-millisecond delay.
A New Tool for Drug Discovery
Cortical Labs (搜索) plans to expand this research in disorienting directions. The company is aiming to study how DishBrain plays when its neurons are exposed to alcohol and pharmaceutical compounds. The purpose is to validate biological computing platforms as tools to discover new drugs and personalise medicine.
The chief executive, Hon Weng Chong, framed the ambition plainly: "DishBrain offers a simpler approach to test how the brain works and gain insights into debilitating conditions such as epilepsy (搜索) and dementia (搜索)."
This therapeutic orientation reflects a broader shift in the field. Nearly every organoid researcher reports that in human clinical trials, the failure rate for neuropsychiatric drugs is close to 95 percent. The pipeline for new medications for conditions like depression (搜索), Alzheimer's (搜索), and epilepsy (搜索) is long, and often dry. That is because drugs are ordinarily tested on animals, not people, and animal testing has never been the most physiologically relevant way to ensure the efficacy of drugs—it has just been the most practical one. Organoids and neural cultures have changed that calculus.
The Biology of Intelligence
"When you think about what you want from AI, it's biology," said Brett Kagan, Cortical Labs (搜索)' chief operating officer. "You want it to be self-repairing as much as possible. You want it to be adaptable. You want it to be long-lived. You want it to be energy-efficient. These are all features you get for free in biology."
In 2022, using a system similar to what currently powers the Cortical Cloud, Kagan grew a neural culture on a microchip and trained it to play the 1972 Atari game Pong, rewarding the neurons with predictable electrical pulses when they made correct decisions and punishing them with chaotic bursts when they made mistakes. The technique served as a minimal proof of concept for the free-energy principle, demonstrating one possible approach for programming living matter.
The Pong program comes preinstalled on the Cortical Cloud, as a package of easily deployable Python code. When run through a two-hour session, the neurons incrementally improved their game in real time, achieving a longest rally of 10 accurate shots. The neurons have since learned to play Doom.
Regulatory and Philosophical Frontiers
The questions synthetic intelligence raises are not new. They are, in some ways, the oldest questions that mankind has wrestled with. The Turing Test, devised by Alan Turing in 1950, framed the question succinctly: "Can a machine imitate a human conversationalist well enough to fool a judge?" Synthetic intelligence stands this assumption on its head. The question is no longer whether a machine can pass for human but whether a machine can develop genuine understanding through entirely different means.
The EU's AI Act, which entered into force in August 2024, regulates AI systems by risk category without distinguishing between artificial and synthetic approaches. This signifies a regulatory architecture which some researchers argue is already obsolete before being fully implemented.
For now, the possibility of what buyers can do with a biological computer is, as the company frames it, gloriously open to the imagination. In a dish in Melbourne, 800,000 neurons are playing Pong. The score, at this particular moment in history, is less important than the game.