Posted by nonmaskable 23 hours ago
Note: Cuda-oxide is similar to Cudarc's host component, but uses a rust-style kernel dialect. Advantage: Share structs between host and device. Disadvantage: Trading standard Cuda kernels for a new, WIP dialect.
I haven't tried the tile API yet; looking forward to it.
The last time I checked, Cuda Oxide was Linux only, and required Async; these are why I haven't tried it yet.
Seems more ergonomic in general though, both approaches they share, compared to cudarc, and less build infrastructure and fiddling with environments, which is great.
Damn even Nvidia is putting out fully Claude-written articles.
Slashdot's spirit shall live somewhere, no? Rent is all-time high and it can only afford here, for now.
Why "even Nvidia"?
They are fully behind using AI for basically everything.
What's next? "Damn, even McDonald's is putting out unhealthy food"
It points to friction rather than cost economics. Same reason we are always surprised why multi billion dollar product companies with millions of install base prefer electron instead of a native app.
People and companies are hungry for knowledge about people's reactions, but the modern internet DOES NOT give an accurate image of people's views.
Only devs think it isn't coming for them, it is empowering and nothing else will happen, no team reductions, nah how come.
They are just better at hiding it or configuring Claude.
I have several skills that reformat text to remove AI-speak tells.
I put the "humanized" output through Pangram and it still comes out as 100% AI generated.
One trade-off is even some obviously LLM text won't get detected by them, but they work really hard to ensure false positives are rare since a false accusation is much worse for society than someone getting away with LLM meatpuppetry.
(Addendum: As I recall, LLM-generated outputs roughly follow Zipf's law, but the distribution still tends to have some subtle distinctions vs human text; pretty interesting, but I don't know where I heard this, so nothing to cite. Sorry.)
But still, this is all very strange because it wasn't that many generations of AI models ago that AI writing was a lot better - I'm talking GPT 4.1, Claude 4.5, that sort of era.
Anthropic newsroom posts on the other hand are carefully constructed and well-written in a way that I have not seen demonstrated by LLMs yet, past or present. I expect that they have well-paid staff who are careful with every detail of their public communications. When you put it that way, it almost feels unfathomable that they wouldn't, doesn't it?
> Anthropic doesn't appear to use Claude for blog posts
My claim is literally the lack of evidence, which, yes, can't prove anything. This claim can be contested easily by showing evidence that they in fact, do appear to be using Claude to write prose in blog posts.
They said:
> Anthropic _absolutely_ does
Sounds pretty certain Anthropic is in fact, using Claude to write blog posts. Enough to emphasize "absolutely". That doesn't read like "I'm going off of vibes", that reads like "I can prove it". So, fine. Prove it. I don't believe it, and I want to hear the proof.
I'm skeptical, but it wouldn't be my first time being wrong. But flatly, if you make claims with this kind of certainty, yes I want to hear your proof.
My point in saying "Even Anthropic doesn't appear to be using Claude for blog posts" was not meant to be some striking revelation, I literally was considering it a prior to make another point. This on the other hand sure does sound like a striking revelation to me, that a lot of people across the Internet would be curious to hear. Like I'm sure these people would be interested:
https://www.reddit.com/r/ClaudeAI/comments/1wdfd92/are_anthr...
I will admit that I am unnecessarily aggressive sometimes, but I wouldn't have changed my response much in any case. If you're going to make a strong claim like this, I want your evidence, not your vibes. Otherwise, the claim should be a lot weaker.
I also realize that this sort of brashness upsets HN a bit, but it is what it is. I pandered comments for votes in my 20s a bit, time to grow up, sometimes people won't like you. Sometimes I feel something deserves a brash response.
that would be pretty cool, you can just get your entire day's calories from one burger
The heck you talking about? How do you think we wrote software for the last 50 years?
And now with AI I’m using it to fact check Claude. And still reading it for myself to understand why other peoples code is written a certain way. It’s basically the most important thing to reference when coding.
Sure today Claude can just read the library code and tell you what a function does or how to do something. But it still won’t tell you why something is a certain way or won’t figure out specifically-designed usage patterns as reliably as the author telling you “this is an example of doing x”
I brushed up on the docs since I haven't touched it in a couple years, explained my understanding of the ob_* functions, and gave him a very brief demo on a PHP playground.
He could have asked any LLM to tell him what that chunk of code did, and to explain the three functions, and instead he reached out to me. That felt _good_. Talking shop has always been a good way for me to form connections, because the pressure to socialize becomes task-oriented and you start to learn about how people think and feel, and that opens up easier paths for actual connection. It was nice.
Just like the Old Internet still exists - niche websites, mailing lists, probably a BBS or two (likely more right?), the pre-LLM world will trudge on, for a time. I hope LLMs actually lead to good things for people in the long run, and for now I personally will remain sparse in my usage of them.
You need the documentation to know why certain things work a particular way, or to know why some relationships or methods are the way they are
It is shocking how much of a differentiator this is. You will discover that the software you’re already using is much more capable than you realized.
I start with reading and exploring documentation first; with the codebase as a secondary tab.
When it’s not LLM generated, documentation is supposed to be easier to read and more insightful than code.
Speak for yourself. I read it.
We are starting to see results indicating cognitive decline due to AI in education, so no, we should do everything possible to ban it except for very limited fields.
LLMs aren't calculators or even computers, their generated output is too flexible, generic and basically starts replacing thinking.
Most likely they should only be allowed during late highschool years or just at university level, when people at least have a chance to learn how to research on their own.
Whether this is a widespread macro trend is another issue, and would be terryfying.
If true, however, it would reflect on the values of the organization: we have spent decades underpaying teachers, and doing a poor job of pretecting schools from frivoluos lawsuits. Add into that, districts have thrown money into new buildings, have been suckered by Big Tech to adopt their policies (common core was pushed by Big Tech and has been a distaster as well as computers in classrooms). As a nation (the USA) we can't get our act together for a rigorous national exam, etc etc.
Alabama is one state that requires the ACT. The mean score in Alabama is below 18/36. Wisconsin is another. Its students score on average about 1 point higher than the national average of 19.4/36.
If you prefer states that require the SAT, the mean SAT score of students from Delaware is less than 980/1600, about 50 points below the national average.
I'll leave it to others to argue about whether these exams are rigorous.
My hot take is that it's not really that terrible in the long run for work since I think LLMs will probably be nearly or actually AGI and better white collar workers than most humans within 5 years of today. But it is very funny and surreal in the meantime.
It is definitely bad for school, though. Kids IMO should actually be encouraged to use LLMs but not in or for class work outside of an AI best practices class. Probably stop giving them homework (90% will always try to find a way to make AI do it) and have them solve problems in class hours with no electronics so that they're forced to not defer learning. This will become even more important once we have AGI.
What if they don't?
> This will become even more important once we have AGI.
What if we achieve AGI in 50+ years? Should everyone live in this Kafkaesque world until then?
Plenty of us share the same opinion on doing reviews of AI generated code.
We are still much better at writing in a way that doesn't waste other people's time.
- "Launch is checked"
- "Question is asked"
- "The implementation answers"
- "The model wants"
- "The results name"
- "The connection surfaces"
- "The prompt wires"
- "The feature rides the mechanism"
Every single fucking thing is alive, wants things, and does things.
It's terrible. Infuriating. I want to rip my eyeballs out reading this filth. All. The. Time. "The anger is real".
It's so horrible. The human element has been completely removed and replaced by..... mediocre.
No it hasn't. The human element is still there, prompting the LLM. The change is that the human is happily accepting the first thing they get rather than critically looking at it and seeing a problem.
Humans are seeing either a shortcut to go faster (accepting low quality to move on immediately; reasonable if they're short on time) or a shortcut to lowering effort (accepting low quality because they don't care; not so reasonable but probably has a deeper root cause).
Kinda the same with language/technology stuff - it can be a great tutor and it can scaffold other parts of a project for you. It can give you feedback and let you focus on the interesting parts.
I guess the motivation itself may be hard because of the fear of it taking over much of our jobs, but having this kind of help/feedback is pretty cool for the sake of learning things just because they are interesting!
Please don't. I've had all of Codex, Claude and Gemini convincingly tell me absolutely wrong stuff, pointing it out with easily verifiable example they come up with more and more weird reasons.
Things don't become correct simply because most sources are again - easily and logically verifiable - wrong. This already was a plague when people "just googled" stuff and effectively returned with the most SEO optimized answer. Now we have very convincingly written instances all over the place.
If these were singular instances I wouldn't be so worried, but if you are learning it already is very easy to learn something wrong. This is why back in the days when people still used physical books to learn new things it was a good idea to check first which books are actually recommended. There have been a lot of "experts" that wrote things they clearly misunderstood but worked for all the examples in their books.
To give a common example for both the backend and frontend devs, that isn't about a specific projects. LLMs and Google searches frequently turn out wrong results regarding CORS caching and how it works in relation to domains/hostnames. The circumstances under which Content-Disposition work are another example. I think a lot of wrong statements that LLMs are "convinced" about are due to wrong statements (sometimes in otherwise correct response) of popular Stack Overflow answers.
It's saddening how much wrong "common knowledge" exists in the industry. I have been bitten by a lot of these, but it feels when people don't even actually code and think anymore this will just rise forever.
I will.
Can these be wrong? Certainly. So can humans. Many of your examples are of humans being wrong. That doesn't make LLMs - or humans - useless. The fact that they are not infallible is not a reason to avoid using them and I'm not going to throw out a tool that has been incredibly valuable to me because someone on the internet got some bad CORS advice.
And that sounds scary but the way I got over the fear is by realizing there are many things that I do very well but I do not know their internals very well. Driving is an example. I barely understand what the steering wheel, clutch or brake pedals do. I have driven over 130,000 Kms and I will perhaps drive more than double that in the next many years.
I have been building software since PHP/Drupal days. Got into AWS S3 as a beta user. Adopted Memcached (and MQ) in 2008 out of necessity. Then Python/Django for 10 years. Then Rust. And tons of JS/TS. I owe a lot to my curiosity. I believe we can keep learning what we need and still delegate most of programming to agents.
Still waiting for this revolution of amazing 10x software! It's been 10 months since Everything Changed in November, surely the 10x pragmatists could have leveraged their effective 8 years of development time? Or maybe we'll move the goalposts again and say that actually, Everything Changed with Astra, we'll just need to wait another three months?
There were humans far superior than you for writting Rust before LLM, now there's a LLM. The only difference is price and time execution.
You get an awesome teacher (LLM) ready to answer all your questions about Rust.
And you still find excuses not to learn it ?
At some point, just realize you've been lazy to learn it and LLMs are just an excuse.
I had LLMs write a pile of cuda-rust code and they were quite competent at it. Ported a bunch of (C++) CUDA kernels over, and ground away on them til they got equivalent performance
https://github.com/rdaum/eider/tree/main/backends/cuda-oxide
And mostly just DeepSeek 4.1 Flash, too. Not even a frontier model.
Sorry.
What the hell is your problem? Getting on the Internet and hurling personal insets around. Get a grip.