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The future of Deep Learning frameworks

neel04.github.io

11–20 of 113 posts

Re: The future of Deep Learning frameworks

#11
PyTorch is a generationally important project. I've never seen a tool that is so inline with how researchers learn and internalize a subject. Teaching Machine Learning before and after its adoption has been a completely different experience. Never can be said enough how cool it is that Meta fosters and supports it.

Viva PyTorch! (Jax rocks too)

Re: The future of Deep Learning frameworks

#12

PyTorch is the javascript of ML. sadly "worse is better" software has better survival characteristics even when there is consensus that technology X is theoretically better

Nothing is even theoretically better than Javascript for its intended use cases, web frontends and backends. Mainly because it went all-in on event loop parallelism early-on, which isn't just for usability but also performance. And didn't go all-in on OOP unlike Java, and has easy imports/packages unlike Python. It has some quirks like the "0 trinity," but that doesn't really matter. No matter how good you are with something else, it still takes more dev time ($$$) than JS.

Now it's been forever since I used PyTorch or TF, but I only remember TF 1.x being more like "why TF isn't this working." At some point I didn't blame myself, I blamed the tooling, which TF2 later admitted. It seemed like no matter how skilled I got with TF1, it'd always take much longer than developing with PyTorch, so I switched early.

Re: The future of Deep Learning frameworks

#13
> I believe that all infrastructure built on Torch is just a huge pile of technical debt, that will haunt the field for a long, long time.

... from the company that pioneered the approach with tensorflow. I've worked with worse ML frameworks, but they're by now pretty obscure; i cannot remember (and i am very happy about it) the last time i saw MXNet in the wild, for example. You'll still find Caffe on some embedded systems, but you can mostly sidestep it.

Re: The future of Deep Learning frameworks

#14

PyTorch is the javascript of ML. sadly "worse is better" software has better survival characteristics even when there is consensus that technology X is theoretically better

Nothing is even theoretically better than Javascript for its intended use cases, web frontends and backends. Mainly because it went all-in on event loop parallelism early-on, which isn't just for usability but also performance. And didn't go all-in on OOP unlike Java, and has easy imports/packages unlike Python. It has some quirks like the "0 trinity," but that doesn't really matter. No matter how good you are with s…

You don't think its possible to (even theoretically) improve on javascript for its intended use case? What a terrific lack of imagination.

Typescript and Elm would like a word

Re: The future of Deep Learning frameworks

#15
post #14

Earlier quoted context omitted.

Nothing is even theoretically better than Javascript for its intended use cases, web frontends and backends. Mainly because it went all-in on event loop parallelism early-on, which isn't just for usability but also performance. And didn't go all-in on OOP unlike Java, and has easy imports/packages unlike Python. It has some quirks like the "0 trinity," but that doesn't really matter. No matter how good you are with s…

You don't think its possible to (even theoretically) improve on javascript for its intended use case? What a terrific lack of imagination. Typescript and Elm would like a word

No, I said there's nothing that exists right now that's theoretically better. Typescript isn't. It'd be great if TS's type inference were smart enough that it basically takes no additional dev input vs JS, but until then, it's expensive to use. It's also bolted on awkwardly, but that's changing soon. Could also imagine JS getting some nice Py features like list comp.

Also, generally when people complain that JS won the web, it's not because they prefer TS, it's cause they wanted to use something else and can't.

Never used Elm, but... no variables, kinda like Erlang, which I've used. That has its appeal, but you're not going to find a consensus that this is better for web.

Re: The future of Deep Learning frameworks

#16
post #9

Jax is dead, long live PyTorch. PyTorch has _twenty times_ as many users as Jax. Any rumors of its death are highly exaggerated

They used to say the same thing about Perl and Python

Downvoted. Hmmm. I’m a little tired so I don’t want to go into detail. However, I was a Perl programmer when Python was rising. So, needless to say, having a big lead doesn’t matter.

Please learn from history. A big lead means nothing.

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