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Can brain cells run computers? This startup powers data centre using human neurons | Euronews
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Summary
As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems. Cortical Labs has developed a system that combines lab-grown neurons with silicon hardware, allowing users to explore applications ranging from neuroscience and disease modelling to robotics and artificial intelligence (AI). Kagan, the chief scientific officer and chief operating officer at Cortical Labs, Euronews Next. “All you need is a little bit of blood or some skin, and you can generate an indefinite supply of these cells that you can then turn into neurons,” Kagan added. While the idea of growing neurons in the lab is not new, what Cortical Labs says it has done differently is to standardise a system that can be used more easily when connecting cell cultures to electronic interfaces, rather than requiring complex, custom-built lab setups.
## Summary
As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems. Cortical Labs has developed a system that combines lab-grown neurons with silicon hardware, allowing users to explore applications ranging from neuroscience and disease modelling to robotics and artificial intelligence (AI). Kagan, the chief scientific officer and chief operating officer at Cortical Labs, Euronews Next. “All you need is a little bit of blood or some skin, and you can generate an indefinite supply of these cells that you can then turn into neurons,” Kagan added. While the idea of growing neurons in the lab is not new, what Cortical Labs says it has done differently is to standardise a system that can be used more easily when connecting cell cultures to electronic interfaces, rather than requiring complex, custom-built lab setups.
## Article Content
By 
Roselyne Min
Published on
04/04/2026 - 7:01 GMT+2
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What previously required months or years of specialised lab work can now be done in hours or days thanks to its integrated platform.
As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems.
ADVERTISEMENT
ADVERTISEMENT
An Australian start-up says it has created the world’s first device that allows users to “run code” on living human brain cells.
Cortical Labs has developed a system that combines lab-grown neurons with silicon hardware, allowing users to explore applications ranging from neuroscience and disease modelling to robotics and artificial intelligence (AI).
The system, CL1, works by growing neurons from stem cells and placing them on chips that can send and receive electrical signals.
“We're using these cells more like an engineering approach to build something that's never really existed before and might have properties that we've never been able to use before. And so far, the results are very exciting,” Brett J. Kagan, the chief scientific officer and chief operating officer at Cortical Labs, Euronews Next.
“All you need is a little bit of blood or some skin, and you can generate an indefinite supply of these cells that you can then turn into neurons,” Kagan added.
The company says it is working on biological computing facilities in Melbourne and Singapore, where multiple units of its system could be deployed and accessed remotely.
Related
Parkinson’s patient moves freely again after world-first implant of lab-grown cells into his brain
How is it different from the conventional silicon chip?
CL1 allows users to interact directly with the neurons, sending electrical signals as inputs and interpreting how the cells respond in real time.
Similar to conventional computing systems, it uses silicon chips, but they are equipped with microelectrodes that communicate with living neurons, sending signals and reading their responses as part of the computation.
Unlike conventional silicon-based computers, the shoebox-sized system uses living cell cultures that require a nutrient-rich liquid to survive, an approach sometimes described as “wetware”.
Some 120 units of such a system are running a small data centre in Melbourne, Australia, Cortical Labs says.
While the idea of growing neurons in the lab is not new, what Cortical Labs says it has done differently is to standardise a system that can be used more easily when connecting cell cultures to electronic interfaces, rather than requiring complex, custom-built lab setups.
Related
These lab-grown hearts made from human stem cells are used to train AI to detect heart diseases
Efficiency found in human biology
What previously required months or years of specialised lab work can now be done in hours or days thanks to its integrated platform, the company says.
Interacting with biological neurons in this way could make computing more energy-efficient and adaptable than conventional systems.
“Biology is incredibly energy efficient. We [humans] don't require huge amounts of data. Kagan said.
“I have a small daughter, and for her to learn what a dog is, she just needs to see a couple of pictures of a dog. Machine learning needs to be tens of thousands, hundreds of thousands, depending on what the task is. We can also deal with uncertainty, with noisy information,” he added.
Using human-derived cells could also have research applications. Because the neurons are grown from donor samples, they may reflect genetic traits, allowing scientists to study how cells respond to different treatments in a lab setting.
That said, traditional silicon-based computers remain far more effective at precise, fast mathematical calculations, Kagan said. Advances in current AI systems may be reaching practical limits, as they require ever larger amounts of data and computing power.
Instead, future systems are likely to integrate biological and silicon-based approaches to achieve capabilities that neither could deliver alone, the co-founder said.
“The future of computing is when we can leverage all of the tools that we have available to get the best result”.
Some experts agree that biological systems offer advantages such as low energy use and adaptability, but question how far current approaches can go.
“If you are only using a flat network of human neurons, I do not believe it would have any major advantages compared to traditional silicon-based systems,” Alysson R. Muotri, the Director of Sanford Stem Cell Education and Integrated Space Stem Cell Orbital Research (ISSCOR) Center at University of California, San Diego, in the United States, told Euronews Next.
He said more complex, three-dimensional brain-like structures, known
---
## Expert Analysis
### Merits
- That said, traditional silicon-based computers remain far more effective at precise, fast mathematical calculations, Kagan said.
### Areas for Consideration
- Related Spanish doctors created an artificial womb to solve a major cause of miscarriage Ethical questions around biology in computing The use of human cells in computing raises ethical questions, although researchers say the level of concern depends on the complexity of the system.
- Go to accessibility shortcuts Share Comments Read more Tech News Europe's AI leader Mistral raises $830m for data centre near Paris Tech News Google sets 2029 deadline to prepare for quantum cyber threat Tech News Could data centres use human brain cells to process information? start-up brain Robotic Artificial intelligence BioNTech
### Implications
- As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems.
- The system, CL1, works by growing neurons from stem cells and placing them on chips that can send and receive electrical signals. “We're using these cells more like an engineering approach to build something that's never really existed before and might have properties that we've never been able to use before.
- The company says it is working on biological computing facilities in Melbourne and Singapore, where multiple units of its system could be deployed and accessed remotely.
- Interacting with biological neurons in this way could make computing more energy-efficient and adaptable than conventional systems. “Biology is incredibly energy efficient.
### Expert Commentary
This article covers cells, neurons, human topics. Notable strengths include discussion of cells. Areas of concern are also raised. Readability: Flesch-Kincaid grade 0.0. Word count: 997.
As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems. Cortical Labs has developed a system that combines lab-grown neurons with silicon hardware, allowing users to explore applications ranging from neuroscience and disease modelling to robotics and artificial intelligence (AI). Kagan, the chief scientific officer and chief operating officer at Cortical Labs, Euronews Next. “All you need is a little bit of blood or some skin, and you can generate an indefinite supply of these cells that you can then turn into neurons,” Kagan added. While the idea of growing neurons in the lab is not new, what Cortical Labs says it has done differently is to standardise a system that can be used more easily when connecting cell cultures to electronic interfaces, rather than requiring complex, custom-built lab setups.
## Article Content
By 
Roselyne Min
Published on
04/04/2026 - 7:01 GMT+2
Share
Comments
Share
Send
Messenger
Telegram
VK
Bluesky
Threads
Copy/paste the article video embed link below:
Copied
What previously required months or years of specialised lab work can now be done in hours or days thanks to its integrated platform.
As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems.
ADVERTISEMENT
ADVERTISEMENT
An Australian start-up says it has created the world’s first device that allows users to “run code” on living human brain cells.
Cortical Labs has developed a system that combines lab-grown neurons with silicon hardware, allowing users to explore applications ranging from neuroscience and disease modelling to robotics and artificial intelligence (AI).
The system, CL1, works by growing neurons from stem cells and placing them on chips that can send and receive electrical signals.
“We're using these cells more like an engineering approach to build something that's never really existed before and might have properties that we've never been able to use before. And so far, the results are very exciting,” Brett J. Kagan, the chief scientific officer and chief operating officer at Cortical Labs, Euronews Next.
“All you need is a little bit of blood or some skin, and you can generate an indefinite supply of these cells that you can then turn into neurons,” Kagan added.
The company says it is working on biological computing facilities in Melbourne and Singapore, where multiple units of its system could be deployed and accessed remotely.
Related
Parkinson’s patient moves freely again after world-first implant of lab-grown cells into his brain
How is it different from the conventional silicon chip?
CL1 allows users to interact directly with the neurons, sending electrical signals as inputs and interpreting how the cells respond in real time.
Similar to conventional computing systems, it uses silicon chips, but they are equipped with microelectrodes that communicate with living neurons, sending signals and reading their responses as part of the computation.
Unlike conventional silicon-based computers, the shoebox-sized system uses living cell cultures that require a nutrient-rich liquid to survive, an approach sometimes described as “wetware”.
Some 120 units of such a system are running a small data centre in Melbourne, Australia, Cortical Labs says.
While the idea of growing neurons in the lab is not new, what Cortical Labs says it has done differently is to standardise a system that can be used more easily when connecting cell cultures to electronic interfaces, rather than requiring complex, custom-built lab setups.
Related
These lab-grown hearts made from human stem cells are used to train AI to detect heart diseases
Efficiency found in human biology
What previously required months or years of specialised lab work can now be done in hours or days thanks to its integrated platform, the company says.
Interacting with biological neurons in this way could make computing more energy-efficient and adaptable than conventional systems.
“Biology is incredibly energy efficient. We [humans] don't require huge amounts of data. Kagan said.
“I have a small daughter, and for her to learn what a dog is, she just needs to see a couple of pictures of a dog. Machine learning needs to be tens of thousands, hundreds of thousands, depending on what the task is. We can also deal with uncertainty, with noisy information,” he added.
Using human-derived cells could also have research applications. Because the neurons are grown from donor samples, they may reflect genetic traits, allowing scientists to study how cells respond to different treatments in a lab setting.
That said, traditional silicon-based computers remain far more effective at precise, fast mathematical calculations, Kagan said. Advances in current AI systems may be reaching practical limits, as they require ever larger amounts of data and computing power.
Instead, future systems are likely to integrate biological and silicon-based approaches to achieve capabilities that neither could deliver alone, the co-founder said.
“The future of computing is when we can leverage all of the tools that we have available to get the best result”.
Some experts agree that biological systems offer advantages such as low energy use and adaptability, but question how far current approaches can go.
“If you are only using a flat network of human neurons, I do not believe it would have any major advantages compared to traditional silicon-based systems,” Alysson R. Muotri, the Director of Sanford Stem Cell Education and Integrated Space Stem Cell Orbital Research (ISSCOR) Center at University of California, San Diego, in the United States, told Euronews Next.
He said more complex, three-dimensional brain-like structures, known
---
## Expert Analysis
### Merits
- That said, traditional silicon-based computers remain far more effective at precise, fast mathematical calculations, Kagan said.
### Areas for Consideration
- Related Spanish doctors created an artificial womb to solve a major cause of miscarriage Ethical questions around biology in computing The use of human cells in computing raises ethical questions, although researchers say the level of concern depends on the complexity of the system.
- Go to accessibility shortcuts Share Comments Read more Tech News Europe's AI leader Mistral raises $830m for data centre near Paris Tech News Google sets 2029 deadline to prepare for quantum cyber threat Tech News Could data centres use human brain cells to process information? start-up brain Robotic Artificial intelligence BioNTech
### Implications
- As companies around the world race to build more data centres to power artificial intelligence (AI) models, researchers are exploring whether living human cells could be used in computing systems.
- The system, CL1, works by growing neurons from stem cells and placing them on chips that can send and receive electrical signals. “We're using these cells more like an engineering approach to build something that's never really existed before and might have properties that we've never been able to use before.
- The company says it is working on biological computing facilities in Melbourne and Singapore, where multiple units of its system could be deployed and accessed remotely.
- Interacting with biological neurons in this way could make computing more energy-efficient and adaptable than conventional systems. “Biology is incredibly energy efficient.
### Expert Commentary
This article covers cells, neurons, human topics. Notable strengths include discussion of cells. Areas of concern are also raised. Readability: Flesch-Kincaid grade 0.0. Word count: 997.
cells
neurons
human
lab
computing
systems
system
silicon
