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Novel memristors to overcome AI's 'catastrophic forgetting'

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Summary
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78% Informative

Memristors consume extremely little power and behave similarly to brain cells.

Unique properties could help address problem of 'catastrophic forgetting' where artificial neural networks abruptly forget previously learned information.

Memristive elements are considered ideal candidates for learning-capable, neuro-inspired computer components modeled on the brain.

Memristive component is chemically and electrically more stable, more resistant to high temperatures, have a wider voltage window and require lower voltages to produce.

This combination of analog and digital behavior is particularly interesting for neuromorphic chips because it can help to overcome the problem of "catastrophic forgetting" "Our results will further advance the development of electronics for 'computation-in-memory' applications," says Valov .

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