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AI winter is well on its way

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Re: AI winter is well on its way

#31

Post by cooper12 »

kettlecorn wrote: post #23
buvanshak wrote: post #19

Earlier quoted context omitted.

>caption over a billion videos in 10 languages on YouTube; Utterly useless. And I don't think it is improving.

This is less useless than you think. Captioning video could allow for video to become searchable as easily as text is now searchable. This could lead to far better search results for video and a leap forward in the way people produce and consume video content.

They mean useless in the end result. Of course having perfect captions could potentially allow indexable videos, but the case is that the captions suck. They're so bad in fact that it's a common meme on Youtube comments for people to say "Go to timestamp and turn on subtitles" so people can laugh at whatever garbled interpretation the speech recognition made.

Re: AI winter is well on its way

#32

Post by CamelCaseName »

kettlecorn wrote: post #23
buvanshak wrote: post #19

Earlier quoted context omitted.

>caption over a billion videos in 10 languages on YouTube; Utterly useless. And I don't think it is improving.

This is less useless than you think. Captioning video could allow for video to become searchable as easily as text is now searchable. This could lead to far better search results for video and a leap forward in the way people produce and consume video content.

I think he is stating that the quality of the transcription is poor.

Re: AI winter is well on its way

#33

Post by mirceal »

slowmovintarget wrote: post #24
mirceal wrote: post #17

I would not call it the “AI winter”. If you look at what people have called AI over time, the definition and the approaches have evolved (sometimes drastically) over time. Instead of being stuck on the fact that deep learning and the current methods seem to have hit a limit I think I am actually excited about the fact that this opens the door for experimenting other approaches that may or may not build on top of what…

Perhaps it'd be more correct to call it a "Strong AI Winter". We're no closer to "aware" machines. We've simply gotten very good at automating tasks that were once difficult to automate.

A friend that’s more optimistic about Strong AI once said that the ML that goes on today will probably serve the purpose of driving the peripheral sense organs of a future AI. Although it stretches a bit what’s possible today I could see that. I would call this a win if this ends up happening although I still belive we’re hundreds of years away from Strong AI.

Re: AI winter is well on its way

#34

Post by felippee »

oh-kumudo wrote: post #29

Author's reasons: 1.Hype dies down (which is really good! Meaning the chance of burst, is actually lower!) 2.Doesn't scale is false claim. DL methods have scaled MUCH better than any other ML algorithms in recent history (scale SVM is no small task). Scaling for DL methods are much either as comparing to other traditional ML algorithms, where it can be naturally distributed and aggregated. 3. Partially true. But self…

Author here: I'm using deep learning daily so I have a bit of an idea on what I'm talking about.

1) Not my point. Hype is doing very well. But narrative begins to crack, actually indicative of a burst... 2) DL does not scale very well. It does scale better than other ML algorithm because those did not scale at all. If you want to know what scales very well, look at CFD (computational fluid dynamics). DL in nowhere near that ease in scaling. 3) self driving is the poster child of current "AI-revolution". And it is where by far most money is allocated. So if that falls, rest of DL does not matter. 4) Not that this matters, does it?

Re: AI winter is well on its way

#35

Post by mirceal »

felippee wrote: post #18
mirceal wrote: post #17

I would not call it the “AI winter”. If you look at what people have called AI over time, the definition and the approaches have evolved (sometimes drastically) over time. Instead of being stuck on the fact that deep learning and the current methods seem to have hit a limit I think I am actually excited about the fact that this opens the door for experimenting other approaches that may or may not build on top of what…

Yeah, the problem is deep learning sucked a bunch of money - essentially took a loan against the future in the form of VC investments. And if that loan does not get payed, for the next few years you may not afford to explore all that other stuff.

Technically, VCs are not loaning you money. They’re more likely betting on you. It’s true that maybe they’ll be more reluctant to place big bets, but as with everything in life the VC optimism is cyclical.

Re: AI winter is well on its way

#36

Post by nopinsight »

cooper12 wrote: post #31
kettlecorn wrote: post #23

Earlier quoted context omitted.

This is less useless than you think. Captioning video could allow for video to become searchable as easily as text is now searchable. This could lead to far better search results for video and a leap forward in the way people produce and consume video content.

They mean useless in the end result. Of course having perfect captions could potentially allow indexable videos, but the case is that the captions suck. They're so bad in fact that it's a common meme on Youtube comments for people to say "Go to timestamp and turn on subtitles" so people can laugh at whatever garbled interpretation the speech recognition made.

Have you used/tried them recently? The improvement relative to 5 years ago is major.

At least in English, they are now good enough that I can read without listening to the audio and understand almost everything said. (There are still a few mistakes here and there but they often don’t matter.)

Re: AI winter is well on its way

#37

Post by AlexCoventry »

matiasz wrote: post #3

Judea Pearl sees a way out of the winter. https://www.theatlantic.com/technology/archive/2018/05/machi...

I think a lot of GOFAI approaches ought to be revisited to see whether they benefit from the new perceptual and decision capabilities of Deep Learning systems. Alex Graves's papers are particularly good at this.

Things like this reinforcement learner for theorem proving are pretty exciting possibilities. https://arxiv.org/pdf/1805.07563v1.pdf

Re: AI winter is well on its way

#38

Post by Schoolmeister »

cooper12 wrote: post #31
kettlecorn wrote: post #23

Earlier quoted context omitted.

This is less useless than you think. Captioning video could allow for video to become searchable as easily as text is now searchable. This could lead to far better search results for video and a leap forward in the way people produce and consume video content.

They mean useless in the end result. Of course having perfect captions could potentially allow indexable videos, but the case is that the captions suck. They're so bad in fact that it's a common meme on Youtube comments for people to say "Go to timestamp and turn on subtitles" so people can laugh at whatever garbled interpretation the speech recognition made.

To be honest, as the other child comment said, I too have noticed they have gotten way better in the last 5 years. Also, the words of which it isn't 100% sure are in a slightly more transparent gray than the other words, which kind of helps.

Re: AI winter is well on its way

#39

Post by AlexCoventry »

zitterbewegung wrote: post #10
joejerryronnie wrote: post #9

Well, now that the cat's out of the bag in regards to AI/ML, we can all get in on the ground floor of the next hype wave - quantum computing!

IMHO Quantum computing is as well hyped as Cold Fusion and shares some of its properties. Until "quantum supremacy" occurs or something that will show a real speedup we won't hear that much from it.

Cold Fusion was outright scientific misconduct. I'm not optimistic about QC working as intended, but I think the hope around it is honest.

Re: AI winter is well on its way

#40

Post by imh »

FYI This post is about deep learning. It could be the case that neural networks stop getting so much hype soon, but the biggest driver of the current "AI" (ugh I hate the term) boom is the fact that everything happens on computers now, and that isn't changing any time soon.

We log everything and are even starting to automate decisions. Statistics, machine learning, and econometrics are booming fields. To talk about two topics dear to my heart, we're getting way better at modeling uncertainty (bayesianism is cool now, and resampling-esque procedures aged really well with a few decades of cheaper compute) and we're better at not only talking about what causes what (causal inference), but what causes what when (heterogeneous treatment effect estimation, e.g. giving you aspirin right now does something different from giving me aspirin now). We're learning to learn those things super efficiently (contextual bandits and active learning). The current data science boom goes far far far far beyond deep learning, and most of the field is doing great. Maybe those bits will even get better faster if deep learning stops hogging the glory. More likely, we'll learn to combine these things in cool ways (as is happening now).

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