Australia-based Cortical Labs announced that it is working on two biological data centers, one in Melbourne and another in Singapore. The biotech company has partnered with data center company DayOne to establish the two data centers, powered by the 'body-in-the-box' CL1s.
The timing signals something significant for Asian infrastructure and Australia's tech sector. By 2030, global data center capacity could reach 200 GW while Southeast Asian data-center power demand could quadruple from 2.6GW (2025) to 10.7GW (2035) in its base case, intensifying pressure on grids and emissions trajectories. For Australian exporters and technology investors tracking the region, this partnership demonstrates how local innovation can address a structural problem facing Asian markets: the collision between booming AI demand and finite energy budgets.
The CL1 units consist of a silicon chip with 200,000 lab-grown human neurons 'grown' on top, converted initially from human blood cells. The neurons used in the system are derived from human blood cells that are converted into stem cells, then differentiated into neural cells, before being integrated with the chip-based interface. The energy economics are striking. The neural approach used by the CL1 requires far less energy than a typical computer, according to Cortical Labs, requiring only a fraction of that used by conventional AI chips – less than a handheld calculator, even, according to Hon. More precisely, they draw as little as 30 watts each, positioning them as a low-power alternative to Nvidia GPU-based AI racks. By comparison, this is less than the up to 6,000 watts typically used by a GPU.
The Melbourne facility is Cortical Labs' proof of concept. According to the company, the Melbourne facility will initially house about 120 CL1 units. The Singapore deployment is more ambitious. The company is partnering with sustainability-focused data center firm DayOne to set up a smaller prototype facility at the Yong Loo Lin School of Medicine at the National University of Singapore, with plans to eventually deploy the technology in a commercial DayOne data center and test it under real-world conditions. The phased expansion could eventually scale up to deploy as many as 1,000 CL1 units at a DayOne facility.
The broader context explains the investment appetite. The announcement comes as tech giants like Google, Amazon, Microsoft, and OpenAI are spending billions of dollars to build new data centers to train and run their most advanced AI models. Traditional data centers are notoriously energy-hungry, with many requiring the equivalent power needed to supply entire neighborhoods. Electricity consumption in accelerated servers, which is mainly driven by AI adoption, is projected to grow by 30% annually in the Base Case, while conventional server electricity consumption growth is slower at 9% per year.
The technology remains experimental and unproven at commercial scale. The project remains experimental and far from replacing conventional processors. Tjeerd olde Scheper from Oxford Brookes University cautioned that the technology is still in its nascent stages, asking "Is it going to work as people might think? No, we're still in the early days of this development," and noting that direct size comparisons are challenging because CL1 chips cannot perform conventional calculations like standard silicon-based AI chips.
Still, the demonstration of capability has impressed independent researchers. The company has already appeared on radar with the CL1's launch last March, with an update just a week ago that showcased its ability to play DOOM. The neurons taught themselves a complex task in roughly a week. This matters to Singapore's strategic ambitions around sustainability-driven digital infrastructure.
The collaboration comes as Singapore expands data center capacity under tighter sustainability guardrails, making at least 200MW of new capacity in DC-CFA-2 available while reinforcing higher standards for energy efficiency and greener energy pathways under the Infocomm Media Development Authority's Green Data Center Roadmap. For Australian companies and investors watching Asia's infrastructure play, Cortical Labs' partnership is worth tracking not because biological computing will replace GPUs tomorrow, but because it signals that regional energy constraints are forcing innovation away from brute-force processing approaches.
The bottleneck remains practical. Keeping cells alive in the real world remains a key bottleneck in biocomputing and is often "laborious and time-consuming," with the company having to swap out CL1 tubing every "five to six months," though cells have been kept alive "for 500 days with no issues." Scaling from prototype to production means solving not just the neuroscience, but the logistics of keeping living systems operational in commercial conditions.
The financial model remains to be tested. These units are individually priced at around $35,000 each. Whether that price drops as volume scales, and whether the operating costs of maintaining living neural tissue prove economical against cheaper electricity in other regions, will determine whether this technology becomes a viable alternative or a sophisticated laboratory curiosity. For now, Cortical Labs and DayOne have chosen Singapore and Melbourne as the proving grounds. The region's heat and energy constraints make both cities logical testbeds for a technology that, if it works, could reshape how Asia thinks about computing infrastructure.