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An understanding of AI’s limitations is starting to sink in

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Re: An understanding of AI’s limitations is starting to sink in

#201
post #194

Earlier quoted context omitted.

I'm not good at math, but I'm confused by the association of AI with non-linear stuff, setting aside the association of non-linear with "bad". I thought ML involved linear algebra or something (says xkcd!) which would presumably be...linear?

The underlying derivatives are linear (like all derivatives) but neural networks' ability to approximate arbitrary non linear functions is one of their biggest strengths.

Yes, so I'm left wondering, when making the association of the math to the badness, how do you decide if the linearity or the non-linearity is the salient part?

Re: An understanding of AI’s limitations is starting to sink in

#202

Earlier quoted context omitted.

> can get things very wrong if faced with unexpected input Alice: Bob, Can you translate "Eat my shorts" into latin for me? Bob: No. I don't speak latin. Alice: Go on - try anyway. Bob: "Eatus mine shortus" Alice: Wrong! The answer is "Vescere bracis meis". You're totally wrong Bob! I was expecting more of you!

If models actually were able to tell you what they know and don’t know, then sure. But instead they just give you an output for any input you give them, whether they have a clue or not.

This is such a simplistic view of a vast and evolving field of scientific research, it's too cartoonish of an argument to even warrant a real response. Which is why the conversation around ML gets negatively selected against actual researchers and practitioners, who get headaches from opinions like the one above.

Re: An understanding of AI’s limitations is starting to sink in

#203
post #59

We have also been watching these machine learning models for 6 months: - increase the volatility in virtually every financial market they touched - be exploited by adversarial learning networks to amplify funded propaganda as news - use poorly contrived sentiment analysis to generate incomprehensibly meaningless news headlines These non-linear "function approximators" have absolutely unpredictable and insane non-line…

How have machine learning algorithms negatively affected financial markets in the last 6 months? Markets have been volatile because information about the real world has been volatile. I don't think markets in an earlier era would have handled a global pandemic any more robustly than they did in 2020.

Re: An understanding of AI’s limitations is starting to sink in

#204

Earlier quoted context omitted.

There has been next to ZERO progress towards genuine AGI despite a never-ending deluge of AI articles; that's normally the cause of scepticism. After several decades and a much-hyped last few years we have fake cleverness - impressively so in both cases - but nothing more.

> After several decades and a much-hyped last few years we have fake cleverness - impressively so in both cases - but nothing more. Why should I care if my fridge is fake clever or real clever?

I think the problem is that in a long list of edge cases, it's neither fake clever nor real clever but just "dumb". This is, of course, always an issue with computers, but what makes ML so vexing is that it's inscrutable.

For your fridge that's an annoyance, but when used for more serious applications the ramifications can be large. Example: https://www.technologyreview.com/2019/01/21/137783/algorithm... – there's much more where that came from.

ML works by taking a huge amount of data and finding patterns and is pretty much incapable of judging individual cases. We have ugly words for humans who judge people based on generalisations instead of judging the individual...

Computers and algorithms are devoid of empathy and humanity, I am extremely apprehensive in using them to make any sort of judgement call, especially if the calculation is inscrutable. Humans may not be perfect, but at least they're ... human.

ML is an interesting tool which can be used for many things, but right now it's also being misapplied for many things. I think a lot of opposition comes from that, rather than your fridge or whatnot.

Re: An understanding of AI’s limitations is starting to sink in

#205
post #101

Earlier quoted context omitted.

Aside from possibly Google, all of these products / services would have just as much, if not more, value without any AI beyond basic statistics.

Many AI systems are used in the backend to increase revenue. Netflix has a very complex recommendation algorithm based on deep learning/statistics. Amazon uses a lot of machine learning to optimize transportation (NP-hard problem!) , sales, etc..

My tastes may be a bit hard to model but I don't get any value from Netflix's recommendation algorithm at all. I find new things on Netflix by reading human curated reviews online and then searching for titles by name.

Re: An understanding of AI’s limitations is starting to sink in

#206
I think there's an opportunity right now for new, human curated indexes in the style of the old Yahoo index. AI content generation is getting too good at fooling AI curation and I'm getting less and less value in broad searches on Google. I would pay a monthly fee for hand-vetted lists of the best content on topics I'm interested in.

Re: An understanding of AI’s limitations is starting to sink in

#207
post #59

We have also been watching these machine learning models for 6 months: - increase the volatility in virtually every financial market they touched - be exploited by adversarial learning networks to amplify funded propaganda as news - use poorly contrived sentiment analysis to generate incomprehensibly meaningless news headlines These non-linear "function approximators" have absolutely unpredictable and insane non-line…

"AI" is a very vague term. What you described aren't entirely "machine learning", but a combination of existing linguistic techniques and machine (deep) learning.

People confuse what AI can do, and what is AI all the time. It also doesn't help when there are so many inexperienced data scientist making promises that they can't achieve.

In your example, I'd argue that a human is not necessarily a better driver than a machine. An attentive and careful driver is certainly better than a machine right now, but there are many who drive carelessly. While a person is unlikely to mistake a square stop sign as something else, there are so many drivers that would simply ignore the sign, and traffic lights in general. They'd also drive dangerously because of road rage, and inattentiveness. And the majority of traffic accidents are caused by these drivers. A machine is unlikely to do these.

That said, until we figure out how to run all these deep learning models without a crazily expensive and power-consuming GPU, it is unlikely AI would be used as general purpose programs.

Re: An understanding of AI’s limitations is starting to sink in

#208
post #101

Earlier quoted context omitted.

Aside from possibly Google, all of these products / services would have just as much, if not more, value without any AI beyond basic statistics.

Many AI systems are used in the backend to increase revenue. Netflix has a very complex recommendation algorithm based on deep learning/statistics. Amazon uses a lot of machine learning to optimize transportation (NP-hard problem!) , sales, etc..

A while ago I watched a 4-part documentary about the every-day lives of ancient Egyptians. Pretty interesting.[1]

For weeks after that my recommendations were filled with bullshit such as "PROOF ALIENS BUILT THE PYRAMIDS!" and such.

So yeah, maybe those "very complex recommendation algorithm based on deep learning/statistics" is perhaps not always such a great idea. In this particular case, it's just a mere annoyance for me, but imagine a 13-year old watching a few genuine documentary videos on Egypt and then seeing this bullshit; they don't have the capacity I have to see it's bullshit.

And imagine if it was on a more serious topic than who built the pyramids...

If I were to ask a YouTube engineer "why did I get this recommendation specifically?" then the answer would probably be "dunno".

An additional issue is that the YouTube of yesteryear was much better in browsing random videos. Now everything is based on what I've watched before, instead of just "give me a list of science videos" or whatnot. This is also an issue I have with Netflix (or rather, had, since I no longer have an account).

It seems to me that inscrutable mindless AI learning has a part in the spread of misinformation and bullshit. I'm not sure how large that part is, but I suspect it's significant. I'm hesitant of the total value in these cases, regardless of what it may do for the bottom line in terms of revenue.

[1]: I'll just drop the link to it here in case anyone's interested: https://www.youtube.com/watch?v=hnsNwwwHm2I

Re: An understanding of AI’s limitations is starting to sink in

#209
post #96

Earlier quoted context omitted.

I completely agree with this. Let me add a non-US perspective that may surprise some people. I think a big part of what is holding back many companies from making effective, genuine, real-world use of AI is that a significant majority of the individuals involved are bad at their jobs . On the business side, there is an widespread unwillingness to acknowledge that technical people may be better placed to make decision…

>On the business side, there is an widespread unwillingness to acknowledge that technical people may be better placed to make decisions than businesspeople. Maybe acknwledging this would mean losing their jobs. Buisness people have mortgages and children and they probably don't like the idea of having their job replaced by a robot. It is important to remember that the admin/money-side people are not playing the game…

“It is difficult to get a man to understand something, when his salary depends on his not understanding it.” - Upton Sinclair

Re: An understanding of AI’s limitations is starting to sink in

#210

Earlier quoted context omitted.

There has been next to ZERO progress towards genuine AGI despite a never-ending deluge of AI articles; that's normally the cause of scepticism. After several decades and a much-hyped last few years we have fake cleverness - impressively so in both cases - but nothing more.

> There has been next to ZERO progress towards genuine AGI I mean, really? In the most pessimistic evaluation of ML research, we still know which techniques and paradigms won't work for AGI. That's not zero progress. Nobody is expecting this to happen overnight.

My comment was in the context of yet another completely unsourced claim of progress.

No evidence - as always. No progress.

Of course, if you - or anybody else - can show evidence of a genuine advance towards AGI, rather than breathless hype and vague assertions based on the impressive but irrelevant narrow-domain "AI" expertise of Alpha-x and the like, I (and many others) would love to read it.

We've been waiting since at least Alan Turing.

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