Deep learning is changing the way we use and think about machines. These guys have shown that the approach biological systems use to learn, and to forget, can work with artificial neural networks too.
The key is a process known as Hebbian learning, first proposed in the 1940s by the Canadian psychologist Donald Hebb to explain the way brains learn via synaptic plasticity.
So Aljundi and co have developed a way for artificial neural networks to behave in the same way. Neural networks with memory aware synapses turn out to perform better in these tests than other networks. The key point is that the team has found a way for neural networks to employ Hebbian learning.
If these scientists can make their version of Hebbian learning better, it should make machines more flexible in their learning.