Cross-linguistic understanding has grown by leaps and bounds over the last two years. Classification tasks that topped out at 60% accuracy in 2017 are pushing 8

Cross-linguistic understanding has grown by leaps and bounds over the last two years. Classification tasks that topped out at 60% accuracy in 2017 are pushing 80s today. That in part is why I don’t buy any of the “AI winter” chatter. We’ve previously never had machines powerful enough to run most useful ML nor enough data to train effectively. Today, as in right now, we have both. Things that were neat theories in the 90s are profitable businesses today. Nobody in the ML field thinks strong AI is around the corner, or even 10-20 years from now. But that misses the point entirely. ML is useable and useful right now, and that’s not going to revert, no matter how many programmers grumble about “AI hype.”