One model to learn them all
blog.acolyer.org
One model to learn them all
1–10 of 51 posts
Re: One model to learn them all
#2Wow. Can someone pull a Hacker News and explain to me why I'm allowed to be super pessimistic about this result? I want to believe.
Re: One model to learn them all
#3Wow. Can someone pull a Hacker News and explain to me why I'm allowed to be super pessimistic about this result? I want to believe.
To me it looks like they just took a bunch of specialized NN classifiers and glued them together. Not to belittle their work, this is still impressive and an important step towards generalized machine intelligence, but we're still a very long way off.
The next level above this would be to give it some input and without telling the classifier what to do with it, it decides which task it's supposed to do on its own, and then executes.
Re: One model to learn them all
#4Wow. Can someone pull a Hacker News and explain to me why I'm allowed to be super pessimistic about this result? I want to believe.
At first glance, these results appear fairly impressive as far as deep learning transfer studies go.
However, standard caveats about the limits of those approaches should still apply: e.g. https://spectrum.ieee.org/cars-that-think/transportation/sen...
In other words, I don't think MultiModel will be immune to fairly straightforward adversarial image attacks (although you might need a different adversarial network to generate them).
Furthermore, the problems being addressed by MultiModel (image recognition, natural language processing, machine translation) are problems that already have fairly robust deep learning results.
I'd be more interested if MultiModel showed significantly better results on problem areas that are currently difficult for standard deep learning approaches.
Re: One model to learn them all
#5Wow. Can someone pull a Hacker News and explain to me why I'm allowed to be super pessimistic about this result? I want to believe.
To me it looks like they just took a bunch of specialized NN classifiers and glued them together. Not to belittle their work, this is still impressive and an important step towards generalized machine intelligence, but we're still a very long way off. The next level above this would be to give it some input and without telling the classifier what to do with it , it decides which task it's supposed to do on its own, a…
Wouldn't you "just" need to train a classifier on top to select the best fitting model? Or use ensemble learning? I dunno. My point is that it wouldn't be much more generalized even without that input.
Re: One model to learn them all
#6Seriously 'one model to learn them all'? Isn't that a tiny bit overreaching?
The results are not very surprising after the Google translate post about multi language translation.
Re: One model to learn them all
#7One model to rule them all, one model to find them,
One model to bring them all, and in the darkness bind them.
Re: One model to learn them all
#8Earlier quoted context omitted.
To me it looks like they just took a bunch of specialized NN classifiers and glued them together. Not to belittle their work, this is still impressive and an important step towards generalized machine intelligence, but we're still a very long way off. The next level above this would be to give it some input and without telling the classifier what to do with it , it decides which task it's supposed to do on its own, a…
Wouldn't you "just" need to train a classifier on top to select the best fitting model? Or use ensemble learning? I dunno. My point is that it wouldn't be much more generalized even without that input.
Yeah, that would just be one step out of the however dozens/hundreds/thousands more to go before AGI.
Re: One model to learn them all
#9One model to overfit it all
Re: One model to learn them all
#10Wow. Can someone pull a Hacker News and explain to me why I'm allowed to be super pessimistic about this result? I want to believe.
At first glance, these results appear fairly impressive as far as deep learning transfer studies go. However, standard caveats about the limits of those approaches should still apply: e.g. https://spectrum.ieee.org/cars-that-think/transportation/sen... In other words, I don't think MultiModel will be immune to fairly straightforward adversarial image attacks (although you might need a different adversarial network to…
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