IBM is teaching AI to behave more like the human brain

Deep learning neural networks -- the likes of which power AlphaGo as well as the current generation of image recognition and language translation systems -- are the best machine learning systems we've developed to date. They're capable of incredible feats but still face significant technological hurdles, like the fact that in order to be trained on a specific skill they require upfront access to massive data sets. What's more if you want to retrain that neural network to perform a new skill, you've essentially got to wipe its memory and start over from scratch -- a process known as "catastrophic forgetting". Compare that to the human brain, which learns incrementally rather than bursting forth fully-formed from a sea of data points. It's a fundamental difference: deep learning AIs are generated from the top down, knowing everything it needs to from the get-go, while the human mind is built from the ground up with previous lessons learned being applied to subsequent experiences to create new knowledge.