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amkkma

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twitter.com 1y ago

CosineAI coding agent tops software engineering bench

amkkma
1pts0
news.ycombinator.com 2y ago

Task Management for Tech Startup

amkkma
1pts3
imaginativeclinician.substack.com 2y ago

Musings on long Covid and the epistemology of medicine

amkkma
1pts1
github.com 2y ago

Formal specifications and static checking of interfaces in Julia

amkkma
4pts0
github.com 2y ago

Composable static typing, proofs and formal verification for Julia

amkkma
2pts0
news.ycombinator.com 3y ago

Advice for new data scientist at mobile app startup

amkkma
1pts0
huijzer.xyz 4y ago

Why I still recommend Julia

amkkma
219pts204
plutojl-preview.netlify.app 4y ago

Pluto: A Simple, reactive programming environment for Julia

amkkma
2pts0
www.youtube.com 4y ago

Dex: A new array oriented research language from Google

amkkma
5pts2
www.youtube.com 4y ago

The GPGPU developer experience has a long way to go

amkkma
10pts1
computationalthinking.mit.edu 4y ago

MIT Introduction to Computational Thinking

amkkma
2pts0
github.com 4y ago

Julia PR: Separate codegen/LLVM from runtime for static compilation

amkkma
3pts0
juliaacademy.com 4y ago

Decision Making Under Uncertainty with POMDPs.jl

amkkma
87pts9
juliacomputing.com 4y ago

Julia Computing funded by DARPA to Build AI-Based Digital Phased Arrays w/ GPUs

amkkma
17pts3
compiler-research.org 4y ago

A brief History of Julia's C++ REPL and interop [pdf]

amkkma
3pts3
frankschae.github.io 4y ago

AbstractDifferentiation.jl for AD-back end agnostic code

amkkma
1pts0
www.youtube.com 4y ago

Bpfnative.jl: eBPF/Linux kernel programming in Julia

amkkma
2pts0
www.youtube.com 4y ago

State of Julia and Roadmap

amkkma
4pts0
www.youtube.com 5y ago

Multiple Dispatch vs. Multi Parameter Function Overloading

amkkma
1pts0
juliafolds.github.io 5y ago

Efficient and safe approaches to mutation in data parallelism

amkkma
1pts0
twitter.com 5y ago

PClean: Bayesian Data Cleaning at Scale with Domain-Specific Prob Programming

amkkma
1pts0
alan-turing-institute.github.io 5y ago

MLJ.jl: A Julia package for composable machine learning

amkkma
234pts56
plutojl.org 5y ago

PlutoCon 2021

amkkma
40pts6
computationalthinking.mit.edu 5y ago

MIT's introduction to computational thinking Spring 2021

amkkma
5pts0
github.com 5y ago

Jet.jl: A WIP compile time type checker for Julia

amkkma
146pts19
genieframework.com 5y ago

Genie: The highly productive Julia web framework

amkkma
2pts0
juliafolds.github.io 5y ago

A quick introduction to data parallelism in Julia

amkkma
160pts15
juliagpu.org 5y ago

Julia mixed precision GEMM codegen meets and exceeds CUBLAS

amkkma
4pts0
andreaskroepelin.de 5y ago

The missing harm of manual dispatch in Julia

amkkma
102pts39
twitter.com 5y ago

Grant of 3 blue 1 brown tutoring free MIT Computational Thinking course in Julia

amkkma
5pts0
Zed AI 2 years ago

Hey! I really see the power in Zed and the extensibility and simplicity. Great approach.

I posted this above, but want you to see it:

Two areas where I think Zed might fall behind: Cursor Tab is REALLY good and probably requires some finetuning/ML chops and some boutique training data.

For composer, there's going to be more use of "shadow workspace" https://www.cursor.com/blog/shadow-workspace to create an agentic feedback loop/ objective function for codegen, along with an ability to navigate the language server and look up definitions and just generally have full context like an engineer

Also, cursor has a model agnostic apply model, whereas you all are leaning on claude.

Any plans to address this from the core team or more of a community thing? I think some of this might be a heavy lift

I really like the shared context idea, and the transparency and building primitives for an ecosystem

Zed AI 2 years ago

Two areas where I think Zed might fall behind: Cursor Tab is REALLY good and probably requires some finetuning/ML chops and some boutique training data.

For composer, there's going to be more use of "shadow workspace" https://www.cursor.com/blog/shadow-workspace to create an agentic feedback loop/ objective function for codegen along with an ability to navigate the language server and look up definitions and just generally have full context like an engineer. Are there plans for the same in zed?

Also, cursor has a model agnostic apply model, whereas you all are leaning on claude.

Zed AI 2 years ago

I think Zed is starting with a more transparent elegant foundations and then they'll build in more optional magic from there. For example, they're working on automatic codebase RAG

Anyone know how the hardware compares to the latest mac laptops for running LLMs locally? (compute and vram, shared or otherwise)

Don't forget ten years of schooling to be bad at formal methods to step out of that decision tree:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237793/ https://blogs.cornell.edu/info2040/2014/11/12/doctors-dont-k... https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3016704/ https://www.overcomingbias.com/p/doctor-there-arhtml

And many more.

go to r/residency or other doctor forums if you want to see the most repugnant combination of dunning kruger and condescension

Sorry. I have a brilliant, extremely driven friend who did undergrad at an ivy. After getting covid, She had to drop out of her grad school program and her new life is a shell compared to what it used to be like. 2 years later, and there's a tiny fraction of improvement which she attributes to extreme rest. I forward her literature about emerging LC treatments and mechanisms of which her physicians are laughably ignorant.

It's a sad state of affairs.

But it's still not comparable to GPT 4, nor will it likely be for some time at least. And by the time we have GPT 4 class open source models, I'd imagine there'd be significant advancements in closed source models, such as inference time symbolic reasoning using MCTS, something google is working on for gemini...or just bigger/better architectures, data etc

Very interesting. Can you please elaborate or give a TLDR on the linguistics angle here?

Does it have something to do with grounding or implicit knowledge/ connotations and context?

Various people have expressed skepticism of needing language level traits, but it's in vogue to be writing interface packages with no top level abstract types (see Tables.jl) because we don't have some way to extensibly express being part of multiple type trees.

It's challenging enough that Abstract Types have no interface specs (it's claimed that this is a feature, allows interfaces to develop over time), but it's even tougher when things get even looser with this new trend towards have untyped functions...even various interface package maintainers themselves have said the current state of affairs is difficult.

And if we do want to opt into abstract typing, you're going to be inheriting lots of functionality that could be better broken into smaller typeclass like components (see AbstractArray).

I think Julia is screaming for some capability to break up Abstract types and being able to inherit from multiple kinds of things, along with specified interfaces with these things.

The problem is that this is very difficult, given the complex subtyping system and multiple dispatch. Adding more complexity exacerbates already present method and typing decidability issues. People are working on this on the periphery, but I hope it can become a priority of the core team and that it's solvable.

Thanks.

regarding "improving a lot of the underlying compiler infrastructure overall"

Is the compiler plugin project still active/ planned?

to add, as you know, this is part of a more general problem about type level programming vs write your own compiler vs the non composability of DSLs, where Julia folks in various other non ML domains like PPLs and fancy arrays have been wondering about how to do things that get compiled away, without relying on compiler heuristics or generated function blowups: https://julialang.zulipchat.com/#narrow/stream/256674-compil...

Another non ML example I discussed with some Probprog folks is that there was an arxiv review of PPLs and Julian ones that heavily rely on macros don't compose well within and across packages. The same mechanism for composability which Dex uses for parallelism and AD (effect handlers) is what new gen PPLs in jax and Haskell are using for composable transformable semantics, so maybe that's worth looking into.

We've been having some discussions about how to bring that to Julia, but stalled on engineering time and PL knowledge. Eventually wanted to talk to the core team about it with proposal in hand, but never got there. Let me know if you'd like to talk to some of those folks who have been involved in the discussions as you design the new compiler plugin infra.

https://julialang.zulipchat.com/#narrow/stream/256674-compil...