There is a relatively widely adopted tool (100+ citations, >500k invocations collected via telemetry) for mass spectrometry-based proteomics written in Rust, and quite a few others in the works.
The title is >Create value for others and don’t worry about the returns.
Isn't being an anti-masker the opposite of this viewpoint? Literally saying, I only care about the returns for myself, even if creates negative value for others.
As someone who is "into" programming languages (and making toy implementations of them), I think some of the most important macros are along the lines of Rust/Haskells `derive/deriving` for quickly enabling serialization, printing etc. Using a language without such capability quickly becomes frustrating once you move to any kind of "real" task.
In any kind of real task, serialization is not the hard part.
If you can write a meta program for it, you can execute that in CI and spit out generated code and be done with it. This is a viable approach in any programming language that can print strings to files.
It’s not frustrating, but maybe it feels tacky. But then you shrug and move on to the real task at hand.
Dealing with nested association lists is a pain. this let you write your code with a dot notation like jq.
Macros are not only for solving a particular task (serialization, dependency injection, snippets,…) they let you write things the way it makes sense. Like having html-flavored lisps for template, sql-flavored lisp for query,… Lisp code is a tree, and most languages are trees, so you can bring easily their semantic in lisp.
You say that, but I've run into real production problems which were ultimately caused by bad serialization tooling. Language semantics are never going to be your biggest problem, but rough edges add up and do ultimately contribute to larger issues.
As someone who has been primarily writing Rust for the past 8+ years, I am actually unaware of any political drama surrounding Rust. It's just a programming language.
The tells are in the cadence. And the not x but y. And the last line that basically says nothing, while using big words. It's like "In conclusion", but worded differently. Enough tells for me to click on their history. They have the exact same cadence on every comment. It's a bit more sophisticated than "chatgpt write a reply", but it's still 100% aigen. Check it out, you'll see it after a few messages in their history.
No, it doesn't. The "I'm an expert at AI detection" crowd likes to cite things like "It's not X, it's Y" and other expression patterns without stopping to think that perhaps LLMs regurgitate those patterns because they are frequently used in written speech.
I assign a <5% probability that GP comment was AI written. It's easy to tell, because AI writing has no soul.
The message is 100% AI written. And if you click on their username and check their comment history you'll see that ALL their comments are "identical". Just do it, you'll see it by the 5th message. No one talks like that. No one talks like that on every message.
Exactly, if a comment just feels a little off but you're unsure, do a quick scan of the profile, takes 15-30 seconds at most to get sufficient signal.
If it's actually AI, the pattern becomes extremely obvious reading them back-to-back. If no clear pattern, I'll happily give them the benefit of the doubt at that point. I don't particularly care if someone occasionally cleans up a post with an LLM as long as there is a real person driving it and it's not overused.
The other day on Reddit I saw a post in r/sysadmin that absolutely screamed karma farming AI and it was really depressing seeing a bunch of people defending them as the victim of an anti-AI mob without noticing the entire profile was variations of generic "Does anyone else dislike [Tool X], am I alone? [generic filler] What does everyone else think?" posts.
Looking at their profile I'm inclined to agree. But I think in isolation, this one post isn't setting off enough red flags for me. At the very least, they aren't just using default prompts.
I think at this point it's not easy to accurately detect whether or not something is AI written. A real person can definitely write like this. In fact, that's probably where the LLMs got their writing style from.
It's not totally novel, but it's very cool to see the continued simplification of protein folding models - AF2 -> AF3 was a reduction in model architecture complexity, and this is a another step in the direction of the bitter lesson.
I’m not sure AF3’s performance would hold up if it hadn’t been trained on data from AF2 which itself bakes in a lot of inductive bias like equivariance
Protein folding is in no way "solved". AlphaFold dramatically improved the state-of-the-art, and works very well for monomeric protein chains with structurally resolved nearest neighbors. It abjectly fails on the most interesting proteins - just go check out any of the industry's hottest undrugged targets (e.g. transcription factors)
> When it comes to very complicated things, physics tends to fall down and we need to try non-physics modeling, and/or come up with non-physics abstraction.
"When things are complicated, if I just dream that it is not complicated and solve another problem than the one I have, I find a great solution!"
Joking apart, models that can help target potentially very interesting sub phase space much smaller than the original one, are incredibly useful, but fundamental understanding of the underlying principles, allowing to make very educated guesses on what can and cannot be ignored, usually wins against throwing everything at the wall...
And as you are pointing out, when the complex reality comes knocking in it usually is much much messier...
I have your spherical cow standing on a frictionless surface right here, sir. If you act quickly, I can include the "spherical gaussian sphere" addon with it, at no extra cost.
[1] https://github.com/lazear/sage