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Staff reportedly replace the liquid bathing Cortical Labs’ living-neuron computers every 24 hours because the cells use oxygen and glucose from it. Despite the vivid headline, the available reporting does not establish that the liquid is fluid taken from human spinal columns: it is better understood as a laboratory cell-culture medium that supports the neurons.
What the CL1 biological computer is
Cortical Labs’ CL1 is a biological-computing system: living neurons are connected to electronics so the system can receive input, produce measurable activity and use that activity in a computational task. The reported units contain upwards of 200,000 neurons, a company- or press-reported figure rather than an independently verified count in the available coverage. Futurism’s report on the CL1 describes neurons interfaced with electronics; it does not describe a miniature complete brain.
Here, “neural network” means a culture of living neurons, not necessarily the software-based artificial neural network used in conventional AI. “Wetware” is an informal label for biological components in a computing system. An organoid is a three-dimensional cell culture that models some properties of an organ; the available reporting does not establish that every CL1 preparation should be called an organoid.
Why staff change the liquid every 24 hours
Cortical Labs CEO and founder Hong Weng Chong reportedly said staff remove and replace the liquid every 24 hours because the neurons consume oxygen and glucose from it. The liquid is therefore part of the cells’ support system, not simply a coolant. Cell-culture media can supply nutrients and help maintain conditions that cells need, while routine exchange can refresh that environment.
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- 【FILTER CAP FOR GAS EXCHANGE】The vented filter cap supports continuous gas exchange, making the flask suitable for open cell culture conditions, routine incubation, and cell expansion workflows.
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- 【EASY ACCESS AND HANDLING】The short, wide, angled neck provides convenient access for pipettes, serological pipettes, cell scrapers, and cell lifters. The ergonomic design makes filling, feeding, and cell harvesting easier.
- 【CLEAR VIEW OF CELL GROWTH】Made from high-quality polystyrene with excellent optical clarity for convenient observation of cell distribution and morphology under a microscope. The flat growth surface supports consistent viewing.
- 【PREPARED FOR LAB USE】Processed by Irradiation Sterilized and supplied DNase-free and RNase-free. Available in 25 cm², 75 cm², and 175 cm² culture areas to support different laboratory culture scales.
Popular coverage describes the liquid as cerebrospinal fluid, or CSF—the body fluid surrounding the brain and spinal cord. But the reported daily procedure is more precisely described as replacing the nutrient-rich laboratory medium bathing the neurons. The coverage does not establish that staff use harvested human CSF, and it gives no exact medium formulation, exchange volume, or details of the transfer and disposal procedure. The syndicated report of the 24-hour replacement attributes the detail to Chong.
What the reported 5% oxygen means
Chong reportedly said the company uses nitrogen and carbon dioxide to produce a surrounding atmosphere containing 5% oxygen, which he described as optimal for the computerized neurons. That is about one-quarter of the roughly 21% oxygen in ordinary air. It is a company-reported laboratory operating detail, not evidence that technicians work in an oxygen-free room.
The figure refers to the reported surrounding gas mixture; it does not, by itself, specify how much oxygen is dissolved in the culture medium or reaches the cells. The available reporting also does not show whether 5% applies to every CL1 operating condition.
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- Secure Sealing and Convenient Labeling: the tissue culture kit equipped with a frosted writing area, the flask allows easy marking of sample information; Dual-sided volume graduation lines enable real-time monitoring of culture medium levels, aiding in precise experimental control; The sealing design prevents leakage and minimizes the release of metal ions, ensuring the integrity of cell cultures
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- User-friendly Operation Design: the wide, short neck structure is compatible with pipettes, cell scrapers, and other common tools, simplifying liquid transfer and cell harvesting; The angled neck design reduces operational complexity, streamlining workflows and improving overall experimental efficiency
How neuron activity becomes a computer output
At a high level, the system closes a loop between software, electronics and living cells:
- Software or an external task supplies input to the neuron culture through electrical stimulation or another interface.
- The neurons respond through their biological activity.
- Electrodes record activity, which software interprets as an output or control signal.
- Feedback from the task can then be supplied to the culture, allowing the system’s activity to adapt.
The coverage does not specify the exact electrode design, signal-encoding scheme, learning algorithm, training duration or error rate. Those details matter when comparing performance, so the broad description of a working input-output loop should not be mistaken for a complete technical specification.
What Pong and Doom demonstrations show—and what they do not
Cortical Labs drew attention in 2022 with neurons trained to play Pong. The CL1 has since been demonstrated playing Doom, a task involving movement, navigation and responses to enemies, according to the same Futurism coverage. The company describes the CL1 as the “world’s first code-deployable biological computer.” That is a company claim, not an independently established industry ranking in the reporting available here.
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A game demonstration is evidence that a neuron-electronics system can participate in a particular closed-loop task. It does not establish general intelligence, superiority to CPUs or GPUs, or reliable execution of arbitrary commercial workloads. The report supplies no benchmark methodology or comparative performance figures for Pong or Doom.
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Why “data center” needs qualification
A conventional data center primarily houses computing hardware and the infrastructure that powers, cools and connects it. A facility for living-neuron computers also needs biological support and servicing: culture maintenance, controlled gases, sterile operations, electronics and software. “Biological-computing facility with data-center ambitions” is a more accurate description of the reported plans than an assumption that this is already a conventional cloud-scale deployment.
The report describes a planned Singapore site with room for up to 1,000 CL1 systems; that is a stated capacity, not proof that 1,000 units are operating there. It also reports a cloud service using a stack of 120 CL1 units for API-accessible computing, but does not establish audited deployment, public availability, signup terms or customer scale. A reported preparation time of about one week and the need to tailor cells and physical environments to customer requirements also distinguish this setup from provisioning an ordinary server.
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- Facilitates Gas Exchange: Filter cap suitable for open culture conditions, ensure gas exchange during cell and tissue culture, maintain normal cell growth and metabolism
- Easy Access: Short, wide, angled neck design for easy access, can be used with cell scraper, inoculating loops
- Improve Cultivation Efficiency: Advanced TC treatment enables cells to attach and grow better, optimizes the adhesion effect, and improves culture efficiency
- Easy to Observe: Made of high-quality polystyrene, high transparency, easy to observe the cell growth through the microscope
- Widespread Use: Gamma radiation sterilized, non-pyrogenic, suitable for most cell culture and cell expansion experiments in laboratories and schools
The energy claim is only part of the operating picture
Chong reportedly told Bloomberg that each CL1 uses less power than a handheld calculator. The coverage provides no measured wattage, workload, test conditions or comparison method, so the statement should be treated as a CEO claim rather than a full-system energy result.
Even a low-power figure for an individual unit would not answer how much energy a facility uses. A meaningful comparison would need to account for supporting equipment such as incubators, gas control, pumps, temperature regulation, monitoring and networking, as well as labor and consumables. It would also need to measure useful work per unit of energy against a defined CPU, GPU or other baseline. The reported figure does not supply those comparisons.
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Operational constraints that scaling would have to solve
Living cultures impose requirements that do not map neatly to adding more silicon servers. The reported daily medium exchange and controlled gas environment illustrate how much of the system’s operation is biological maintenance. The reported week-long preparation estimate adds lead time before a machine is ready for a job.
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- Facilitates Gas Exchange: Filter cap suitable for open culture conditions, ensure gas exchange during cell and tissue culture, maintain normal cell growth and metabolism
- Easy Access: Short, wide, angled neck design for easy access, can be used with cell scraper, inoculating loops
- Improve Cultivation Efficiency: Advanced TC treatment enables cells to attach and grow better, optimizes the adhesion effect, and improves culture efficiency
- Easy to Observe: Made of high-quality polystyrene, high transparency, easy to observe the cell growth through the microscope
- Widespread Use:Irradiation Sterilized, non-pyrogenic, suitable for most cell culture and cell expansion experiments in laboratories and schools
- Culture care: Nutrient depletion, contamination, or gas and temperature conditions outside the required range could harm a culture. The available reporting does not give operating thresholds or failure-recovery procedures.
- Consistency: Living cultures can vary from preparation to preparation, making reproducibility and transfer of a result between units important questions.
- Lifetime and reliability: The coverage does not state how long a culture remains usable, its uptime, or whether learned behavior drifts over time.
- Scale and cost: More units mean more biological servicing and environmental control, not just more rack space. No full-system cost per useful result is reported.
- Workload fit: A platform useful for adaptive experiments may not suit databases, web hosting, graphics or routine machine-learning inference. No reliable throughput comparison is supplied.
These are evaluation questions, not proof that the system fails at them. To establish practical value, results would need to report reproducibility, culture longevity, latency, throughput, uptime, training time and full-facility energy use alongside the workload being tested.
Human neurons do not establish a human-like mind
The coverage describes the CL1 units as using human neurons, but it does not establish the cells’ provenance, the consent and governance arrangements, or whether the cultures can support consciousness. A culture of neurons connected to electronics is not, on that basis, a miniature person or a complete human brain; the reported game demonstrations do not show that the system is conscious or sentient.
As biological-computing systems develop, relevant questions include donor consent and cell provenance, oversight of experiments, welfare standards for living neural tissue, and limits for increasingly complex cultures. The available reporting does not provide enough information to make claims about Cortical Labs’ specific ethics procedures.
What would show that the technology is commercially useful?
The key test is not whether neurons can produce an interesting demonstration, but whether a defined task can be performed reliably and economically. A persuasive comparison would include independently reproducible results, full-system power, culture lifespan, labor and consumable costs, uptime, latency and throughput, measured against suitable conventional or neuromorphic alternatives. Those results would also need to show where the biological approach is useful rather than assuming it replaces general-purpose computing.
Biological computing and conventional computing are not automatically head-to-head substitutes: CPUs serve broad general-purpose workloads, while GPUs and AI accelerators are built for demanding parallel computation. Neuromorphic chips emulate aspects of neural processing in silicon without living cells; quantum computing targets a different set of problems. Which comparison matters depends on the task. The available coverage does not establish that the CL1 outperforms any of these alternatives on a standard benchmark.
What the daily fluid change tells us
The daily replacement is more than an unusual maintenance detail. It reveals the central engineering trade-off in computing with living neurons: the cells may offer a different way to process signals, but they must be kept alive under controlled conditions. Cortical Labs has reported demonstrations and commercial ambitions; the available reporting does not yet establish that its planned capacity, energy claims or game results translate into a dependable, broadly useful data-center service.
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