For those who started their careers in AI and left in disillusionment (Andrew Ng confessed to this, yet jumped back in) or data scientists today, the consensus is often that artificial intelligence is just a new fancy marketing term for good old predictive analytics. They point to the reality of Apple’s Siri to listen and respond to requests as adequate but more often frustrating. Or, IBM Watson’s win on Jeopardy as data loading and brute force programming. Their perspective, real value is the pragmatic logic of the predictive analytics we have.
But, is this fair? No.
I think this article makes an important point. A lot of old school AI people are unhappy with the direction that commercial AI has taken. Commercial AI has largely abandoned trying to create an artificial mind, and is instead focusing on where they can make computing systems more intelligent.
They are, of course, driven by the profit motive. They’ll take what results they can use now, and worry less about pie in the sky aspirations. I think that’s totally reasonable for them. Getting upset that they aren’t working toward building a human like mind is just misguided.
I also think it’s a strategy that can eventually lead to breakthroughs. A lot of times, when you can’t figure out how to solve the big problem, often times focusing on smaller problems will eventually shake things up enough until a solution for the big problem becomes apparent.