NEW YORK: A brain cell computer powered by life itself can be found at Princeton University – and the ramifications for artificial intelligence, neuroscience, and medicine all come at once with one piece of technology that upends many traditional notions of computers and how they must function.
The Princeton scientists have merged live brain cells with electronics to build a single three-dimensional structure capable of recognising electrical signals, learning through experience, and running at an energy efficiency that renders current artificial intelligence systems incredibly inefficient by comparison.
How the Living Brain Cell Computer Really Functions
Previous efforts to use brain cells as computational tools focused almost solely on growing cells in a 2-dimensional culture, in petri dishes, or in 3-dimensional groups in which scientists observed them externally without much interaction. This prevented scientists from obtaining high-quality data and precise manipulation of stimulation of the cells.
The Princeton living brain cell computer works in an entirely different way. Instead of analyzing the neurons externally, the machine works by interacting with brain cells internally, which marks a significant difference in the quality and profundity of biological computation.
70,000 Neurons Create a Living Network
The scientists employed the mesh scaffold to grow thousands of neurons into a vast network. The resulting living brain cell computer is made up of around 70,000 neurons that communicate through the mesh along with multiple tiny electrodes that are able to monitor and control the neurons’ electrical impulses with great accuracy.
Such accuracy is, in fact, what sets apart the crucial innovation provided by the Princeton device. The combination of these two methods provides research with the ability to observe and control neuronal electrical activity much more accurately than was possible in any previous biological computer something entirely out of reach of the flat culture approach.
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Learning and Experimentation for Six Months
In the Princeton study, the living brain cell computer’s evolution and capability were measured for over six months. They watched the neural network as it developed and experimented with ways to make the connections between specific neurons either stronger or weaker.
Next, the scientists taught the algorithm how to detect patterns in the electrical signals that were produced by the neurons during their activity. The test was carried out under two completely different conditions: pattern recognition in space and pattern recognition in time. In both instances, the biological computer made up of brain cells successfully recognized various patterns, showing real computational abilities derived from biological neuron activity.
Energy Usage: Key Vulnerability in Modern Artificial Intelligence
The biological neuron computer resolves an issue that the artificial intelligence sector itself has recognized as the single biggest bottleneck to growth for its future. Training and utilizing the complex neural networks required by modern AI consumes unprecedented levels of electrical energy, which creates a critical question mark regarding the sustainability of AI in the future.
According to Assistant Professor Tian Ming Fu of the Department of Electrical and Computer Engineering at Princeton University, the energy gap is expressed very accurately indeed. The human brain requires about one millionth of the energy needed by modern AI for similar operations. In other words, there is such an energy gap between humans and machines that it forms the essence of the problem itself.
Brain Understanding for Treating Brain Diseases
The living brain cell computer was originally created as a research instrument in neuroscience but only later did it become clear how it could be used for computing. As Kumar Mritunjay, the postdoctoral researcher who was the lead author on the paper, explained, not only does the development of three-dimensional biological neural networks improve computing power, but it also assists in discovering the computational processes used by the brain itself.
This combination serves to provide both improvements in computer efficiency as well as insight into brain functioning and illness, which means that the living brain cell computer becomes a research vehicle whose contributions range across various sciences and medicine at once.
