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Author: Joseph Sun
Imagine a computer that isn't just built from metal and silicon, but one that also incorporates living human brain cells. This technology is known as biocomputing, and it has major implications for the race in developing Artificial General Intelligence.
Cortical Lab's first ever commercial Biocomputer (Credit: Cortical Labs)
What is biocomputing?
What is biocomputing?
Biocomputing is an emerging field that combines biology with computing. Unlike traditional computers that solely use silicon and electronic circuits, biocomputers incorporate both living neurons and silicon chips to create systems that can process information in ways similar to the human brain.
How does it work?
How does it work?
Researchers in biocomputing cultivate human neurons in a lab environment and then integrate them with electronic hardware. These neurons communicate with electrical and chemical signals, just as they do inside the brain. And when they connect to silicon chips, they form hybrid systems capable of real-time processing, decision-making, and learning.
So far, New Zealand researchers have made significant progress in biocomputing by engineering living cells to function like basic circuits. Using 9 different human cell types arranged in 3D cultures, they programmed each cell to perform specific computational instructions, mimicking logic gates such as AND, NOT, and OR, in order to create a primitive biological computer. These cells communicate chemically, enabling adaptable and evolving computing systems.
While they have a long way to go before they are as advanced as today's computers, the fact that researchers have already created rudimentary prototypes is already a notable achievement.
Actual Neurons, living on a neuron chip (Credit: Cortical Labs)
Why is biocomputing crucial in developing Artificial General Intelligence?
Why is biocomputing crucial in developing Artificial General Intelligence?
Projected AI Energy Demands by year 2030 (Credit: Vinson and Elkins LLP)
- Energy Efficiency
Normal AI models require constant re-training, which means that they need millions of watts and insurmountable amounts of data. In Ireland, AI development has already taken up 17% of national energy consumption. And in America, analysts predict that AI's energy consumption from AI development is going to encompass 20% of America's electricity demand by year 2030.
On the other hand, neurons have the incredible ability to absorb information and learn on their own, mitigating the need for constant retraining and adjustment. This has allowed the human brain to be incredibly energy-efficient. In fact, the brain uses only 20 watts, and is able to manage vast networks of neurons performing trillions of calculations and actions.
2. Creativity
2. Creativity
Artificial General Intelligence (AGI) is a type of AI that has human-level cognition and reasoning, meaning that it can create new ideas and perform beyond its set parameters.
However, current AI models cannot think for themselves. They cannot create new ideas or concepts; rather, they regurgitate whatever data they were trained on.
In contrast, living cells can form dynamic networks that learn, adapt, and generate novel ideas by processing information in ways that reflect the human brain's complex thought processes. This ability to innovate is critical for AGI, which requires flexible, generalized intelligence capable of reasoning at a human level. Thus, biocomputing offers a path toward AGI that conventional, silicon-based AI cannot.
Creativity, By Vierre Cloud
Challenges and Ethics of Biocomputing
Challenges and Ethics of Biocomputing
That being said, biocomputing has its issues.
Neurons' activity and performance can be drastically affected by high temperatures/heat. In fact, researchers from Yale discovered that even small changes in temperature of less than 1 degree celsius can lead to inactivity. This is a major issue, as computers usually generate a lot of heat.
Next, there are several ethical concerns regarding the use of biocomputing. If biocomputers use living human neurons, could they develop some form of consciousness/sentience? Wouldn't it be unethical to create or experiment on potentially conscious beings? And finally, if they gain self-awareness or cognitive abilities, will they fight back?
Moving forward, we must consider strict regulations in order to make sure that the development of biocomputing can go smoothly without any issues with consciousness/sentience.
Conclusion
Conclusion
Simply put, biocomputing is the future. It is millions of times more efficient than conventional silicon computers, making it crucial in reducing our carbon output and energy usage. Moreover, biocomputing harnesses living neurons that can think for themselves, paving the way for computers that have human-level intelligence and reasoning. This can allow us to discover all kinds of novel innovations and ideas, driving future prosperity. However, as we advance, it is essential to carefully address the ethical and moral implications these technologies raise. Strict regulations and responsible oversight must be put in place to ensure their development benefits humanity safely and equitably. Biocomputing has the potential to bring widespread benefits to society, but only if we do so in a safe and ethical way.
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