In translate it replaces a naive translator's job. In speech recognition it gives you a new-ish interface to systems.
In prediction and personalization it gives you what you likely want. (Local weather, local traffic info, local news, in the language it knows you understand, in the format you prefer, at the time it think you most likely want it, etc..).
It puts some "smart" into things. But translate is just a smart dictionary, it's not a real translator, for that we need stronger AI (something like the Jeopardy playing Watson + Google Knowledge Graph / FreeBase + language translation + it should ask questions if it doesn't understand something).
ML is amazing, but it's just a slow march toward more and more adaptive smarts (general intelligence) in a box (hence artificial). And there's probably a tipping point for that. When it can start to learn, or program itself, blablabla... ( https://intelligence.org/2013/04/29/intelligence-explosion-m... )
If we look at things from that point of view, then nothing is new.
What are computers good for? They are just replacing a calculator, which was just replacing some manual calculation machines, which were just replacing mental calculus.
A "naive translator's job" cannot translate arbitrary sentences for free and instantaneously. We are not far from real-time (and quality) translation that will make it possible to talk to somebody in a foreign language and have everything translated on the go (there's already a feature that replaces text in a foreign language in the image you're viewing).
I don't know :) I think I'm quite satisfied with the level of disruption ML is bringing to the world. And I feel people are constantly pushing away against this ("This is not real AI!") every time we start to understand how these things work.
Reinforcement Learning is the case of a program teaching itself (without training data or instructions) but I still, some will argue it is not AI because "it's just maths and engineering hacks", I guess.
I understand how ML/AI works, and there are great things like collaborative filtering, self-driving whatevers, "expert systems" (IBM Watson), magical image processing (which just shows how much detail our own brains just imagines and fills in for us in non-ideal conditions).
I'm not saying it's not real AI, I'm saying I can't wait for the time when these separate components/models can be "synergized", when one big system can be trained for multiple tasks, and when it can train itself tasks.
In translate it replaces a naive translator's job. In speech recognition it gives you a new-ish interface to systems.
In prediction and personalization it gives you what you likely want. (Local weather, local traffic info, local news, in the language it knows you understand, in the format you prefer, at the time it think you most likely want it, etc..).
It puts some "smart" into things. But translate is just a smart dictionary, it's not a real translator, for that we need stronger AI (something like the Jeopardy playing Watson + Google Knowledge Graph / FreeBase + language translation + it should ask questions if it doesn't understand something).
ML is amazing, but it's just a slow march toward more and more adaptive smarts (general intelligence) in a box (hence artificial). And there's probably a tipping point for that. When it can start to learn, or program itself, blablabla... ( https://intelligence.org/2013/04/29/intelligence-explosion-m... )