Superconducting Loops Mimic the Brain, New Research Shows

Superconducting Loops Mimic the Brain, New Research Shows

According to the latest reports, it seems that superconducting loops are mimicking the brain. Check out the latest reports about this below.

Superconducting loops could allow computers to retain and retrieve data easily

Computers operate using binary digits, which consist of only 0s and 1s. They perform digital calculations, processes and store information digitally. However, all of these operations require a significant amount of power resources. As we move towards the next phase of computing and explore the development of neuromorphic or “brain-like” computing, the current power requirements are impractical.

Researchers are exploring analog improvements to advance neuromorphic computing. This means advancing hardware in addition to software.

The University of California San Diego and UC Riverside have conducted research on a promising new method of storing and transmitting information using disordered superconducting loops.

The team’s research, published in the Proceedings of the National Academy of Sciences, shows that superconducting loops have the ability to demonstrate associative memory.

This is similar to how the human brain remembers the relationship between two unrelated items.

“I hope what we’re designing, simulating and building will be able to do that kind of associative processing really fast,” stated UC San Diego Professor of Physics Robert C. Dynes, who is one of the paper’s co-authors.

According to Dynes, short-term memory can be converted into long-term memory through repetition. For instance, if you frequently encounter a person and use their name, their name will be engraved into your memory more deeply.

This is why we tend to remember a song we heard when we were children but struggle to recollect what we ate for lunch yesterday.

“Our brains have this remarkable gift of associative memory, which we don’t really understand,” stated Dynes, who is also president emeritus of the University of California and former UC San Diego chancellor. “It can work through the probability of answers because it’s so highly interconnected. This computer brain we built and modeled is also highly interactive. If you input a signal, the whole computer brain knows you did it.”

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