Import AI: Changes at Twitter Cortex, Catastrophic Forgetting, and a $1000 bet

Reusability: One of the reasons why AI progress is accelerating is the community is creating more and more reusable components that can be plugged into different domains, frequently attaining performance equivalent to or better than hand-designed algorithms. The 2015 ImageNet challenge was won by a Microsoft system built out of Residual Networks, then in 2016 Microsoft made a speech processing breakthrough via a system that also relied on Residual Networks. Similarly, DeepMind's WaveNet system has been slightly tweaked and re-applied to the domain of neural machine translation (PDF). This kind of re-use is a good thing as it suggests we are beginning to create the right sorts of low-level primitives that general intelligences can be built out of.