cudarc been great for me, because it's easy to look up existing examples and references, and it maps 1-to-1 with what I see. I'm already having a tough time with CUDA itself, a dialect of it makes a tad harder to rely on previous work.

Seems more ergonomic in general though, both approaches they share, compared to cudarc, and less build infrastructure and fiddling with environments, which is great.

oh no no no, this is going to break the CPP hold on AI and game dev.

And quite a few reasons that something better than C should be used. Rust seems a good candidate.

This thread flags an honest assessment of AI signal detection.

It gets fun when someone uses an uncensored model to bypass a refusal, but they accidentally pick one that was trained for erotic writing and brings its particular talent to the documentation task.

Thanks, saved me a few minutes

You’re absolutely right!

Why this is important: it's the honest take.

I think you can't trust Pangram in a high stakes situation, but it is absolutely better than random noise at detecting AI-generated text. Which isn't surprising. If the distribution of probabilities can yield blatant Claudisms, it's not surprising it would also have more subtle deviations.

(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.)

Pangram has an extremely low false positive rate. Even on adversarial examples.

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.

To be honest with you, I don't think I would be able to identify with high certainty that the bottom text is AI generated, so it definitely goes a long way to obscure the AI-generated nature of it, but I also think it still feels unnatural somehow. I realize my framing naturally calls into question whether I'm being honest, but I am being honest. Given my experience with similar "skills" (it's just chunks of prompt, nothing magical after all) I expected even less.

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?

I don't really have any opinion on your tone; I just still don't agree with your framing. A lack of evidence would be neutral like "there's no evidence to indicate either possibility is more likely", but your phrasing conveyed that one possibility was more likely than the other. I pushed back against your follow-up because it seemed like you were arguing for a higher threshold of evidence than you provided.

According to https://news.ycombinator.com/item?id=49417480, Anthropic hires writers who do not use LLMs, and reading their updates I also feel that they don't use LLMs for communication.

It does suggest that they are not accurately measuring the value of paying for content writers or proof readers.

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.

No. It suggests they don't mind littering slop into the information environment.

I believe most of their marketing videos use fairly convincing text to speech too, not voice actors.

found the McShill. The King will hear of this!

I couldn't even finish it man, it was so fucking sloppy. I had to throw away like 40% of it.

Their CEO also has the dubious distinction of claiming we've reached AGI more then once: https://www.theverge.com/ai-artificial-intelligence/985597/j...

Is Jensen Huang still all-in on OpenClaw? That moment feels more like a flash in the pan.

This is extremely depressing, I think I'm coming around to the realization that you may be right and I've been naive my entire career.

only reliable way to know how things work is to reverse engineer them

Where do you work? Sounds nice!

A small percentage of engineers

Copy past the example code, then tweak until it breaks? If we were meant to read documentation, not reading it would cause a compiler error!

The good news is your attention to actually reading and understanding documentation will differentiate you more and more as others (short-sighted, IMO) outsource understanding to an LLM.

What? People never read documentation?

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.

People never really read documentation before.

Speak for yourself. I read it.

Is that your honest load bearing assessment you’re going to flag?

I hadn't read the article and read this comment as though NVIDIA themselves were implying that this library was checked but not trusted by them since it was fully LLM generated.

... doesn't one of those imply the other?

I'm also an optimist but the crash is imminent. I hope I am wrong.

Land, chickens, and private local AI running sustainably on the farm sounds like the least dystopian version of this AI future!

Then here we are. AI apocalypse. Something of note. I've started to pay more attention to canned goods. Soups with lentils and so forth.

It's true of most work in many and soon most white collar jobs, too. Claude writes some dense useless thing, everyone else uses Claude to summarize and write a reply to the thing. The Claude-submitted PRs get automatically reviewed and commented on by a GitHub Claude review bot. The programmer asks Claude to check out Claude's review comments to Claude. Claude pushes a commit to the branch and writes a comment. The Claude review bot reviews the commit and leaves a comment. The human [...].

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.

I know many teachers who actually have respect for the profession, themselves, and the students. Thankfully that means they don't do this.

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.

As a high schooler going to a school with stricter rules on AI than most in my area, I can say that it's been going downhill ever since GPT 4. Teachers constantly use AI to create assignments(my French Teacher regularly handed us work with GPT 5.1 prose and emojis). Students are also rampantly using AI and bypassing school restrictions(We have a google account, making it easy to use Gemini if we just sign out), causing an inflation in GPAs and test scores. There's no easy solution to the problem, banning AI-tools only help somewhat as even typing into Google has AI web results, and students are quickly overcoming ways to restrict them. I have a friend that vibe coded an application that allowed his Mac Mini's desktop to be mirrored on his school chromebook, bypassing every restriction with sub 1-second latency. Of course, that opens the can of worms to whether schools should allow students to use AI...

I find it interesting that this was downvoted twice without explanation.

Claude, rewrite my graphics card in Rust. Make no mistakes.

Yeah. I think if the text is written for other machines, then by all means have an LLM generate it, but if it is intended for a human audience, have a human being write it.

We are still much better at writing in a way that doesn't waste other people's time.

Create any page with a file uploader. They all look the same now. It's like the Twitter Bootstrap days of responsive design. You'll get an icon which looks like ones on (on the drop space) those sites which are like "you must wait 60 seconds for this file to download".

It's so horrible. The human element has been completely removed and replaced by..... mediocre.

Even their writing skills are getting rusty.

it seems like that's the way the industry is headed

First of all, this is a pre-1.0 release that requires a nightly Rust compiler (if you choose the SIMT track with cuda-oxide) so that one is going to be unstable software.

Secondly, When an issue occurs with a kernel or you want to write your own custom kernel in Rust, now we need to diagnose if the problem came from either cuda-oxide (SIMT), Rust's side, CUDA or Tile (If you decide to choose the Tile track).

Another dependency into the list and course everything is open source except CUDA itself. So any issue that happens on the CUDA level, you are forced to wait for them to fix it.

LLM don't need to be trained in a library to use it well. It's just Rust which they know well.

the sole motivation is feeding and sheltering my family. in the time BC (before Clankers), rust was a better way to do that.

Wtf does that have to do with learning, you should be encouraging people to learn.

Just because an LLM can do something doesnt mean we shouldnt learn it. Imagine if your math teacher had this attitude with calculators. Or your engliah teacher with audio books, "no need to learn to read we have audio books and llms".

I sometimes also struggle with the motivation to learn these days, but I realize its a crutch and super bad for my future to fall for that trap.

You having access to an llm does not make you special, you will not get farther than the person who also understands the thing they can do with the LLM, just like how the kid who did well on math in high school didnt rely on a calculator (and is doing far better in life than those who did).

That code looks like garbage btw...

There are two types of programmers: the pragmatists who see programming as a chore and would gladly never write a line of code again given the right tools, and the gardeners who don't want their enjoyable and rewarding garden-tending work taken away from them.

I've found sorta the opposite - in any area, it can just do everything for you, or it can be an incredible teacher. I've been re-learning a lot of higher-level math and it has been an knowledgeable, infinitely patient, always-available tutor. Of course, I could just have it do just about any math I want for me, but that's not the point.

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!

what this article tells me is that no one at Nvidia actually cares about this project whatsoever. otherwise, they would have had a person actually write the announcement.

Is this satire? D3D12 and Metal aren't any less proprietary than CUDA.

This true, but you can write the two separately if you want.

The disadvantages of writing them together are listed in the various parent posts. But some code authors really like the convenience of having the two in the same file.

I thought they already did and released the compiler source code under Apache 2.0.

Nice, thank you. There is an old python project I've been thinking about converting to Mojo.

I highly recommend Julia for (scientific) GPU programming but it would be nice if there was a larger community and/or funding behind the GPU side of things. It has very few core devs for what it is.

The CUDA runtime is a special case of one of the libraries provided by the CUDA Toolkit. The CUDA runtime provides both an API and some language extensions to handle common tasks such as allocating memory, copying data between GPUs and other GPUs or CPUs, and launching kernels. The API components of the CUDA runtime are referred to as the CUDA runtime API.

From: https://docs.nvidia.com/cuda/cuda-programming-guide/01-intro...

Your programs shall never grace my systems.

yeah, just write a stub/wrapper around it and abstract. it's the classic coupling problem. nothing to do with CUDA

pretty crappy list

They dont like "seppo" for some reason.

It doesn't read as emphasis to me. It reads like the person is trying hard not to curse, and they think "crap" is a curse word. It's a little bit adorable, like I'm reading a comment from an obedient child.

More like p**p, as in "that cunt p**ped in my yard".

I'll admit, it never once occurred to me that people might be using censored characters to provide more emphasis that a word is a swear, but I guess it does indeed do that, at least to the writer. Whether that comes across to the reader, and whether the writer cares that their intention was understood... I'm not so sure.

My guess is that jacobgorm will not reply. I would love a reply, because I want to understand how others think.

I believe we'll be left to wonder.

Launching kernels manually is an error prone PITA which I believe is the principle reason for CUDA's popularity. Having the compiler give an error when you mess up is a huge benefit. But having the compiler allow you to express "I want to launch this kernel over a grid with these dimensions, with these arguments" as a single expression is where the vast majority of the value comes from.

The having it all in a single file is mostly an artefact of the fact that it is C++, because C++ is single file at a time compilation. In D (which is multiple files in a single compiler invocation) with DCompute (which targets CUDA and OpenCL with upcoming support for Vulkan and Metal), you are required to write the kernels in a separate module, but you get all the benefits of the compiler complaining when you mess up _and_ the expressivity of "launch me this kernel".

Having also played with Metal and WebGPU (at least years ago), I would say that CUDA is, amazingly, the best GPGPU API we have. Do I wish we had an open source parallel programming language as good or better than it? Yes. But asymmetrically hating on CUDA like this is how we continue to lag behind it in UX.

The best way to program GPUs is face up to the reality that they are not the same machine as the CPU, write your kernels in separate files, and launch them manually

Not to mention that this is a completely sane way to use CUDA as well.

I don't mind CUDA, I do mind that all of the SDKs don't dynamically load the various CUDA shared libraries at runtime.. intertwining itself into your application linking process makes for extreme binary portability inconvenience.

? I find it hard to see the issue here. Just put it in a separate file and call it?

Anyone here looking at Modular's offerings?

VectorWare founder here. We are working with them and stoked they are investing more in Rust. I just gave a talk at RustConf about our different takes (https://rustconf2026.sched.com/event/2KNQj/making-gpus-feel-...). The video isn't up yet but you should check it out when it is. The efforts are complementary.

Towards the end of the post, we (NVIDIA) mention that this work was done in collaboration with Vectorware and others in the Rust community. And we can't wait to build further with the community.

Will it then be possible to query TJunc hotspot temps on linux?

Rust just makes you sign a waiver first.

AI slop article, how can I trust on this?

Once again... There's literally no point to a low level shader language for heterogenous back ends.

Rust for GPU programming? My CUDA debugging sessions just got a whole lot less painful, hopefully.

Been waiting for something like this. CUDA C++ is a pain; Rust's safety for kernel programming could be a game changer.

Interesting direction from Nvidia. Anything that makes writing reliable GPU code less painful is definitely a good thing.

Don't think we're gonna see garbage collections anywhere near gpu for many reasons.

I’ve had this happen to me several time over the past weeks and it’s gone from quaint to humorous to farcical to outright “is-the-world-gaslighting-me” insane.

Just today I was reading Stanley Druckenmiller’s op ed in WSJ. This dude is like 80 and has made billions of dollars, and he got Claude to write his op ed???

Unbelievable. And the tells are so obvious, yet people still love the Claude-like quips and odd grammatical choices that read like halfway asshole halfway mid-sentence confusion.

Does this mean I can write shaders in Rust for use with WGPU or Vulkan?

Worth mentioning that Nvidia open sourced CUDA Tile IR ~8 months ago. And yes the code is open source too. https://news.ycombinator.com/item?id=46330732

The recent circular moves that Nvidia is making is designed to wrap things around them, anything to keep the AI model party going.

I read this the other day - definitely think it is the right direction Nvidia is taking.

Thank you NVIDIA - for once (not twice though - you've given us nothing but despair for Linux+GPU).