The Rise of Biological Computing: From Pong to DOOM and Beyond
Forget silicon – the future of computing may be… alive. Australian biotech firm Cortical Labs is pioneering a radical new approach, building computers powered by living neurons. While still in its infancy, biological computing is rapidly evolving, moving from academic curiosity to commercially available cloud services. But what does this mean for the future of technology, and what hurdles remain?
Nurturing the Neural Network: A Day in the Life of a Biocomputer
The reality of maintaining a biological computer is surprisingly hands-on. Technicians at Cortical Labs’ Melbourne datacenter begin each day by replenishing the computers with a cerebrospinal fluid-like liquid, essential for keeping the neurons alive and functioning. This isn’t a set-it-and-forget-it operation; the fluid is depleted of oxygen and glucose within 24 hours, requiring daily top-ups. The atmospheric composition around the computers is carefully controlled, maintaining around five percent oxygen with a nitrogen and carbon dioxide mix – optimal conditions for these biological processors.
Beyond Speed: The Unique Advantages of Neuronal Computation
Cortical Labs isn’t simply aiming to replicate the speed of traditional computers. CEO Hon Weng Chong believes biological computers possess unique capabilities. Unlike Large Language Models (LLMs) that primarily re-order existing information, these systems can learn and devise novel solutions to problems. Crucially, they promise to do so with significantly lower energy consumption than conventional datacenters. Recent demonstrations, including teaching neurons to play DOOM, showcase this potential. The underlying research, detailed in a 2022 paper, highlights how biological neural networks (BNNs) composed of human and rodent stem cells can be integrated with silicon systems through electrophysiological stimulation and recording.
The CL1 and the Cortical Cloud: Accessing Biocomputing Power
In 2025, Cortical Labs launched the CL1, described as the world’s first commercially available biological computer. However, access to this technology isn’t yet straightforward. Recognizing the challenges of widespread adoption, the company has launched a cloud service. This allows users to access 120 CL1 units via an API and Jupyter Notebook interface, enabling them to run Python code on biological hardware. While users pay via credit card, the process isn’t as streamlined as hyperscale cloud providers; each job requires approximately a week of preparation, including sourcing specific cell lines and establishing the necessary environmental conditions.
The Cell Foundry Bottleneck and the Future of Scalability
A major obstacle to the growth of biological computing is the lack of infrastructure for cell production and handling. Chong identifies the demand for a “cell foundry” – an equivalent to TSMC for biological components – to make these computers more accessible. Currently, few organizations possess the expertise or resources to provide the necessary cells. Early adopters of Cortical Labs’ cloud service are likely to be research labs lacking in-house CL1 capabilities, or organizations exploring the technology for specialized applications, similar to early investments in quantum computing by institutions like Australian banks.
Ethical Considerations and the Quest for Automation
As biological computing advances, ethical considerations come into play. Chong admits to a degree of discomfort with granting biological computers complete autonomy, hinting at the need for careful control and oversight. Looking ahead, automation is key to scaling the technology. Streamlining the process of fluid and gas management will be crucial for wider adoption.
Biological Computing: Frequently Asked Questions
What is biological computing?
Biological computing uses living cells, like neurons, to perform computational tasks, offering potential advantages in energy efficiency and novel problem-solving approaches.
How does Cortical Labs’ CL1 work?
The CL1 uses lab-grown neurons connected to silicon hardware. Users can run code on the system via a cloud interface, leveraging the neurons’ ability to learn and adapt.
What are the potential applications of biological computing?
Potential applications include accelerating medical research, reducing animal testing, improving human health, and solving complex problems that are difficult for traditional computers.
Is biological computing energy efficient?
Yes, biological computers are expected to consume significantly less energy than conventional computers, making them a potentially sustainable alternative.
What is the biggest challenge facing biological computing?
The biggest challenge is the lack of infrastructure for cell production and handling, requiring the development of specialized “cell foundries.”
Pro Tip: Keep an eye on developments in stem cell research and bioengineering – these fields are crucial for advancing biological computing.
Want to learn more about the cutting edge of technology? Explore Cortical Labs’ website to discover the latest advancements in biological computing.
