An AI inspired by the way humans form long-term memories during sleep can learn to perform tasks better than existing models
Building AIs that sleep and dream can lead to better results and more reliable models, according to researchers who aim to replicate the architecture and behaviour of the human brain. But other experts say recreating the intelligence we see within ourselves may not be the most fruitful path for AI research.
Concetto Spampinato and his colleagues at the University of Catania, Italy, were looking for ways to avoid a phenomenon known as “catastrophic forgetting”, where an AI model trained to do a new task loses the ability to carry out jobs it previously aced. For instance, a model trained to identify animals could learn to spot different fish species, but then it might inadvertently lose its proficiency at recognising birds.
They developed a new method of training AI called wake-sleep consolidated learning (WSCL), which mimics the way human brains reinforce new information. People shuffle short-term memories of experiences and lessons learned throughout the day into long-term memories while sleeping. The researchers say this method of learning can be applied to any existing AI.