[jsemrau]

We (humanity) have made huge progress to understand images in terms of content and emotions of people. Imagenet is truly a gift to the world. However, that has brought us only a small but important step forward. Clearly expectation has to catch up to reality. However, all these solutions are becoming quickly more accessible to the laymen bringing another boost to operational efficiencies for companies worldwide.

[cirgue]

> We (humanity) have made huge progress to understand images in terms of content and emotions of people.

We don't have systems that 'understand' anything, nor do we have anything remotely close. We have systems that can associate an arbitrary tag with an image based on a set of patterns that exist in the image. That's a pretty awesome accomplishment, but it is a tiny fraction of the problem of 'understanding'.

[unityByFreedom]

> Clearly expectation has to catch up to reality.

Woah, you feel expectations are behind reality? I feel there's a lot of news lately predicting AGI.

[psyc]

I actually do feel that expectations are behind reality, at least amongst those who are just barely too smart for their own good. I still see comments daily on HN or Reddit that promote the narrative that there is no AGI, people only work on ML, and all ML is a narrow party trick. And I think that is a terrible characterization of what, e.g., the computational neuroscientists are doing. Peruse some of the research happening at MIT and Stanford right now, and I don't see how anyone can cling to the "it's just ML" canned response.

[pdimitar]

Maybe because, gods forbid, people judge by real-world results and not by the words of a bunch of narrow specialists patting themselves on the back?

The author's points still stand. Robots do fall over trying to open doors and they don't invent new ways to climb a chair. This is a fact. The terrible characterization you speak of is well-founded in observable reality. That is a fact as well.

[psyc]

If this is your attitude towards long-term academic research, there's little hope I could expand your awareness of what the state of the art in AI actually is. I'm reminded of a point Yudkowsky made 10 years ago:

http://lesswrong.com/lw/kj/no_one_knows_what_science_doesnt_...

[pdimitar]

I am sure you misunderstand me but I gladly take the blame for it. I am all for people doing experiments just for the heck of it and being paid for it -- we as a race need a lot more leisure and discovery time. We're being robbed of leisure and discovery time more and more with each passing year, we always owe somebody money, there's always something else that is urgent to do, and in the end we never get to just slack for a year or two, especially after a burnout -- something that was deemed very normal even only 50 years ago. This is an awful period of human history and one I am sure will be remembered with great deal of shame one day. But let me not digress a lot...

I am 100% behind science, experimentation, and even silly / goofy discoveries whose usefulness might come centuries later (or never; I am okay with that). Please don't get me wrong. We need much more of that as a race.

I will also immediately agree that I am oblivious to what is happening in the AI area. But can you blame my cynicism? Everybody, their dog, and its butler are now claiming to do "AI innovation" and in the end 99% of them just swallow investment dollars, figure out a lucrative exit, and some even repeat that a year or two later. Naturally, people get worn out and start putting snarky remarks when they hear the now-meaningless term "AI" -- I am one of them, and I don't feel bad about it. I believe the sarcastic attitude is well justified.

Everybody keeps praising certain, very specifically tuned, NNs when they do certain very specific tasks. Fine. I will grant you that I can't code the algorithms needed to surpass human doctors in recognizing latent cancer or any kind of early signs of a dangerous disease. This is true. But the current way of doing things is like "input heckton of data, go to lunch, expect magic when you return". It definitely feels like it, even if I know that it's not factually true.

NNs show bias. Seems like nobody cares, they're like "yeah we know it's a problem, we'll get to it" and yet there are NNs that very likely already deny black families loans due to the inherent bias in the datasets they've been fed with. The concept of implementing a truly explainable AI seems to be very new when it had to be there right from the start and shouldn't have ever been missing; what are you people even thinking?! A driverless car makes a strange decision and what, "the NN worked perfectly"?! Bah.

To me, "AI" advocates are very content to deny very real issues that exist RIGHT NOW and that makes me cynical about that branch of science since you guys always seem to try and sprint into the future while blindfolding yourself about things that need attention here and now.

I admit I got off on a tangent. In any case, these are my collective thoughts on the topic.

[unityByFreedom]

If you want to cite some form of AI tech that isn't based on statistics, I'm all ears. ML isn't real magic, that's for sure.

[psyc]

I can't even imagine what relevance magic would have to any of this.

[jsemrau]

Well I guess it's a grammar issue ;-) Of course expectations are somewhere near HAL while we are throwing bones.