Today, most AI systems are based on layers of mathematics that are only loosely inspired by the way the human brain works. Different types of machine-learning applications require different mathematical structures, and the resulting algorithms are only able to perform very specific tasks such as speech recognition or the identification of objects.
While there are many domains where AI is superior, humans still have an advantage when tasks depend on the flexible use of memory. If we can understand that mechanism, the hope is that we can replicate this process with a new generation of neuroscience-inspired AI systems for rapidly solving novel problems.
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