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byt143on ICJ orders Israel to prevent genocide in Gaza, stops short of ordering ceasefire

So Israel can't enjoy the same right to self defense that any other state would? They can't conduct a war in an urban environment with an actual intentionally genocidal enemy, and must resort to targeted assassinations? That standard is absurd. Surely you can admit some middle ground ,if you're discussing in good faith.

byt143on Why do some people feel tired all the time?

Second !

byt143on On the link between Lyme disease and bioweapons (2019)

How about the misery of a loved one going untreated, undiagnosed and dismissed by physicians with a facile understanding of chronic multi system disease dynamics. People who do that are usually ones who cannot find physical relief elsewhere.

byt143on On the link between Lyme disease and bioweapons (2019)

Don't expect a good answer. That brand of skepticism is performative rationality devoid of actual critical thinking.

byt143on LLMs Unleashed: The Power of Fine-Tuning

It's really depressing that a handful of big corporations will be able to exert such control over labor and productivity

byt143on LLMs Unleashed: The Power of Fine-Tuning

What tasks?

byt143on GPT-4 API General Availability

What's the difference between chat and instruction tuning?

byt143on Mojo – a new programming language for AI developers

How does mojo handle function polymorphism and abstraction? Julia uses multiple dispatch, Haskell type classes etc

Edit: I see you're going to have protocols/ traits. Can those be specializes/monomoprhized at function call time like Julia abstract types?

And how about function specialization? Will functions be attached to structs in a single dispatch fashion or free floating multimethods?

byt143on An example of LLM prompting for programming

Interesting. What's your prompt?

byt143on NeRF: Representing scenes as neural radiance fields for view synthesis

If you're only looking for one novel view, can it use less views that are close to the novel one?

byt143on Google/Trax – Understand and explore advanced deep learning

Even then shape errors would require a dependent type system not found in most static languages.

byt143on Building a neural network from scratch in Haskell

What are your concerns around the support / dev?

Google has a fairly sizable team around it, it has a fast path to adoption by the large pool of swift devs and fast.ai, and of course, google hype.

Chris leaving doesn't seem to be an issue: https://twitter.com/clattner_llvm/status/1222032740897284097

byt143on JuliaLang: The Ingredients for a Composable Programming Language

It does not have macros.

byt143on JuliaLang: The Ingredients for a Composable Programming Language

Why can't you just have the higher level representation of the code available and just recompile everything?

byt143on JuliaLang: The Ingredients for a Composable Programming Language

Perhaps this helps? https://github.com/apple/swift-evolution/blob/master/proposa...

and this

https://twitter.com/jckarter/status/1202260205074968578

byt143on JuliaLang: The Ingredients for a Composable Programming Language

So it's a package, not a language issue?

Here's a revamp based on protocols https://github.com/apple/swift-numerics

byt143on JuliaLang: The Ingredients for a Composable Programming Language

That makes sense. Swift is also way too complex and syntatically noisy imo. I like that Julia has a smaller set of very powerful abstractions.

Though isn't point (2) just a convention thing? Protocols can refine other protocols. So in S4TF there's a layer protocol and an RNN protocol which extends that, IIRC.

byt143on JuliaLang: The Ingredients for a Composable Programming Language

This can be done better with traits in Julia, which are more powerful, safer and faster.

See here: https://white.ucc.asn.au/2018/10/03/Dispatch,-Traits-and-Met...

byt143on JuliaLang: The Ingredients for a Composable Programming Language

Thanks. I mean in julia you can use traits for that, but it's not built in (yet). Though there's no speed penalty, as you probably know.

So this is about extending types, but it sounds like swift is strictly "better" then, since it's also statically checked? Or is there something that multiple dispatch gives that substantively better?

I'm trying to get a feel for if the Swift for Tensorflow project will afford the same kind of composability, while keeping static type checking, modules etc (assuming they work out cross module code specialization, which I think is happening).

byt143on JuliaLang: The Ingredients for a Composable Programming Language

Sure, but I'm more looking for something from the swift side of whether Swift can do the same sort of composable generic programming.

byt143on JuliaLang: The Ingredients for a Composable Programming Language

Anyone know how this compares to swift and its protocols etc?

byt143on Standardizing OpenAI’s deep learning framework on PyTorch

Julia gives you the best of both worlds. And more.

All those pretty function like things you see above are actually callable objects that can be introspected, intercepted and dispatched on...so you can mix and match pure object abstractions, pure function abstractions and objects with function like properties depending on the usecase.

This is because Julia's philosophy is to make Differentiable Programming a completely seamless and normal programming paradigm inter-operable with all standard code patterns.

And all this is only possible because of a unique mix of amazing reflection, code gen (including hooking into the compiler from third party packages, allowing source to source autodiff and GPU codegen), fast generic/parametric polymorphism even across packages, multiple dispatch and macros, among other technologies.

It's not quite at the stage of "write any normal julia code and it just works", as there are some rough edges being worked out, but that's the vision and it's even now it's leaps and bounds above pytorch.

byt143on Standardizing OpenAI’s deep learning framework on PyTorch

https://forums.fast.ai/t/swift-for-tensorflow/40167/72

byt143on Standardizing OpenAI’s deep learning framework on PyTorch

https://twitter.com/clattner_llvm/status/1222032740897284097

Jeff Dean seems to disagree.

Also, I think it hasn't picked up steam because it just isn't mature enough yet

byt143on Pandas 1.0

>The people that maintain infrastructure/maintenance support for Julia apps are almost ready to quit their jobs. It sucks so bad.

Any specific examples?

byt143on Pandas 1.0

To which version of Julia are you referring? All of those things are much improved now.

byt143on Chris Lattner to Lead SiFive Platform Engineering Team

Even in swift it isn't "turtles all the way down".

The AD stuff is hardcored into the C++ guts of the compiler, whereas Julia's source to source autodiff accesses a compiler pass from a fully Julia user package.

Aside from making it easier to hack and improve the AD system as just a Julia user, this capability enables other package program transforms like that in https://github.com/MikeInnes/Poirot.jl for prob programming.

So Julia is already further ahead in that regard and it's more hackable.

byt143on Chris Lattner to Lead SiFive Platform Engineering Team

Would you be open to doing a Fast.ai initiative in Julia? If so, what would that take?

byt143on What is Rust and why is it so popular?

Not sure the data supports that ,: https://juliacomputing.com/blog/2020/01/06/january-newslette...

byt143on Why I use R

Better static compilation and compile times which will reduce the time to first plot.