Well, unlike the compiler I don't trust the AI enough not to re read the result.
For now it's the pair programing buddy that helps me debug. There are stuff where it's definitely more efficient than a human is.
This is a most excellent place for technology news and articles.
Well, unlike the compiler I don't trust the AI enough not to re read the result.
For now it's the pair programing buddy that helps me debug. There are stuff where it's definitely more efficient than a human is.
I understand the spirit of what he means, but I still don't know how an LLM can be used efficiently as a precise tool like this. If I can describe a problem narrowly enough to guide an LLM to give a useful output, I've already solved it myself and may as well just type it out.
Exactly same thinking. I can usually type it out faster than AI (when taking into account latency, context building, prompt writing, prompt fixing, AI hallucination review) if I know what exactly needs to be done.
When you're out of your depth, it shines in providing beautifully confident and a botanical garden of a code piece that wil most likely be broken and break in new and exciting ways. Great for incompetent sycophantically-challenged managers that forgot how to code, or never actually had any experience.
Large-scale code transformations, taking into account the bigger picture of the repository are most likely hallucination free (not generative, just transformative, as per the actual LLM model) and a very exciting use-case.
Also it's currently a very nice pragmatic tool for checking for any mistakes, because it can connect the larger context of the repository quickly to the diff. Terrible if done by a manager without understanding of copilot and workflow, but a great tool if done through claude and cli as a pre-commit step with just quick checklists. Makes plenty of mistakes, but allows to catch your own big mistakes nicely quickly.
If there's anybody I trust to use LLMs in a responsible way, (to whatever degree that's even possible) it would be Linus Torvalds. He has some of the highest standards for software development in the world, and the same can be said for the core Linux kernel development team.
The general problem though, is that the people who are the least qualified to do software development are very often the people who are the most likely to use LLMs to try to slop their way to the top.
I think that the combination of cost increases for inference, inherent limitations in model integrity, and the economic destruction that will ensue when these fraudster CEOs have finally squeezed every last drop of blood from every last stone they can find, will leave "AI" in a similar place as blockchain/crypto/NFTs.
There will be a relatively niche market for software engineers and related tech workers; local LLM boxes, some subscription-based models that companies pay for with their licensing packages, hobbyists, and some minimal integrations into software suites for tools like background removal, lighting enhancement, etc.
There will be no Singularity, no AGI, no all-knowing Machine God.
I wish more would listen.
Many seem to interpret the headline as “Torvalds is an AI Bro now,” when its more like him yelling “If you all don’t treat these things as tools, shit is going to hit the fan.”
After seeing what happened to windows because of this "tool" I think many of us are rightfully skeptical of what will happen to this community.
It happened before, why are we okay with it happening again?
Microsoft doesn’t treat it as a tool; that’s the problem.
…Which isn’t surprising. Not only because Microsoft is Microsoft, but they own like a third of OpenAI, so they have a vested interest in perpetuating the AI hype.
Never seen a non-deterministic compiler though
Or one that pretends compilation was a success when it wasn't.
C/C++ compilers are non deterministic due to support of super macros that change run to run, non-deterministic optimisation strategies or ordering due to parallelism, and linkers often produce different outputs every time they are run where subtle bugs can cause crashes when addresses don't line up how you expect. And that's without mentioning projects that use a configuration step.
Can't most serious compilers produce reproducible builds these days given the same build environment. I know there has been a drive towards reproducible builds in general for security verification purposes.
Yeah, but it does take a lot of work to coerce them to do it.
GCC is honestly obnoxious, and you have to do a bunch of unintuitive things to get it. The compile stage needs the built-in RNG seeded, parent file paths stripped, you need to ensure that the date/time macros are not used anywhere, and you need to ensure that all command line flags are passed in the exact same order every time.
I just went through this with GCC16 on a new project.
Technically, LLMs (and most ML models) are deterministic with the same input and same seed.
I get what you mean though.
So does ChatGPT intentionally change seed at every interaction so it always spits two different outputs given the same input?
In short: yes. You can tune these values when self hosting - it basically changes the b chance which tokens will be used under which circumstances.
Like Scipitie said, sort of.
In the ChatGPT app, there's tons of shuffling in the background, like context being injected, maybe sampling changed, agenic action, quantization... its "far" from the actual LLM, opaque by design, and as a result certainly not deterministic.
You can sometimes get deterministic output with the OpenAI API, but it's also dependent on nothing changing on their end. And their end changes a lot.
But self hosting or using a more consistent provider will give you deterministic output.
@inari@piefed.zip , may I ask why do you change the title so awfully it does not only not state the same as the article but misleads it?
So it looks like the source originally used that awful title misrepresenting the article it self. In other words the source needs to be blacklisted for spreading bullshit. Dose this community have a blacklist yet?
I know blacklisting sources is a steep slope to censorship, but at a certain point if the source feels they need to click bait people with tabloid headlines they are not worth our time.
It's moderation, automating a local rule about reliable sources.
I just think it should fail early, so the user doesn't type a whole post only for it to be blocked.
The URL they posted has the same title as the post here so it's the source that changed their title after the fact.
fuckin gross.
Did the headline change? The current headline is Torvalds: "100% of Their Code is Written by Compilers" Too
The title of this post makes for a dumb headline, at any rate. Linus, in response to claims in the industry that projects are now "99% written by AI", drew an analogy to compilers by saying that all machine code for projects are written by compilers, yet no one says their project was 100% written by a compiler. It's just talking about stupid hype, which is valid.
That being said, it's still quite unfortunate that Linus has fallen into the trap of LLMs.
I don’t get the impression he’s fallen in the trap at all.
More so, he sees it for what it is. It’s a tool that can help, but needs smart people that can validate its output. It can’t design entire systems nor effectively solve real world business problems on its own. It’s not going anywhere, so may as well adapt to our new reality.
Source did change the title if you look at the URL matches what OP posted
Even Linus is conflating "doing more" with "being more productive". A car factory could, if they wanted, pump 10x more cars out the door. But qualiry would decrease these would be full of defects, so in the end you weren't more productive
I don't care if there's more PRs. It's just and illusion of productivity
Even Linus is conflating “doing more” with “being more productive”.
No he isn't:
Torvalds’ broader argument is that generating code has become easy, while maintaining a system over years or decades remains hard — and AI does not close that gap on its own. Without a working understanding of the underlying architecture, he suggested, AI assistance can help someone make mistakes faster rather than build something durable.
Productivity = Doing more things Efficiency = Doing the right things
I wrote a whole thesis on the subject AMA
But you still have to compile
When the next thing is invented, then we'll have to do three things.
So funny thing, a colleague of mine was arguing that there's no reason to do a compiler because he got Claude to generate ELF binary directly for a hello world...
Some of the AI bros are very extremely bullish on it too the point of saying compilers are a waste of time..
Linus seems to be taking a perfectly pragmatic approach, given that AI is not going away short of WW3.
I can imagine some individual sub-system maintainers introducing various AI-roadblocks though.
I also expect this to be increasingly addressed (in general) with model & tooling improvements, giving more weight to higher quality reports and MRs, and more respect for project rules and processes. A mix of soft and hard gates, CLAs, improved early automated bug report & patch reviews and other CI gates.