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Opening — When the Computer Becomes Alive
Imagine walking into a laboratory and seeing a small container filled with liquid. Inside that liquid are living neurons, the same kind of cells found in the human brain. They are not connected to a human body. They have no eyes, ears, hands, or feet. Yet scientists have connected these cells to electronic equipment and are using them to interact with video games.
In 2022, researchers demonstrated that living neurons could adapt their activity while interacting with a simplified version of Pong. Now a company called Frontier Computing reports that neurons have been trained to navigate Frogger, a game where the player must cross dangerous roads and avoid obstacles. The company reports reaching a peak success rate of 92 percent after one hour of training. That result still requires independent verification, but the underlying science is real.
And now comes the part that caught my attention. Frontier Computing has announced plans to build a system containing 500 million living neurons. Think about that number. Five hundred million living brain cells, grown outside the human body, connected to computers, and potentially used to process information.
But why?
We already have powerful computers. We have artificial intelligence, enormous data centers, and companies spending billions of dollars building faster processors. So why are scientists turning toward living biological material? What can these neurons potentially accomplish that conventional computers cannot?
And where are these cells coming from?
During our investigation, we encountered a mysterious name circulating online: Donor 11. Some discussions suggest a connection between an unidentified human donor and biological computing experiments. But we have not established that Donor 11 is an authenticated laboratory donor or that this person's cells were used in the Frogger experiment. That uncertainty raises a much larger question. When someone donates biological material for research, who controls what eventually happens to it?
Then we discovered something else. China is developing its own biological neural technologies. Researchers at Tianjin University have been experimenting with brain organoids connected to robotic systems. Meanwhile, researchers and companies in Australia and Singapore are developing biological computing infrastructure that allows living neurons to become part of an emerging commercial service.
And wherever we find a new industry, we should ask familiar questions. Who is financing it? Who owns the patents? Who controls the technology? Who stands to profit? And who is responsible if something goes wrong?
There is also a question we cannot ignore. These neurons are alive. They respond to electrical stimulation. They can change their behavior. But does that mean they think? Could they eventually become conscious? Could they suffer? Science has not established that these cultures possess conscious experience, and we must be careful not to confuse learning with awareness.
Tonight, we are not here to frighten anyone or declare that scientists are creating human beings in laboratories. We are here to examine what is actually happening, what researchers hope to accomplish, and what the evidence tells us.
Scripture teaches us to test all things and hold fast to what is good. That means neither rejecting scientific discovery out of fear nor accepting every technological advancement without examination.
Because the most important question tonight may not be whether humanity can build a computer from living neurons.
It may be whether humanity has developed the wisdom to understand what it is building, who will control it, and what responsibilities come with turning living cells into technology.
Investigation One — The Neurons Living in Liquid
Before we can understand why scientists want 500 million neurons, we need to understand what these cells actually are. Because when someone says they have grown a brain inside a laboratory, the image that comes to mind is often very different from what scientists have created.
A neuron is a specialized living cell that receives and transmits information. Inside our bodies, billions of neurons communicate through electrical and chemical signals. They help us move, remember, recognize patterns, and respond to the world around us. But a single neuron does not possess the abilities of an entire brain. Those abilities emerge from complicated networks of cells working together.
Scientists have discovered ways to grow neurons outside the body. Some come from animal tissue. Others are produced using human stem cells. Researchers can even take certain adult human cells, reprogram them into a stem-cell-like state, and guide their development into neurons. This means the starting material does not necessarily have to come from someone's brain.
The neurons are placed in carefully controlled laboratory environments. They may grow on flat surfaces or form three-dimensional structures called organoids. These cultures are surrounded by liquid containing nutrients necessary for survival. Scientists must regulate temperature, oxygen, acidity, and waste. Without proper conditions, the cells become unhealthy and eventually die.
Now imagine placing those neurons onto a specialized electronic device containing tiny electrodes. These electrodes can detect electrical activity produced by the cells. They can also deliver controlled electrical stimulation. A computer translates information into signals that the neurons receive, then measures how the neurons respond.
This creates a communication pathway between living biology and conventional electronics.
But here is something important. The neurons do not see a computer screen. They do not recognize a keyboard or understand that someone has started a video game. Researchers must translate information from the outside world into patterns of electrical stimulation. They must also interpret the resulting neural activity and decide how those signals affect the computer.
In other words, the entire system depends upon both living cells and human-designed software.
Our neuroscience books explain another important fact. Neurons change through experience. Connections between cells can strengthen or weaken. Their electrical activity can become organized differently after repeated stimulation. Scientists call some of these changes neural plasticity, and they are fundamental to how biological nervous systems learn.
However, changing electrical activity does not automatically mean a culture is thinking, remembering like a person, or experiencing consciousness. Those are separate questions requiring additional evidence.
And there is another problem. Living neurons are not manufactured like silicon chips. They grow, mature, change, and die. Two cultures containing the same number of neurons may behave differently. Maintaining stable performance over months or years presents enormous engineering challenges.
This brings us back to the liquid.
That liquid is not merely something holding the neurons in place. It is part of the life-support system that makes biological computing possible. Without nutrients, oxygen, waste removal, and environmental control, there is no functioning biological computer.
So when companies discuss building machines containing hundreds of millions of living neurons, they are proposing much more than a new processor. They are proposing infrastructure capable of sustaining and communicating with enormous networks of living cells.
And that raises our first important question.
If the computer depends upon keeping biological material alive, should we evaluate it only as a machine, or must we also consider our responsibilities toward the living material inside it?
Investigation Two — Teaching Brain Cells to Play Video Games
Now that we understand how scientists keep neurons alive and connect them to computers, we need to examine something remarkable. Researchers have discovered that living neural networks can change their behavior when interacting with a computer-generated environment. But what does it actually mean to teach brain cells to play a video game?
In 2022, researchers working with Cortical Labs published an experiment called DishBrain. They grew human-derived and mouse neurons on a specialized electronic surface containing thousands of tiny electrodes. These electrodes allowed a computer to send electrical signals into the neural culture and record the resulting activity.
The researchers connected this system to a simplified version of Pong. When the virtual ball moved across the screen, the computer translated its position into electrical stimulation. The neurons responded with their own electrical activity, which the computer interpreted as commands controlling the paddle.
The neurons never saw a ball. They never held a controller. Everything they experienced came through electrical stimulation designed by the researchers.
What made the experiment interesting was the feedback. When the paddle successfully intercepted the ball, the system delivered a predictable pattern of stimulation. When it missed, the feedback became less predictable. The researchers wanted to determine whether the neural network would adapt its activity in ways that improved performance.
They reported learning-like changes within minutes. The experiment included comparisons intended to determine whether the observed behavior differed from random or uncontrolled activity.
But we need to be careful. The researchers did not demonstrate that the neurons understood Pong. They demonstrated that biological neural activity could adapt within a structured feedback environment. That distinction matters because learning, intelligence, and consciousness are not interchangeable.
Now consider Frontier Computing and Frogger.
Frontier reports that its biological neural system learned to navigate a Frogger-style game, achieving a peak crossing success rate of 92 percent across 25 games after approximately one hour of training. The company presents this as evidence that living neurons can adapt to a more complicated interactive environment.
However, we must examine what that number actually means. Twenty-five games represent a limited sample. A peak performance result does not necessarily represent average performance across repeated experiments. We also need to know how many cultures were tested, how the game information was encoded, what software assisted the system, and whether independent researchers reproduced the findings.
Without those details, we cannot responsibly conclude that the neurons independently mastered Frogger.
Our book *Theoretical Neuroscience* helps explain why this distinction is important. Neural networks can change their activity through repeated stimulation, but demonstrating meaningful learning requires careful measurement and comparison against appropriate controls.
There is another interesting possibility. Living neural networks may adapt using mechanisms different from those employed by conventional artificial intelligence. Instead of adjusting numerical parameters inside a computer model, biological neurons alter their electrical activity and cellular connections.
That could eventually become useful for certain computing problems. But usefulness must be demonstrated, not assumed.
So what have we actually discovered?
Scientists have demonstrated that living neurons can participate in computer-controlled environments and exhibit learning-like adaptation. Companies are now attempting to develop that capability into commercial technology.
But playing Pong or Frogger does not prove that a dish of neurons possesses a mind.
And that leads us to the next investigation. If these neurons are derived from human biological material, whose cells are they, and what did the original donor agree to?
Investigation Three — Donor 11: Whose Brain Cells Are These?
We have established that scientists can grow living neurons outside the human body and connect them to computers. But there is a question that deserves just as much attention as the technology itself. Where did those cells come from, and who has the right to decide what happens to them?
During our research, we encountered a name circulating online: Donor 11. The name has attracted attention because people want to know whether an identifiable human being supplied the biological material used in these experiments. But our investigation uncovered an important problem. We have not authenticated Donor 11 as an official laboratory identifier or established a connection to Frontier Computing's Frogger experiment.
That does not make the questions surrounding human donors any less important. It means we must separate a mysterious internet story from the documented practices of biological research.
Scientists can produce neurons by collecting certain adult human cells, such as blood or skin cells, and reprogramming them into induced pluripotent stem cells. These cells can then be guided into becoming neurons. Under appropriate laboratory conditions, researchers may maintain and reproduce these cell lines for extended periods.
Think about what that means. Someone could donate a biological sample for research, and cells derived from that sample might eventually be used in experiments that did not exist when the original donation occurred.
This brings us to a remarkable historical comparison.
In 1951, doctors collected cancer cells from a woman named Henrietta Lacks without obtaining her informed consent. Those cells became the famous HeLa cell line, which contributed to decades of medical research. Rebecca Skloot documented this history in *The Immortal Life of Henrietta Lacks*, including the consequences for Henrietta's family.
The comparison does not mean today's biological computing companies have committed the same wrongdoing. It demonstrates why consent, transparency, and commercial ownership deserve careful examination.
When someone donates cells, what exactly are they agreeing to? Are they consenting to medical research, commercial product development, or the creation of living neural computing systems? Can the resulting cell line be patented or licensed? Does the donor retain any rights to profits generated from discoveries involving those cells?
The answers depend on the circumstances, agreements, and applicable laws. There is no universal rule guaranteeing that donors receive compensation whenever their biological material becomes commercially valuable.
Our books on brain organoid ethics raise another concern. Donors may understand that their cells will be used for medical research without anticipating that those cells could eventually become components of a computer.
And we must distinguish ownership of a donated sample from ownership of inventions developed using that sample. Those are different legal questions.
Now return to Donor 11. Rather than inventing an identity, we should ask companies to document their cell sources, consent procedures, and policies governing future commercial applications.
Because the important issue is not whether we can uncover someone's private identity. It is whether people who donate biological material receive meaningful information about how that material may be used.
Scripture reminds us in Proverbs 11:1 that dishonest scales are an abomination to the Lord. The principle is fairness, including in transactions where one party possesses far more knowledge than another.
If living human-derived cells become valuable computing resources, we should examine whether the people supplying the original biological material are being treated fairly.
And that leaves us with a question.
When human cells become commercial technology, does the original donor remain a person whose interests matter, or become merely the source of a product someone else owns?
Investigation Four — Why Do They Want 500 Million Neurons?
Now we arrive at one of the most important questions in this investigation. Why would a company want to grow 500 million living neurons? What happens when scientists move from thousands of cells to millions, and eventually hundreds of millions? Is there something special about that number, or are we witnessing an attempt to build an entirely new kind of computing infrastructure?
Frontier Computing has announced an ambition to develop a biological computing system containing 500 million neurons. The company believes that living neural networks could eventually perform certain computational tasks more efficiently than conventional artificial intelligence. But there is an enormous difference between growing neurons and building a reliable computer from them.
Our neuroscience books explain that neurons do not become intelligent simply because more of them are placed together. The human brain contains approximately 86 billion neurons, but those cells are organized into extraordinarily complicated networks. Different regions perform different functions, and the connections between them develop through biological processes that scientists cannot simply reproduce by increasing cell counts.
Consider what happens when a neural culture becomes larger. Cells near the surface may receive sufficient oxygen and nutrients, while cells deeper inside struggle to survive. Waste products accumulate. Electrical communication becomes harder to measure. Some neurons form useful connections, while others may produce activity that contributes little to the intended task.
Frontier identifies oxygen delivery as one of the major obstacles it hopes to overcome. That is significant because maintaining large volumes of living neural tissue requires more than a container of nutrient liquid. It requires an environment capable of supporting the cells throughout their development and operation.
But even if researchers successfully grow 500 million healthy neurons, another problem remains. How will they communicate with them?
A conventional processor contains engineered circuits with predictable connections. Living neurons develop connections through biological processes. Researchers can influence their activity, but they cannot assume that every neuron will participate in useful computation.
The challenge is therefore not merely producing 500 million cells. It is creating a functioning network that can receive information, process it, produce measurable results, and repeat those results reliably.
And here is something we should examine carefully. There is no established scientific threshold at 500 million neurons where consciousness suddenly appears. Nor is there evidence that a culture containing that number automatically becomes capable of human reasoning.
So why announce such an ambitious target?
One possible explanation is engineering. Larger networks might eventually support more complicated information processing. Another is commercial positioning. Companies developing emerging technologies frequently announce milestones to attract investment, demonstrate progress, and establish themselves ahead of competitors.
Those explanations are not mutually exclusive. A legitimate scientific objective can also serve a commercial purpose.
But we should measure progress by demonstrated capabilities, not impressive numbers.
Can the system learn tasks that smaller cultures cannot? Does it retain information? Can it operate reliably for months? How much electricity and maintenance does it require? And can it outperform conventional technology on a comparable task?
Until those questions are answered, 500 million neurons remains an announced objective rather than proof of a revolutionary computer.
And perhaps that is the lesson.
We should not confuse the size of a biological system with the intelligence of that system, any more than we should confuse the size of a corporation with the wisdom of its leadership.
The real breakthrough will not be reaching 500 million living neurons.
It will be demonstrating what those neurons can actually do.
Investigation Five — The Companies Turning Living Cells Into Computers
Now that we understand why scientists want to grow hundreds of millions of neurons, we need to examine the companies attempting to turn this research into an industry. Because there is a difference between discovering something in a laboratory and building a business around it. And that difference usually involves investors, patents, customers, and ownership.
Let's begin with Frontier Computing, the company behind the reported Frogger experiment. Frontier has announced a ten-million-dollar pre-seed financing round led by General Catalyst. Its ambition is to develop large networks of living neurons that can eventually become useful computing systems. The company is not simply interested in demonstrating that neurons can respond to a video game. It wants to make biological computation commercially accessible.
But Frontier is not alone.
In Australia, Cortical Labs has developed a biological computing device called CL1. The company previously participated in the DishBrain experiment, where living neurons interacted with Pong. CL1 combines neural cultures, electronic interfaces, and life-support equipment into a system designed for biological computing research.
What makes Cortical Labs particularly interesting is its commercial approach. Rather than requiring every researcher to establish a specialized cell laboratory, the company wants customers to access biological computing through standardized equipment and remote services.
Now consider FinalSpark, a Swiss company developing what it calls the Neuroplatform. Its researchers have worked with living brain organoids connected to electronic systems. The platform allows approved researchers to conduct experiments remotely, sending stimulation commands and recording neural responses.
Think about what these businesses are attempting. They are developing a model in which customers may pay to access living neural tissue as a computing resource.
That brings us to Singapore.
In August 2026, the National University of Singapore announced a biological data center prototype developed with DayOne and Cortical Labs. The installation contains twenty CL1 units, with plans being explored for a much larger deployment.
This is an important distinction. We are no longer discussing only individual experiments performed inside university laboratories. We are seeing efforts to organize biological computing equipment into shared infrastructure.
But we must examine what customers are actually purchasing. These systems are not demonstrated replacements for ordinary cloud computers. Their present applications remain heavily focused on research, experimentation, and developing methods for interacting with living neural networks.
And unlike silicon processors, biological systems require constant care. Neurons need nutrients, stable temperatures, controlled environments, and protection from contamination. They mature, change their electrical behavior, and eventually die.
FinalSpark's published research describes improvements in organoid survival, with some cultures maintained for approximately one hundred days. That is progress, but it also reveals a commercial challenge. A customer purchasing computing services expects reliability. What happens when the biological processor changes or must be replaced?
Another issue is ownership. Companies may control the hardware, software, training methods, and cell lines used within their systems. Customers might receive access without owning any part of the underlying biological infrastructure.
That business model resembles conventional cloud computing, but with an unusual difference. The processing material is alive.
So we should ask who controls the biological supply chain, who receives the investment money, and who owns the resulting inventions.
We should also ask whether these companies are selling demonstrated computing advantages or financing the possibility of future breakthroughs.
Because the emerging business opportunity may not depend upon creating a conscious artificial brain.
It may depend upon convincing customers that living neurons can become a valuable service.
And once biological computing becomes a commercial service, the next question is unavoidable.
Which countries intend to control that industry?
Investigation Six — China and the International Biological Computing Race
Now we need to look beyond the United States and Europe, because biological computing is not being developed in isolation. China is conducting its own research into living neural systems, brain organoids, and machines that imitate biological intelligence. And understanding what China is actually building may tell us where this technology is heading.
In 2024, researchers associated with Tianjin University introduced a system called MetaBOC. It combines laboratory-grown brain organoids with electronic interfaces designed to communicate with robotic systems. The objective is to explore whether living neural tissue can participate in controlling machines through electrical stimulation and feedback.
Think about the difference between this and Frogger. In one experiment, neurons interact with a computer-generated environment. In the other, researchers are investigating how biological neural activity can influence physical robotic behavior.
But China did not begin this work in 2024.
Tianjin University documents a government-funded research program beginning in 2021, with a reported budget of approximately 27.45 million yuan. Its work includes engineered brain-like systems, neural interfaces, and methods for training biological networks. University records also identify a subsequent research program extending from 2026 through 2030.
This demonstrates organized, continuing investment rather than a single publicity experiment.
China is also developing powerful brain-inspired computers. Zhejiang University's Darwin Monkey system was announced as capable of simulating more than two billion neurons. But we must make an important distinction. Those are artificial neurons represented electronically, not billions of living cells floating in liquid.
Confusing the two technologies would give our audience a false understanding of China's progress.
Now consider the larger international picture.
Australia's Cortical Labs has developed biological computing hardware. Switzerland's FinalSpark provides remote access to neural cultures. Frontier Computing is pursuing larger biological networks. And Singapore has established a research-scale biological data center prototype involving Cortical Labs, DayOne, and the National University of Singapore.
We should also examine the commercial relationships surrounding these projects. International partnerships can provide financing, research expertise, manufacturing capabilities, and access to markets. But a company's business relationships do not automatically prove that a foreign government controls its technology.
What about military applications?
Any technology that improves autonomous systems, adaptive control, or information processing could potentially attract defense interest. China, like other major powers, invests in technologies with possible civilian and military applications.
However, we have not established that China's MetaBOC system is a military weapon or that the People's Liberation Army operates a functioning biological data center. Those claims would require evidence beyond the existence of government-funded research.
And here is another question worth considering. Why would governments invest in biological computing when conventional artificial intelligence is advancing so rapidly?
One possible answer is strategic independence. Countries that develop new computing methods may reduce reliance on technologies controlled by foreign companies. Another possibility is that biological systems could eventually perform specialized tasks more efficiently.
Neither outcome is guaranteed.
The international competition is therefore about more than who can grow the largest collection of neurons. It involves patents, scientific expertise, research infrastructure, commercial applications, and potentially future technological independence.
We should also recognize that international scientific collaboration can advance medicine and neuroscience, not merely national competition.
So what does the evidence tell us?
China has a documented biological neural research program. Other countries are developing commercial platforms and infrastructure. But we have not demonstrated that any nation has achieved a decisive advantage in large-scale living-neuron computing.
And that brings us to the next investigation.
If governments, universities, and private companies are all investing in this technology, who is financing the race, and who stands to own the results?
Investigation Seven — Follow the Money: Who Owns Living Intelligence?
We have examined the science, the companies, and the international competition. Now we need to ask a question that often reveals why new technologies develop in particular directions. Who is paying for biological computing, and what do they expect to receive in return?
Frontier Computing has announced ten million dollars in pre-seed financing, led by the investment firm General Catalyst. Other reported investors include LocalGlobe, Amino Collective, Kaya, Long Journey, Off Piste, and SVA.
Why would investors place millions of dollars into technology that has not yet demonstrated it can replace conventional computers?
Because investors do not necessarily purchase what a company can accomplish today. They purchase an ownership interest in what they believe that company might become tomorrow.
If biological computing eventually develops into a profitable industry, early investors could benefit from the company's increased value. They might profit through future investment rounds, acquisitions, or an eventual public offering.
But that outcome is uncertain. Many promising technologies never become profitable businesses.
Now consider what these companies might eventually own.
They can develop patents covering electronic interfaces, methods for maintaining neural cultures, techniques for stimulating cells, and systems for interpreting biological signals. They may also control proprietary software, manufacturing processes, and contracts providing customers access to their equipment.
Notice something important. A company does not have to own the concept of a neuron to control valuable parts of biological computing. It may only need ownership of the technology required to use neurons commercially.
This is where the business model becomes interesting.
Imagine a university that wants to experiment with living neural networks but cannot afford to build an entire laboratory. Instead, it rents access to a company's biological computing platform. The university conducts experiments, while the provider maintains the cells, equipment, and software.
That arrangement could make research more accessible. But it could also create dependence upon a small number of commercial providers.
Who owns the data generated during those experiments? Who controls the underlying cell lines? Can the provider reuse discoveries to improve its products? And who receives the intellectual property rights when researchers develop something valuable?
Those questions depend upon contracts and applicable laws. We should not assume every company uses the same terms.
There is also public money to consider.
Universities conducting biological computing research may receive government grants, public research funding, and institutional support. China has documented state-supported research programs. In other countries, public institutions are also participating in developing the science.
This creates another question. When taxpayers help finance foundational research, how much of the eventual economic benefit should return to the public?
We have seen similar debates surrounding pharmaceuticals, telecommunications, and conventional computing.
But we must avoid jumping to conclusions. Investment does not prove corruption. Patents do not automatically establish monopoly control. And government funding does not prove a secret military program.
What these financial relationships establish is something simpler. Biological computing is becoming an economic activity with identifiable interests, incentives, and potential beneficiaries.
And those incentives deserve examination before the industry becomes too established to question.
Proverbs 22:7 reminds us that financial dependence can create relationships of power. That principle should encourage us to examine who controls essential infrastructure and who depends upon it.
So perhaps the question is not merely whether scientists can make living neurons compute.
It is whether the next generation of computing will become another system where a small number of institutions own the infrastructure while everyone else pays for access.
And that brings us to the biological data center itself. Can living cells really compete with the machines we already have?
Investigation Eight — The Biological Data Center: Replacing Silicon With Life?
Now we arrive at a development that could change how people understand biological computing. Researchers are no longer discussing only small experiments in laboratories. They are beginning to organize living neural systems into something resembling a data center.
In August 2026, the National University of Singapore announced a biological computing prototype developed with DayOne and Australia's Cortical Labs. The installation contains twenty CL1 units, with ambitions to expand the technology considerably.
But what exactly is a biological data center?
A conventional data center contains electronic processors, memory, storage equipment, networking systems, and cooling infrastructure. It processes information using silicon-based electronics. A biological computing facility introduces something different: living neurons connected to electronic systems that allow researchers to stimulate and measure their activity.
The attraction is understandable. The human brain performs extraordinarily complicated tasks while consuming roughly twenty watts of power. Modern artificial intelligence systems can require enormous amounts of electricity, particularly when operating across large computing facilities.
So companies are asking whether biological neurons might eventually process certain kinds of information more efficiently.
Cortical Labs has described its CL1 system as operating at approximately thirty watts per unit. That sounds impressive, but we must be careful about what we are comparing.
Thirty watts for a biological computing device is not the same as thirty watts for an entire functioning data center. The cells require environmental control, nutrients, monitoring, and supporting equipment. A fair comparison must include the electricity consumed by the complete system.
And there is another problem. Energy efficiency means very little unless we compare the same computational task.
Imagine two machines. One uses thirty watts but performs a limited experiment. Another uses three hundred watts but completes millions of useful calculations. We cannot declare the first machine superior merely because its electrical consumption is lower.
We must measure useful work performed per unit of energy.
That brings us to reliability.
Conventional processors can operate for years. Living neural cultures change as they mature. They can become contaminated, lose viability, or develop different electrical responses over time. Researchers must continually monitor their condition.
What happens when a biological processor begins behaving differently after several weeks? Can its performance be restored? Must the cells be replaced? And can a customer expect identical results from one biological unit to another?
These are not minor details. They determine whether biological computing can become dependable infrastructure.
We should also examine the proposed expansion in Singapore. Plans involving hundreds or even a thousand biological computing units demonstrate commercial ambition. They do not establish that those units are already operating or delivering computing performance comparable to conventional data centers.
The distinction matters because announcements often describe what companies hope to build rather than what they have demonstrated.
Still, we should not dismiss the research. Biological computing might eventually prove useful for studying neurological diseases, testing medicines, examining neural learning, or solving specialized problems that benefit from biological adaptation.
Those applications could be valuable even if living neurons never replace silicon processors.
And perhaps that is the more realistic possibility. Instead of replacing conventional computers, biological systems may become specialized tools operating alongside them.
But there is a larger question.
If companies eventually operate thousands of living neural cultures as commercial computing resources, what responsibilities will they have toward the biological material inside those machines?
Because the more successfully we make living cells perform useful work, the more urgently we must ask whether those cells can experience anything at all.
And that is where our next investigation begins.
Investigation Nine — Can Living Computers Think, Remember, or Suffer?
We have examined the technology, the companies, the investors, and the international competition. But now we arrive at a question that may be more important than everything we have discussed. If scientists can grow living neurons and train them to respond to information, could those neurons eventually become conscious?
To answer that question, we must first understand that consciousness and intelligence are not the same thing.
A computer can recognize faces, translate languages, and defeat human champions at complicated games. But performing those tasks does not establish that the computer experiences anything. Likewise, a network of living neurons may change its behavior through electrical stimulation without necessarily possessing awareness.
Christof Koch explores this distinction in *The Feeling of Life Itself*. He examines consciousness as subjective experience, the difference between processing information and actually feeling something. Anil Seth, in *Being You*, examines how conscious experience relates to the brain's interpretation of the body and surrounding world.
Mark Solms, in *The Hidden Spring*, places particular importance on feeling, biological needs, and the systems that regulate an organism's survival.
These researchers do not agree on every explanation of consciousness. And that disagreement matters because scientists have not established a universally accepted test for determining whether an isolated neural culture possesses subjective experience.
Now return to DishBrain and Frogger.
Researchers observed changes in neural activity associated with feedback and task performance. Those findings are interesting, but they do not demonstrate that the neurons understood the games, experienced frustration when they failed, or felt satisfaction when they succeeded.
A learning response is not proof of a conscious experience.
But here is where the ethical question becomes difficult.
If we cannot confidently determine whether a sufficiently complex biological system has subjective experience, how should researchers approach the possibility?
Some scientists argue that present neural cultures lack the organized structures, sensory systems, and biological integration associated with human consciousness. Others believe that increasing complexity requires continued ethical examination, even without evidence that consciousness has emerged.
Neither position justifies announcing that laboratory-grown neurons are suffering. Nor does uncertainty justify abandoning the question altogether.
Consider how we approach animal research. Scientists do not wait for animals to explain their experiences in human language before establishing welfare protections. Instead, they examine biological evidence, behavior, and the possibility of harm.
That does not mean a dish of neurons should automatically receive the same protections as an animal or human being. It means researchers should establish appropriate safeguards as the technology develops.
And those safeguards might include independent ethical review, transparent reporting, limits on experiments that raise credible welfare concerns, and continued research into possible indicators of conscious experience.
There is also a theological question.
Genesis teaches that human beings are created in the image of God. But Scripture does not tell us that every collection of human-derived cells possesses the identity or consciousness of a human person.
We should therefore be careful not to declare that scientists have created a human soul inside a machine. That would go beyond both the scientific evidence and what Scripture explicitly establishes.
At the same time, our ability to manipulate living material does not free us from moral responsibility.
First Corinthians 10:23 reminds us that not everything permissible is necessarily beneficial.
So perhaps our responsibility is to ask difficult questions before commercial success makes those questions inconvenient.
Can these cultures remember? In limited biological ways, they may retain changes associated with previous stimulation. Can they think like human beings? That has not been demonstrated. Can they suffer? We currently have no reliable evidence that these cultures experience suffering.
But the final question remains.
If biological computing becomes increasingly complex, who will decide when ethical protections are necessary, and will those decisions be made by independent scientists or by the companies profiting from the technology?
Investigation Ten — What Happens When Life Becomes Technology?
We began tonight with living neurons playing video games. We followed those cells into laboratories, commercial computing platforms, international research programs, and the financial institutions investing in their development. Now we need to ask the question that brings everything together. What happens when human beings begin treating living biological material as technology?
There is nothing inherently wrong with scientific discovery. Medical research involving living cells has helped humanity understand diseases, develop treatments, and save lives. The ability to grow neurons outside the body could lead to important breakthroughs in understanding conditions that affect the human nervous system.
But biological computing introduces another purpose. Instead of studying neurons only to understand or heal the human body, researchers are attempting to use those neurons to perform computational work.
That changes the questions we must ask.
First, where do the cells come from? We examined how human-derived cells can be reprogrammed into neurons. We also discovered that the online story surrounding Donor 11 remains unverified. But the larger issue is real. Donors deserve meaningful information about how their biological material may eventually be used.
Second, who owns the technology? Companies are developing equipment, software, cell-culture methods, and intellectual property. Those inventions may become valuable. But ownership also creates power, particularly when researchers and customers depend upon a small number of providers.
Third, who establishes the rules?
Biological computing operates at the intersection of several existing fields, including stem-cell research, human tissue donation, neuroscience, and computing. Ethical guidance already exists for parts of this work, but commercial biological computing raises questions that may not fit neatly into traditional categories.
Governments, universities, independent researchers, and the public should participate in determining appropriate safeguards. We should not assume that companies can adequately regulate themselves simply because they understand their technology.
Fourth, what happens if the science advances beyond our ability to understand its consequences?
Today, we have no reliable evidence that the neural cultures used in these computing experiments possess consciousness or experience suffering. But researchers are attempting to create larger and more complicated biological networks. Ethical oversight should develop alongside those capabilities rather than waiting for a crisis.
Now consider what Scripture teaches.
Genesis describes humanity receiving responsibility for creation. That responsibility is not permission to act without wisdom. Psalm 139 reminds us that human life deserves reverence. And Proverbs 14:15 warns that the simple believe everything, while the prudent examine their steps.
Those principles apply in both directions.
We should not believe every frightening story about scientists growing conscious human brains. But neither should we accept every corporate announcement as proof that the future will be better.
First Thessalonians 5:21 tells us to test all things and hold fast to what is good.
That is our responsibility here.
We must distinguish what researchers have demonstrated from what companies hope to accomplish. We must separate genuine medical possibilities from investment promises. And we must examine whether the people providing biological material, financing research, and using these technologies are being treated fairly.
Perhaps biological computing will eventually transform medicine. Perhaps it will develop into a specialized computing industry. Or perhaps its practical limitations will prevent it from becoming commercially competitive.
We do not yet know.
But we know something else. The decisions made during the early development of a technology can shape who controls it for generations.
And that is why these questions matter now, before living neural systems become ordinary commercial products.
Because humanity's greatest challenge may not be learning how to make living cells perform calculations.
It may be learning how to exercise wisdom, restraint, and responsibility when those calculations become profitable.
Conclusion — We Have Learned to Make Life Compute. Have We Learned to Be Responsible for It?
Tonight, we began with something that sounded almost impossible. Living neurons, growing in liquid, connected to computers and responding to video games. What began with Pong has now advanced to company-reported experiments involving Frogger, and researchers are discussing biological computing systems containing hundreds of millions of neurons.
But after examining the evidence, I believe the most important discovery was not what these cells could do. It was how quickly human beings are preparing to turn them into an industry.
We found scientists exploring the remarkable ability of neurons to adapt to electrical stimulation. We found companies developing machines that keep those cells alive while connecting them to electronic systems. We found investors placing millions of dollars into businesses that hope biological computing will become commercially valuable.
And we found that this research is not limited to one country.
Australia, Switzerland, Singapore, the United Kingdom, and China are all participating in different aspects of this emerging field. Some researchers are studying biological learning. Others are developing robotic interfaces, computing platforms, and infrastructure intended to support larger neural networks.
But we also discovered something important. Much of what is being promised remains unproven.
A culture of neurons responding to a video game is not evidence that scientists have created a conscious human mind. Five hundred million neurons do not automatically produce intelligence. And a biological computer consuming relatively little electricity does not establish that it can outperform a conventional processor.
Those distinctions matter because impressive announcements can create excitement long before the underlying technology fulfills its promises.
We also examined Donor 11. We could not establish that this online name identifies an authenticated donor connected to the Frogger experiment. But investigating that claim brought us to a question we should not ignore.
When someone donates biological material, how much control should that person retain over its future use?
The history of Henrietta Lacks reminds us that scientific advancement and ethical treatment do not always develop at the same pace. We should learn from that history rather than wait for another controversy.
And then there is the question of consciousness.
We have no reliable evidence that today's biological computing cultures experience suffering or possess humanlike awareness. But that does not mean we should abandon ethical oversight as researchers attempt to build increasingly complex systems.
Now I want to bring this back to something larger.
Throughout history, humanity has repeatedly discovered how to do things before fully considering whether those things should be done, how they should be governed, or who might be harmed.
That does not mean discovery itself is evil. It means knowledge and wisdom are not the same thing.
Proverbs 4:7 tells us that wisdom is the principal thing. And First Thessalonians 5:21 instructs us to test all things and hold fast to what is good.
That is what we attempted tonight.
We did not declare biological computing a miracle. We did not declare it an abomination. We examined the evidence, questioned the promises, followed the money, and considered the responsibilities that accompany scientific progress.
And perhaps that is where we should leave this investigation.
The question is not simply whether living neurons will someday replace silicon chips. They may never do so.
The question is whether the people developing, financing, and controlling this technology will place human responsibility ahead of commercial ambition.
Because learning how to make living cells compute may prove to be an extraordinary scientific achievement.
But learning when to exercise restraint, how to protect others, and how to use that knowledge wisely may prove to be the greater achievement.
And that is the cause we must examine before the symptoms appear.
Bibliography
- Abbott, L. F., and Peter Dayan. Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems. Cambridge, MA: MIT Press, 2001.
- Cortical Labs. CL1: Biological Computing Platform. Company technical documentation and product materials. https://corticallabs.com.
- Dederer, Hans-Georg, and Dieter Hamburger, eds. Brain Organoids in Research and Therapy: Fundamental Ethical and Legal Aspects.
- FinalSpark. Neuroplatform: Remote Access to Biological Neural Networks. Research platform documentation. https://finalspark.com.
- Frontier Computing. Company announcements and research materials concerning living-neuron computing, Frogger experiments, financing, and proposed large-scale neural systems.
- General Catalyst. Investment announcements and company information concerning Frontier Computing. https://www.generalcatalyst.com.
- International Society for Stem Cell Research. ISSCR Guidelines for Stem Cell Research and Clinical Translation. 2021, with subsequent updates. https://www.isscr.org/guidelines.
- Kagan, Brett J., et al. “In Vitro Neurons Learn and Exhibit Sentience When Embodied in a Simulated Game-World.” Neuron 110, no. 23 (2022): 3952–3969.e8. https://doi.org/10.1016/j.neuron.2022.09.001.
- Kandel, Eric R., James H. Schwartz, Thomas M. Jessell, Steven A. Siegelbaum, and A. J. Hudspeth, eds. Principles of Neural Science. 5th ed. New York: McGraw-Hill, 2013.
- Koch, Christof. The Feeling of Life Itself: Why Consciousness Is Widespread but Can't Be Computed. Cambridge, MA: MIT Press, 2019.
- Levitan, Irwin B., and Leonard K. Kaczmarek. The Neuron: Cell and Molecular Biology. 3rd ed. New York: Oxford University Press, 2002.
- National Academies of Sciences, Engineering, and Medicine. The Emerging Field of Human Neural Organoids, Transplants, and Chimeras: Science, Ethics, and Governance. Washington, DC: National Academies Press, 2021. https://doi.org/10.17226/26078.
- National University of Singapore, Yong Loo Lin School of Medicine. Institutional announcements concerning biological computing research and collaboration with Cortical Labs and DayOne, 2026.
- Seth, Anil. Being You: A New Science of Consciousness. New York: Dutton, 2021.
- Skloot, Rebecca. The Immortal Life of Henrietta Lacks. New York: Crown, 2010.
- Solms, Mark. The Hidden Spring: A Journey to the Source of Consciousness. New York: W. W. Norton, 2021.
- Tianjin University. Research announcements and institutional materials concerning MetaBOC, brain organoids, and brain-computer interface technologies, 2021–2026.
- Zhejiang University. Institutional research announcements concerning the Darwin series of brain-inspired computers and the Darwin Monkey neuromorphic system.
- The Holy Bible. King James Version. Genesis 1–2; Psalm 139; Proverbs 4:7, 11:1, 14:15, 22:7; 1 Corinthians 10:23; 1 Thessalonians 5:21.
Endnotes
- Irwin B. Levitan and Leonard K. Kaczmarek, The Neuron: Cell and Molecular Biology, 3rd ed. (New York: Oxford University Press, 2002). Explains neuronal structure, electrical signaling, synaptic communication, and the biological requirements of living nerve cells.
- Eric R. Kandel et al., eds., Principles of Neural Science, 5th ed. (New York: McGraw-Hill, 2013). Provides foundational explanations of neural plasticity, learning, memory, and the organization of nervous systems.
- Peter Dayan and L. F. Abbott, Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems (Cambridge, MA: MIT Press, 2001). Examines neural computation, learning mechanisms, and the mathematical interpretation of neural activity.
- Brett J. Kagan et al., “In Vitro Neurons Learn and Exhibit Sentience When Embodied in a Simulated Game-World,” Neuron 110, no. 23 (2022): 3952–3969.e8. https://doi.org/10.1016/j.neuron.2022.09.001. Documents the DishBrain experiment involving living neurons interacting with a simplified version of Pong. The paper's use of the term “sentience” should not be treated as scientific proof of subjective consciousness.
- Cortical Labs, company research and technical materials, https://corticallabs.com. Describes the CL1 biological computing platform, its electronic interfaces, and its intended research and commercial applications. Technical and performance claims originating from the company require independent evaluation.
- Frontier Computing, company announcements concerning its Frogger experiment. The reported peak success rate of 92 percent across 25 games after approximately one hour of training is a company-reported result, not an independently established measure of general intelligence.
- Frontier Computing, announcements concerning its proposed 500-million-neuron biological computing system. The announced cell count represents a development objective, not proof that a functioning system of that scale has been completed.
- Rebecca Skloot, The Immortal Life of Henrietta Lacks (New York: Crown, 2010). Documents the collection and commercialization of HeLa cells and the historical questions surrounding informed consent, family interests, and ownership of human-derived biological material.
- International Society for Stem Cell Research, ISSCR Guidelines for Stem Cell Research and Clinical Translation(2021), https://www.isscr.org/guidelines. Provides ethical guidance relevant to stem-cell research, human biological materials, and research involving increasingly complex neural models.
- The online designation “Donor 11” has not been authenticated in this investigation as an official donor identifier connected to Frontier Computing or its Frogger experiment. No conclusion about an individual's identity, consent, or participation should be drawn from the designation alone.
- FinalSpark, Neuroplatform research and technical documentation, https://finalspark.com. Describes remote experimental access to living neural cultures and efforts to maintain viable biological computing systems.
- National University of Singapore, Yong Loo Lin School of Medicine, institutional announcements concerning its 2026 biological computing collaboration with Cortical Labs and DayOne. The reported twenty-unit prototype must be distinguished from proposed future expansion.
- Tianjin University, institutional research announcements concerning MetaBOC and brain-organoid interfaces. These materials describe research into connecting living neural systems with electronic and robotic environments; they do not independently establish operational military applications.
- Zhejiang University, research announcements concerning the Darwin Monkey neuromorphic system. Its artificial neurons are implemented electronically and must not be confused with living biological neurons.
- Frontier Computing and General Catalyst, financing announcements concerning the company's reported $10 million pre-seed funding round. Investment establishes commercial interest but does not independently validate the technology's performance or future profitability.
- National Academies of Sciences, Engineering, and Medicine, The Emerging Field of Human Neural Organoids, Transplants, and Chimeras: Science, Ethics, and Governance (Washington, DC: National Academies Press, 2021). Examines scientific uncertainty and ethical oversight associated with human neural organoids.
- Christof Koch, The Feeling of Life Itself: Why Consciousness Is Widespread but Can't Be Computed (Cambridge, MA: MIT Press, 2019). Presents one influential theoretical approach to consciousness and subjective experience.
- Anil Seth, Being You: A New Science of Consciousness (New York: Dutton, 2021). Examines the relationship between conscious experience, biological regulation, and the brain's interpretation of the world.
- Mark Solms, The Hidden Spring: A Journey to the Source of Consciousness (New York: W. W. Norton, 2021). Explores the relationship between feeling, biological needs, and consciousness. Its theoretical conclusions should be distinguished from experimentally established findings about cultured neurons.
- The approximately twenty-watt energy consumption commonly attributed to the human brain is a physiological estimate, not a direct measure of the computational efficiency of isolated neurons. Comparisons with biological computing equipment must include supporting infrastructure and equivalent computational workloads.
- Genesis 1–2 and Psalm 139 provide the scriptural foundation for discussing creation, human dignity, and responsibility. Neither passage directly addresses laboratory-grown neural cultures or establishes their consciousness.
- Proverbs 11:1 and 22:7 address fairness and financial power. Their application to biological computing concerns ethical principles rather than specific biblical predictions about biotechnology.
- Proverbs 14:15 and 1 Thessalonians 5:21 support careful examination of claims and the testing of evidence. These passages inform the show's approach to distinguishing demonstrated science from speculation.
- First Corinthians 10:23 distinguishes what is permissible from what is beneficial. The passage provides a framework for considering whether technological capability alone establishes the wisdom of a particular application.
- The central scientific distinction throughout this investigation is between measurable neural adaptation, demonstrated computational usefulness, and subjective conscious experience. Evidence for one does not automatically establish the others.
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