yea exactly
HN user
amkkma
Based on this, what is the outlook for software dev generally, and junior and mid level devs?
Great. They also have other blog posts with product roadmap and research directions https://www.cursor.com/blog/problems-2024 you should look at, and an AI engineer conference talk which goes into their vision: https://youtu.be/6g28WpZbF1I?si=MkHgxMDMjxxOHtcZ
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
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.
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)
I didn't realize they had that option. In general, I still find absurdity in what an NP can do vs an unmatched doctor. That's entirely incoherent.
Also, it's laudable what rads is doing, but didn't the AMA lobby for less residency spots?
You can't legally practice as a primary care physician without one year of internship, after which you get unrestricted licensed. If you're unmatched, no internship. Is that not correct?
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
Why have residency spots shrunk per capita? Why do unmatched grads have to work at mcdonalds but NP's and PA's can practice with more latitude than some residents?
(serious questions)
Good point
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.
Do you know the rate of long term sequalae for flu and how it compares to covid?
"nonsense"
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
What about LMQL?
super bonkers!
What do you think about Haystack vs LangChain?
How does this compare with lmql?
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?
Is there any hope of understanding this with just calc and linalg knowledge?
What about "data science" or applied machine learning? Or even ML research?
Sounds like he's ultimately agnostic on the issue:
" But I’m agnostic about whether at the end of this programme of trying to account in physical terms for properties of experience, there will still be some residue of mystery left, something more to explain."
https://www.theguardian.com/science/2021/aug/21/neuroscienti...
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.
Dex proves indexing correctness without a full dependent type system, including loops.
See: https://github.com/google-research/dex-lang/pull/969 and https://github.com/google-research/dex-lang/blob/5cbbdc50ce0... for examples
Thanks.
regarding "improving a lot of the underlying compiler infrastructure overall"
Is the compiler plugin project still active/ planned?
You think python is free of those things?
Cool! How big were the emitted nim binaries?
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...