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The AI Revolution Hasn’t Happened Yet

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Re: The AI Revolution Hasn’t Happened Yet

#161
post #88

Earlier quoted context omitted.

Such as...? Please don't go BS like "Google is an AI app" etc. I'd expect an app where AI is the indispensable component. You can make a decent search engine/camera/phone/car/microwave without AI.

The problem is that the definition of AI keeps changing. It essentially means "Things computers can't do". A roomba would have been considered AI not long ago, but now its just a vacuum cleaner that moves around randomly for a while and then goes back to its charger. I'd imagine turn by turn directions would be considered AI if you go back far enough.

Whether a roomba is AI or not depends on what it actually does. Moving around randomly based on a computer program is not intelligence.

Re: The AI Revolution Hasn’t Happened Yet

#162
post #121

Earlier quoted context omitted.

Cars (assuming you mean level 5 autonomous ones) are another one of those things which we won’t really be getting for at least 20 more years. 90% of the problem is solved, the remaining 10% are exponentially harder, so no one has a foggiest clue how to solve them, let alone solve economically enough to make the cars viable on the market.

Waymo is going to have a service on the road in Arizona for the general public this year. Sure, it isn't cars in every environment without having seen the territory, but it is an incredibly useful product that can be extended into more cities as the technology improves. And plenty of cities around the world have similar conditions to what is being used in Arizona. Low speed, AI driven electric buses on limited routes…

Busses on predefined routes aren't AI.

Re: The AI Revolution Hasn’t Happened Yet

#163
post #86

Earlier quoted context omitted.

All the more concerning that the Pentagon plans to have autonomous killing machines "ready" this year (hint: they won't actually be ready, but it's not like they'll tell us how many innocents they'll actually kill, especially with their very loose definitions of what a target is. They are yet to do that with the manual ones after all). https://thenextweb.com/syndication/2018/04/16/drones-will-so...

Killing is one of those scenarios where high error rate is no big deal, as long as there are no Americans on the ground. /s

But you have to be able to identify individuals as Americans or non-Americans or at least generate good excuses for why your system killed them.

Re: The AI Revolution Hasn’t Happened Yet

#164

Earlier quoted context omitted.

It's enough to replicate one of the 'AI' projects to see the vaporware yourself. You don't need to go above the university project level. Even a hobby level project will be enough to convince you of the absurdity of current claims of AI

What do you even mean? DeepMind is not vaporware, it really did revolutionize the world of Go. What about self-driving cars? They are actually working! Anyone who calls AI vaporware just has bizarre expectations that are based in sci-fi rather than reality.

Of course you can redefine the revolution to fit the expectations. I mean you just did. Why are you allowed to do that and i am not?

Re: The AI Revolution Hasn’t Happened Yet

#165

Earlier quoted context omitted.

I would also be interested in knowing which projects / applications of ML seemed easy wins - I generally get stumped on "use CV and facial recognition" for a business that has no need of facial recognition.

1. Market prediction -- given basic demographic data, and publicly-available or easily acquirable information like when the person's house was purchased, what their credit score is, etc., how likely is this person to want / need your product, and is it worth spending a salesman's time on them? 2. Data entry. We took a picture of this customer's utility bill / bank statement / receipt / whatever. Now do we give it to…

thank you

Re: The AI Revolution Hasn’t Happened Yet

#166
post #49

Earlier quoted context omitted.

It's worth noting that the training-time inference-time distinction matters here. Most of the fancy tech you've heard of recently (Semantic Seg, Pose, Localisation etc) can be pretty easily optimised for fast inference, and indeed it's not really so much of a research focus because it's so tractable (see MobileNets, v2, etc). Training, however, is still quite daunting.

That's a good point. I tend to be fairly dismissive of inference because what you end up with is a highly specialized algorithm rather than something that can easily continue to adapt. I suspect inference would probably fall into Jordan's category of "things that we call AI but probably shouldn't." But that's not to dismiss how important fast/cheap inference has been in allowing companies to actually build things wit…

Also even on the learning side, perhaps the raw task of making things faster isn't really that hard

https://eng.uber.com/accelerated-neuroevolution/

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