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Swift for TensorFlow Shuts Down

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Re: Swift for TensorFlow Shuts Down

#91
post #26

It's a shame. I had high hopes at the beginning that S4TF - and the investment in Swift from Google - would help Swift break out of the iOS ghetto and cement it as a mainstream language. Swift's a delightful language to use. It has a lot of the nice things about Rust's type system, but is a heck of a lot easier to use at the expense of a bit of performance. For a lot of use cases, I think this is a great value propos…

I agree and am also disappointed. On the other hand, I really don't miss Swift outside of iOS because of Rust and Kotlin.

I wonder if Kotlin is too far from "arms length" from the low level details in your mind? Because other than that, I actually prefer the language over Swift, generally.

Re: Swift for TensorFlow Shuts Down

#92
post #6

Swift now being a 100% Apple-sponsored & owned project again makes me a bit nervous. Anyone knows if chris latner is at least using swift in his new company ? I have the feeling swift never really worked in the server side, data science is now officially a failure, and all that is left is now a very niche market of 100% native mobile development. I love this language, but i'm eager to see it handled by a proper found…

> I have the feeling swift never really worked in the server side

Vapor [1] is wonderful to work with and has a large user base. Apple is also putting significant resources into Server Side Swift with Swift NIO [2]. Lots of really cool stuff happening in that ecosystem

[1]: https://vapor.codes [2]: https://github.com/apple/swift-nio

Re: Swift for TensorFlow Shuts Down

#93
post #51
post #6

Swift now being a 100% Apple-sponsored & owned project again makes me a bit nervous. Anyone knows if chris latner is at least using swift in his new company ? I have the feeling swift never really worked in the server side, data science is now officially a failure, and all that is left is now a very niche market of 100% native mobile development. I love this language, but i'm eager to see it handled by a proper found…

> Swift now being a 100% Apple-sponsored & owned project again makes me a bit nervous. Are you nervous about a language that is designed and supported by the largest and most successful company in the world? > very niche market of 100% native mobile development That "niche" is at least 1.5 billion devices. Devices bought by the 1.5 billion richest people in the world because they like them, not because their employer…

The Uber engineering disaster story from 2 months ago seems to suggest that Apple lacks dogfooding Swift internally: https://news.ycombinator.com/item?id=25373462

Re: Swift for TensorFlow Shuts Down

#94
post #63

Earlier quoted context omitted.

I disagree with the pitch, but the pitch I heard when this was announced was: * Swift lets you write code that's as concise as Python while still being fast, and therefore allows you to get away from the problem of having to write ML code in multiple languages (TensorFlow is actually mostly C++, which makes it difficult for a Python developer to debug.) * That the lack of static typing is a major pain point in Python…

> Swift lets you write code that's as concise as Python while still being fast, > (TensorFlow is actually mostly C++, which makes it difficult for a Python developer to debug.) To be honest, if I had to choose between Python and Swift I'd still choose Python. Swift is a nice evolution from Obj-C and all but it is nowhere near as simple as Python, or Ruby, or PHP, or Javascript, or Kotlin. And Apple's documentation of…

I think considering swift as merely an evolution of obj-c is a drastic underestimation. Swift is a very nice language in its own right. Having spent time with most of the languages you've mentioned, while the learning curve might be a bit steeper, I think Swift is much easier to manage a medium or large project with than any of those options with the exception of maybe Kotlin, and personally I find some of the design choices a bit better in Swift than in Kotlin.

Re: Swift for TensorFlow Shuts Down

#95
post #69
post #26

It's a shame. I had high hopes at the beginning that S4TF - and the investment in Swift from Google - would help Swift break out of the iOS ghetto and cement it as a mainstream language. Swift's a delightful language to use. It has a lot of the nice things about Rust's type system, but is a heck of a lot easier to use at the expense of a bit of performance. For a lot of use cases, I think this is a great value propos…

>I think Serverless would be another ideal use-case for Swift, where the productivity, clarity and correctness tools it offers would be a huge benefit. Oh yes, I would love to have Swift framework for Firebase on server, not only for iOS. Its atrocity to write the server logic in NodeJS after making the user App in Swift. Every time I switch from Swift to JS I deeply appreciate the beauty of Swift. On swift I do much…

Have you looked at Vapor?

Re: Swift for TensorFlow Shuts Down

#97
post #69

Earlier quoted context omitted.

>I think Serverless would be another ideal use-case for Swift, where the productivity, clarity and correctness tools it offers would be a huge benefit. Oh yes, I would love to have Swift framework for Firebase on server, not only for iOS. Its atrocity to write the server logic in NodeJS after making the user App in Swift. Every time I switch from Swift to JS I deeply appreciate the beauty of Swift. On swift I do much…

Have you looked at Vapor?

Yep, Vapor looks nice but I want to use Firestore, so I need a reliable integration of Firestore with Vapor and there isn't one. I rely on listening for live data entries and updates on the Firestore, processing those and putting them back.

I'm doing it on NodeJS currently and I hate it. I used to like JS but Swift showed me that there's more, there's beauty in the world.

The only thing I miss on Swift is async/await and that's coming.

Re: Swift for TensorFlow Shuts Down

#98
post #56

Swift for TensorFlow was a nice idea on paper, but you need more than ideas to push a project forward. You need people who actually want to use your product. For all the comments on HN about how great Swift was, there were hundreds if not thousands of ML engineer and research scientist who did not know it existed and frankly did not really care about it either. Swift for Tensorflow was not addressing the issues of ML…

It's interesting to compare Swift to Julia here – Julia had a base of people who absolutely loved it from the 0.2 days, and has managed to draw many users from Python/Matlab/R. There are many reasons for that, but overall Julia had something that really appealed to scientists: syntax they liked + competitive-with-C performance. In contrast, S4TF's target audience seems to have been Swift developers, and they didn't r…

Precisely, S4TF felt like a startup product with no market research. It really felt like the only reason Swift was chosen was because the main dev created it.

Re: Swift for TensorFlow Shuts Down

#99
post #82

Earlier quoted context omitted.

I suspect that we'll be seeing ObjC for a long time, as the lower-level system language for Apple devices. I know that Apple still uses it for much of their system programming. No idea if that's by choice, or legacy (possibly both). I was looking at the upcoming async/await stuff for Swift, and it's still not comparable to some of the lower-level threading systems. That said, I have not done system programming for a…

We'll see it in legacy code for a long time, sure, but there's every indication that all new Apple frameworks are being written in Swift. Anyone starting a new project in Objective-C is in the minority.

> there's every indication that all new Apple frameworks are being written in Swift

There's no such indication. "The number of binaries using Objective-C is still growing with each iOS release." https://blog.timac.org/2020/1019-evolution-of-the-programmin...

Re: Swift for TensorFlow Shuts Down

#100
It seems this was written on the wall once Chris Lattner left the project. It's a shame since this could have been a real breakthrough in machine learning combining performance and ease. But the success of JAX means Google probably doesn't feel the investment is worth it.
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