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AI winter is well on its way

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Re: AI winter is well on its way

#361

Post by isoprophlex »

akvadrako wrote: post #142
mastrsushi wrote: post #113

Warning 23 year old CS grad angst ridden post: I'm very sick of the AI hype train. I took a PR class for my last year of college, and they couldn't help but mention it. LG Smart TV ads mention it, Microsoft commercials, my 60 year old tech illiterate Dad. Do any end users really know what it's about? Probably not, nor should that matter, but it's very triggering to see something that was once a big part of CS turned…

AI taking over is the biggest threat facing humanity, but I don't think Hawking ever claimed it was imminent; it's likely 1000+ years away. It should be obvious why a superior intelligence is something dangerous.

The day we create a superior intelligence will be the greatest day of humanity. It will be fantastic if there's something beyond humanity. A logical, evolutionary conclusion to us.

All our Darwinian ancestors never had the capacity for intellectual fear of their superior successors...

Hopefully we as a species can get beyond our fear.

Re: AI winter is well on its way

#363

Post by flamedoge »

bitL wrote: post #348

I was recently "playing" with some radiology data. I had no chance to identify diagnoses myself with untrained eyes, something that probably takes years for a decent radiologist to master. Just by using DenseNet-BC-100-12 I ended up with 83% ROC AUC after a few hours of training. In 4 out of 12 categories this classifier beat best human performing radiologists. Now the very same model with no other change than adjust…

Next winter will probably going to be going over that 92% across all domains.

Re: AI winter is well on its way

#364

Post by shmageggy »

mtgx wrote: post #358
dekhn wrote: post #324

I'm a scientist from a field outside ML who knows that ML can contribute to science. But I'm also really sad to see false claims in papers. For example, a good scientist can read an ML paper, see claims of 99% accuracy, and then probe further to figure out what the claims really mean. I do that a lot, and I find that accuracy inflation and careless mismanagement of data mars most "sexy" ML papers. To me, that's what'…

You hear Facebook all the time saying how it "automatically blocks 99% of the terrorist content " with AI to the public and governments. Nobody thought to ask: "How do you know all of that content is terrorist content? Does anyone check every video afterwards to ensure that all the blocked content was indeed terrorist content?" (assuming they even have an exact definition for it).

Also, how do they know how much terrorist content they aren't blocking (the 1%), since they by definition haven't found it yet?

Re: AI winter is well on its way

#365

Post by bitL »

flamedoge wrote: post #363
bitL wrote: post #348

I was recently "playing" with some radiology data. I had no chance to identify diagnoses myself with untrained eyes, something that probably takes years for a decent radiologist to master. Just by using DenseNet-BC-100-12 I ended up with 83% ROC AUC after a few hours of training. In 4 out of 12 categories this classifier beat best human performing radiologists. Now the very same model with no other change than adjust…

Next winter will probably going to be going over that 92% across all domains.

Possibly, but will it be called AI winter, if e.g. average human has 88% accuracy and best human 97%?

Re: AI winter is well on its way

#366

Post by bitL »

imant wrote: post #357
bitL wrote: post #348

I was recently "playing" with some radiology data. I had no chance to identify diagnoses myself with untrained eyes, something that probably takes years for a decent radiologist to master. Just by using DenseNet-BC-100-12 I ended up with 83% ROC AUC after a few hours of training. In 4 out of 12 categories this classifier beat best human performing radiologists. Now the very same model with no other change than adjust…

Would you mind sharing which other, unrelated dataset you have used the model on?

I can't unfortunately, proprietary stuff being plugged into existing business right now.

Re: AI winter is well on its way

#367

Post by cs702 »

Well, the breathless hype around deep learning (with and without reinforcement learning) is bound to subside sooner or later, and attendance to staid academic conferences like NIPS sooner or later will revert back to a smaller group of academics and intellectuals who are truly interested in the subject over the long term.[a] That much is certain.

But we're still in the early stages of a gigantic wave of investment over the next decade or two, as organizations of all sizes find ways to use deep learning in a growing number of applications. Most small businesses, large corporations, nonprofits, and governments are not using deep learning for anything yet.

[a] https://twitter.com/lxbrun/status/908712249379966977

Re: AI winter is well on its way

#368

Post by orwin »

felippee wrote: post #137
tim333 wrote: post #109

Earlier quoted context omitted.

>Deepmind hasn't shown anything breathtaking since their Alpha Go zero They went on to make AlphaZero, a generalised version that could learn chess, shogi or any similar game. The chess version beat a leading conventional chess program 28 wins, 0 losses, and 72 draws. That seemed impressive to me. Also they used loads of compute during the training but not so much during play.(5000 TPUs, 4TPUs). Also it got better th…

It's not like humanity really needs another chess playing program 20 years after IBM solved that problem (but now utilizing 1000x more compute power). I just find all these game playing contraptions really uninteresting. There are plenty real world problems to be solved of much higher practicality. Moravec's paradox in full glow.

The fact that it beat Stockfish9 is not what is impressive with AlphaZero.

What was impressive was the way Stockfish9 was beaten. AlphaZero played like a human player, making sacrifices for position that stockfish thought were detrimental. When it played as white, the fact that is mostly started with the Queen pawn (despite that the King pawn is "best by test") and the way AlphaZero used Stockfish pawnstructure and tempo to basicaly remove a bishop from the game was magical.

Yes, since its a game, it's "useless", but it allowed me (and i'm not the only one) to be a bit better at chess. It's not world hunger, not climate change, it's just a bit of distraction for some people.

PS: I was part of the people thinking that Genetic algorithm+deep learning was not enough to emulate human logical capacities, AlphaZero vs Stockfish games made me admit i was wrong (even if i still think it only works inside well-defined environments)

Re: AI winter is well on its way

#369

Post by evrydayhustling »

felippee wrote: post #86
evrydayhustling wrote: post #71

Earlier quoted context omitted.

More compute -> more precision is just one field's definition of scalable... Saying that DNNs can't get better just by adding GPUs is like complaining that an apple isn't very orange. To generalize notions of scaling, you need to look at the economics of consumed resources and generated utility, and you haven't begun to make the argument that data acquisition and PhD student time hasn't created ROI, or that ROI on th…

OK, the definition of scalable is crucial here and it causes lots of trouble (this is also response to several other posts so forgive me if I don't address your points exactly). Let me try once again: an algorithm is scalable if it can process bigger instances by adding more compute power. E.g. I take a small perceptron and train it on pentium 100, and then take a perceptron with 10x parameters on Core I7 and get bet…

I appreciate the engagement in making this argument more concrete. I understand that you are talking about returns on compute power.

However, your last paragraph about how investors view deep learning does not describe anyone in the community of academics, practitioners and investors that I know. People understand that the limiting inputs to improved performance are data, followed closely by PhD labor. Compute power is relevant mainly because it shortens the feedback loop on that PhD labor, making it more efficient.

Folks investing in AI believe the returns are worth it due to the potential to scale deployment, not (primarily) training. They may be wrong, but this is a straw man definition of scalability that doesn't contribute to that thesis.

Re: AI winter is well on its way

#370

Post by hannasanarion »

some_account wrote: post #242
felippee wrote: post #137

Earlier quoted context omitted.

It's not like humanity really needs another chess playing program 20 years after IBM solved that problem (but now utilizing 1000x more compute power). I just find all these game playing contraptions really uninteresting. There are plenty real world problems to be solved of much higher practicality. Moravec's paradox in full glow.

Tell me about it. The brightest minds are working on ads, and we have AI playing social games. Can AI make the world better? It can, but it won't since we are humans, and humans will weaponize technology every chance it gets. Of course some positive uses will come, but the negative ones will be incredibly destructive.

Just because you haven't seen humongous publicity stunts involving pratical uses of AI doesn't mean they aren't being deployed. My company using similar methods to warn hospitals about patients with high probability of imminent heart attacks and sepsis.

The practical uses of these technologies don't always make national news.

I'm sure you would also have scoffed at the "pointless impractical, wasteful use of our brightest minds" to make the the Flyer hang in the air for 30 yards at Kitty Hawk.

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