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

economist.com

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

#221

Post by Vinceo »

fxtentacle wrote: post #34
seibelj wrote: post #7

I’m a longtime AI skeptic who has been arguing passionately against the doom-sayers, many in my own family and in casual conversations with laymen, for several years. I stand by this article I wrote which summarizes my views https://medium.com/@seibelj/the-artificial-intelligence-scam... The hype on AI was absolutely astonishing. I’m glad it’s finally coming back to reality.

That article is well argued and I am inclined to agree. But then I noticed that we seem to strongly disagree on other topics. I find it fascinating that you can both see AI as what it truly is (a rebranding to solicit investment) yet still cheer for cryptocurrencies, which I personally believe to be not much more than a pyramid scheme to dupe those investors that buy in late. In my opinion, both AI and crypto are qui…

Why do you believe that cryptocurrencies are not much more than a pyramid scheme?

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

#222

Post by mr_toad »

pwdisswordfish2 wrote: post #161
mtgp1000 wrote: post #11

I'm not sure how anyone who's watched the exponential growth of a brand new domain can pick a point today to and say that things aren't as good as we expected. What may have happened was that some eager CEOs have overpromised on timelines and resources. But the revolution is coming, ML is already starting to change society. We're building the tech. Right now. The author does not even realise the immeasurable potentia…

Are there examples in history where things requiring great time and effort were built then abandoned? In recent times, due to a relative dearth of high yield investment opportunities, there is a lot of money with nowhere to go. Some believe much of it is "dumb" money. Overfunded startups are one possible symptom. Heavily-funded "AI" may be another. This is before we even consider the moral and ethical issues of using…

> Are there examples in history where things requiring great time and effort were built then abandoned?

The space program?

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

#223

Post by gwbas1c »

My general guidelines about AI (Machine learning, programming):

1: Computers can't read minds! Your algorithm might know that I like the Beatles because I listen to them a lot, but it can't predict that I woke up today craving to listen to some music from my childhood.

2: You don't know what you don't know! Your algorithm might make 24 frames per second film look smoother at 60 fps, but if something like wheel spokes move backwards at 24fps, it'll have a tough time getting the wheel to move the right way at 60fps.

3: Just because you have the information, doesn't mean you know how to write a program that can extract the knowledge you're looking for.

Which really means we need a super advanced AI with a worldview and context in order to automate certain kinds of information processing. I don't expect this anytime soon.

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

#224

Post by dreamcompiler »

perl4ever wrote: post #190
YeGoblynQueenne wrote: post #183

Earlier quoted context omitted.

Linear models have more bias, so they represent current data less well and are more predictive of future, unseen data (think of a straight line through a point cloud). Non-linear models have more variance so they represent current data better and are less predictive of future, unseen data (think of a line snaking around a point cloud). An added complication is that deep neural net models are, in practice, vectors (or…

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 inner activation function (AF) of neurons is inherently nonlinear; it has to be in order to solve any problem that is not linearly decomposable (which is basically all of the interesting problems). Often the AF nonlinearity shows up as a thresholding operation following a linear weighted sum, but that's not the only mechanism.

And yet neurons are not "pure" binary thresholders the way logic gates are because you can't take the derivative of a binary function, and you can only do backpropagation on differentiable functions. The compromise neurons make is a "smoothed threshold" or sigmoidal curve which is differentiable but still very nonlinear.

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

#225

Post by entha_saava »

mtgp1000 wrote: post #11

I'm not sure how anyone who's watched the exponential growth of a brand new domain can pick a point today to and say that things aren't as good as we expected. What may have happened was that some eager CEOs have overpromised on timelines and resources. But the revolution is coming, ML is already starting to change society. We're building the tech. Right now. The author does not even realise the immeasurable potentia…

It sounds like some buzzword speak. Most things that are heralded as ML are nothing but data science idiots from python schools applying some basic math transformations and overselling them.

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

#226

Post by whymauri »

mellosouls wrote: post #210
whymauri wrote: post #132

Earlier quoted context omitted.

> 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 sin…

I would say the only tangible evidence of a "genuine advance" towards AGI would be the growing amount of computational power available to us every year.

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

#227

Post by wltprgm »

rb808 wrote: post #138

I'm still not sure what successful AI implementations there have been. Stuff like Amazon/Spotify recommendations seem sensible. Is there anything else out there that is impressive?

AlphaGo

Everything about AI is impressive, as long as there is any

--- By HN AI specialists in this thread /s

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

#228

Post by [deleted] »

AlexandrB wrote: post #220
mtgp1000 wrote: post #11

I'm not sure how anyone who's watched the exponential growth of a brand new domain can pick a point today to and say that things aren't as good as we expected. What may have happened was that some eager CEOs have overpromised on timelines and resources. But the revolution is coming, ML is already starting to change society. We're building the tech. Right now. The author does not even realise the immeasurable potentia…

> There's far more to do with ML and AI than self driving cars and shitty ad recommendations. Yeah, there's also shitty sentencing recommendations[1], new-age phrenology[2], and high-tech redlining[3]. I think your entire field needs to take a year off and take some ethics and philosophy courses before going any further. Otherwise we're all going to end up much worse off. [1] https://www.nytimes.com/2017/10/26/opinio…

[deleted]

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

#229

Post by shaklee3 »

bufferoverflow wrote: post #217
joe_the_user wrote: post #169

Earlier quoted context omitted.

You're being a pedantic. Human beings are tremendously better at driving than machines despite sometimes saying hexagonal rather than octagonal. Humans and current AIs both make mistakes but humans manage a kind of robustness, ability to deal gracefully with unexpected situations, that current AIs don't seem to be progressing towards.

> Human beings are tremendously better at driving than machines Human drivers: 1 death per 88 million miles traveled (in the US) [1] Tesla Autopilot: 5 deaths per 3 billion miles [2] [1] https://www.iihs.org/topics/fatality-statistics/detail/state... [2] https://electrek.co/2020/04/22/tesla-autopilot-data-3-billio... and https://en.wikipedia.org/wiki/List_of_self-driving_car_fatal...

Autopilot isn't used in the same conditions.

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

#230

Post by renewiltord »

andbberger wrote: post #74
renewiltord wrote: post #65

It's limited but so effective! The other day a friend asked for photos of her sister (also a friend) that I had because it's her birthday and she wanted to make a collage. I just searched on Google Photos by her name and it found a bunch because of the face classification. That's some good shit.

works great until I add epsilon of adversarial noise and turn your sister into an ostrich

Fortunately, my camera is not my adversary so I'm safe.
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