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Researchers successfully imitate the functioning of brain neurons using semiconductor materials.
The artificial intelligence (AI) industry is growing at breakneck speed, especially since the COVID-19 pandemic disrupted the world order. Be it visual or physical abilities, creators of AI have always created these systems in the shadow of a human’s inspiration.
Teaching these activities demands powerful computer chips which are both - small as well as affordable. However, the optimisation of microelectronics is reaching its zenith - with a shrinking scope of stretching beyond its physical limits. “But that can't go on indefinitely – we need new approaches”, Larysa Baraban, a researcher from Helmholtz-Zentrum Dresden-Rossendorf (HZDR) asserts. Along with her, other scientists at Helmholtz-Zentrum Dresden-Rossendorf (HZDR), a Germany-based research lab and the Technical University, Dresden borrowed the blueprint of the human brain to imitate the functioning of brain neurons using semiconductor materials.
The research was recently published in the journal Nature Electronics. “Our group has extensive experience with biological and chemical electronic sensors,” Baraban said in an interview on the HZDR official website. “So, we simulated the properties of neurons using the principles of biosensors and modified a classical field-effect transistor to create an artificial neurotransistor.” The advantage of such a structure is that it stores and processes information simultaneously, in a single component.
This isn’t the first time that scientists have tried ‘electrifying’ the brain. Scientists made attempts to hook up nerve cells to electronics in Petri dishes decades ago. “But a wet computer chip that has to be fed all the time is of no use to anybody,” says Gianaurelio Cuniberti, a Professor for Materials Science and Nanotechnology at TU Dresden. Apart from Baraban and Cuniberti, Ronald Tetzlaff, Professor of Fundamentals of Electrical Engineering in Dresden, and Leon Chua from the University of California at Berkeley form the main brains behind the AI breakthrough.
The team achieved the feat by some innovative thinking. “We apply a viscous substance – called solgel – to a conventional silicon wafer with circuits. This polymer hardens and becomes a porous ceramic,” explains Cuniberti and continues, “Ions move between the holes. They are heavier than electrons and slower to return to their position after excitation. This delay, called hysteresis, is what causes the storage effect.” As the individual transistor gets excited, it will open and let the current flow.
However, the breakthrough has its own shortcomings. “Computers based on our chip would be less precise and tend to estimate mathematical computations rather than calculating them down to the last decimal,” the scientist explains. “But they would be more intelligent. For example, a robot with such processors would learn to walk or grasp; it would possess an optical system and learn to recognize connections. And all this without having to develop any software.”
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