What's Happening?
Cortical Labs, an Australian biotech startup, has developed a data center powered by human brain cells, requiring daily replacement of cerebrospinal fluid. The company's 'CL1' machines utilize hundreds of thousands of living neurons, which deplete the
oxygen and glucose in the fluid, necessitating daily replenishment. The data center operates under carefully controlled conditions, with technicians managing a gas mixture to maintain optimal oxygen levels for the neurons. The CL1 units, touted as the world's first code-deployable biological computers, have demonstrated capabilities such as playing the complex video game Doom. Despite being highly experimental, these machines are noted for their low energy consumption, using less power than a handheld calculator. Cortical Labs is expanding its operations, planning new facilities in Melbourne and Singapore, and offering a cloud computing service using a stack of CL1 units.
Why It's Important?
The development of biological computers by Cortical Labs represents a significant innovation in computing technology, potentially offering a more energy-efficient alternative to traditional computers. This could have substantial implications for data centers, which are major consumers of electricity. The ability to perform complex tasks with minimal energy could lead to cost savings and reduced environmental impact. However, the practicality and scalability of these machines remain uncertain, as they require specific environmental conditions and a significant setup time. The expansion of Cortical Labs' operations and the introduction of a cloud computing service suggest a growing interest in this technology, which could influence future developments in the computing industry.
What's Next?
Cortical Labs is working on scaling up its operations, with plans to build new data center facilities in Melbourne and Singapore. The Singapore facility is expected to house up to 1,000 CL1 units. The company has also launched a cloud computing service, allowing customers to access the CL1 units via API. As the technology is still in its experimental phase, further research and development will be necessary to determine its full capabilities and potential applications. The success of these initiatives could pave the way for broader adoption of biological computing in various industries.
