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“Deep Learning has outlived its usefulness as a buzz-phrase”

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Re: “Deep Learning has outlived its usefulness as a buzz-phrase”

#3
[Text from post]

OK, Deep Learning has outlived its usefulness as a buzz-phrase. Deep Learning est mort. Vive Differentiable Programming!

Yeah, Differentiable Programming is little more than a rebranding of the modern collection Deep Learning techniques, the same way Deep Learning was a rebranding of the modern incarnations of neural nets with more than two layers.

But the important point is that people are now building a new kind of software by assembling networks of parameterized functional blocks and by training them from examples using some form of gradient-based optimization.

An increasingly large number of people are defining the network procedurally in a data-dependant way (with loops and conditionals), allowing them to change dynamically as a function of the input data fed to them. It's really very much like a regular progam, except it's parameterized, automatically differentiated, and trainable/optimizable. Dynamic networks have become increasingly popular (particularly for NLP), thanks to deep learning frameworks that can handle them such as PyTorch and Chainer (note: our old deep learning framework Lush could handle a particular kind of dynamic nets called Graph Transformer Networks, back in 1994. It was needed for text recognition).

People are now actively working on compilers for imperative differentiable programming languages. This is a very exciting avenue for the development of learning-based AI.

Important note: this won't be sufficient to take us to "true" AI. Other concepts will be needed for that, such as what I used to call predictive learning and now decided to call Imputative Learning. More on this later....

Re: “Deep Learning has outlived its usefulness as a buzz-phrase”

#6
"See more of Yann LeCun on Facebook" popup, no access to the page. No, I don't want to create a Facebook account to read a blog post.

Perhaps links to walled-garden pages where you need an account and need to be logged in should be prohibited or at least discouraged.

Re: “Deep Learning has outlived its usefulness as a buzz-phrase”

#8

"See more of Yann LeCun on Facebook" popup, no access to the page. No, I don't want to create a Facebook account to read a blog post. Perhaps links to walled-garden pages where you need an account and need to be logged in should be prohibited or at least discouraged.

Agreed. I think many posters here assume that everyone has an account at FB, WSJ, NYT, and so on. The web search trick doesn't work for all of these situations either.

Re: “Deep Learning has outlived its usefulness as a buzz-phrase”

#9
post #5

1. Differentiable Programming is horrible branding. It's hard to say, not catchy, and not as easily decipherable. 2. Isn't the evolution of Deep Networks more advance setups such as GANs, RNNs, and so on?

I like it, at least from the little that I read about it. The name describes the core of what it is: differentiate programs, in order to figure out how changes the the program affect the output and using that for optimization purposes. Do we really need to invent obscure, new names for everything just so that it sounds catchy?

Re: “Deep Learning has outlived its usefulness as a buzz-phrase”

#10

"See more of Yann LeCun on Facebook" popup, no access to the page. No, I don't want to create a Facebook account to read a blog post. Perhaps links to walled-garden pages where you need an account and need to be logged in should be prohibited or at least discouraged.

I had an option to click "not now" to dismiss.
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