Mimicking human sleep as a way to prevent catastrophic forgetting in AI systems

A trio of researchers from the University of California, working with a colleague from the Institute of Computer Science of the Czech Academy of Sciences, has found that it is possible to prevent catastrophic forgetting in AI systems by having such systems mimic human REM sleep. In their paper published in PLOS Computational Biology, Ryan Golden, Jean Erik Delanois, Maxim Bazhenov and Pavel Sanda describe teaching artificial intelligence systems to remember what was learned from a beginning task when working on a second task. Prior research has shown that people experience something called consolidation of memory during REM sleep. It is a process whereby things that were experienced recently are moved to long term memory to make room for new experiences. Without such a process, the brain undergoes catastrophic forgetting, where memories of recent things are not retained.