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That's why many researchers called their work "cognitive science", "machine learning", "optimization", "logic" or "applied maths" and avoided "AI".

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For example, automakers are shipping all sorts of fancy driver assistance systems, and a lot of that is driven by fancy image recognition and deep learning systems.

I..."Seems to me that there's a big difference now, in that even limited as it is, current AI advances are finding many important practical uses.

Interesting tweet from the chat bot here:https://twitter.com/Tayand You/status/712698413746298880"Machines have bad days too ya know.easy on me.. "It tries to slip this marketing-survey-type-question into a conversation. I'd bet that it you give her your zipcode, she'll answer your questions about the weather or something. I don't know if you should totally assume data collection as a goal, before you figure out if she's at all making any sense in the first place. It's not fairly common for anybody to just casually ask me for my zip code unless they're going to mail something to my house, or are trying to figure out an estimated distance for a trip. For those wondering what I mean exactly: we're seeing the term A. being used in marketing, in the papers, in the news. There were attempts, and I'm sure there was some commercial success, but it remained a small niche.

She's also suggested someone meet up with her. Outside of that I don't see people casually asking for your zip code. Compare to deep neural networks today, which are driving sales worth billions and have huge resources from major automakers, and no doubt many others.

Current research is producing results that can improve these systems, which means that research is worth a lot of money.