Scientists have designed a transistor that stores and processes information like the human brain and can perform cognitive tasks that most artificial intelligence (AI) systems today struggle with.
This technology, known as a "synaptic transistor," mimics the architecture of the human brain — in which the processing power and memory are fully integrated and found in the same place. This differs from conventional computing architecture, in which the processor and memory are physically separate components.
"The brain has a fundamentally different architecture than a digital computer," Mark Hersam, research co-leader and professor of material science, engineering and computing at Northwestern University, said in a statement. "In a digital computer, data move back and forth between a microprocessor and memory, which consumes a lot of energy and creates a bottleneck when attempting to perform multiple tasks at the same time."
Because of its full integration between computing power and memory, the synaptic transistor can achieve significantly higher energy efficiency and move data extremely fast, researchers wrote in the study, published Dec. 20 in the journal Nature. This new form of computing architecture is needed, the scientists said, because relying on conventional electronics in the age of big data and the growing demand for AI computing workloads will lead to unprecedented energy consumption.
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