Sixteen AI Agents Built a C Compiler From Scratch (arstechnica.com) 162
Anthropic researcher Nicholas Carlini set 16 instances of Claude Opus 4.6 loose on a shared codebase over two weeks to build a C compiler from scratch, and the AI agents produced a 100,000-line Rust-based compiler capable of building a bootable Linux 6.9 kernel on x86, ARM and RISC-V architectures.
The project ran through nearly 2,000 Claude Code sessions and cost about $20,000 in API fees. Each instance operated inside its own Docker container, independently claiming tasks via lock files and pushing completed code to a shared Git repository. No orchestration agent directed traffic. The compiler achieved a 99% pass rate on the GCC torture test suite and can compile major open source projects including PostgreSQL, SQLite, Redis, FFmpeg and Doom. But it lacks a 16-bit x86 backend and calls out to GCC for that step, its assembler and linker remain buggy, and it produces less efficient code than GCC running with all optimizations disabled.
Carlini also invested significant effort building test harnesses and feedback systems to keep the agents productive, and the model hit a practical ceiling at around 100,000 lines as bug fixes and new features frequently broke existing functionality.
The project ran through nearly 2,000 Claude Code sessions and cost about $20,000 in API fees. Each instance operated inside its own Docker container, independently claiming tasks via lock files and pushing completed code to a shared Git repository. No orchestration agent directed traffic. The compiler achieved a 99% pass rate on the GCC torture test suite and can compile major open source projects including PostgreSQL, SQLite, Redis, FFmpeg and Doom. But it lacks a 16-bit x86 backend and calls out to GCC for that step, its assembler and linker remain buggy, and it produces less efficient code than GCC running with all optimizations disabled.
Carlini also invested significant effort building test harnesses and feedback systems to keep the agents productive, and the model hit a practical ceiling at around 100,000 lines as bug fixes and new features frequently broke existing functionality.
why multiple agents? (Score:2)
Wouldn't it give better results if just one did it?
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First of all, why would it give better results? Agents do not have the capacity to understand how one part of the code interacts with another.
Also, I'm guessing it would have taken 32 weeks with one single agent. Probably not interesting to anyone willing to foot the bill.
Re:why multiple agents? (Score:4, Interesting)
Agents do not have the capacity to understand how one part of the code interacts with another.
Of course they do.
How else would 16 of them work on a common code base?
Cell Biologists will be amazed to learn that individual phospholipids which work on the common task of forming cellular membranes, have been thinking beings this entire time.
Does every cell in your body, and every molecule in every cell in your body, and every embryonic stem cell, coordinate and collaborate to produce the extraordinarily complex body of a mammal? Does that mean they have cognition? Does that mean your cardio-electric tissues understand electrolytes and nephrology?
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Forth is a variant of an assembly language,
False, as I have conclusively proven. You're delusional.
I suggest to read a damn forth manual
Take your own advice. I linked to one earlier to show you just how full of shit your claims are. Learn how to read, dipshit.
it is not that complicated.
You're right, it's not complicated. So why are you incapable of understanding even the basics? (Hint: It's because you're really stupid.)
Sorry, no idea how you do not consider this a low level language.
LOL! You're changing your claim! You called Forth "an artificial assembly language interpreter", which is laughable nonsense. Forth is a high-level language. [wikipedia.org]
And K&R C is low level, a portable macro assembler.
LOL! Just how fucking stupi
Re:why multiple agents? (Score:4, Insightful)
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So a bit like a large team of developers. We go off the rails too without supervision. Kind of why you need to collect status updates and maintain a schedule and project plan and architectural documents.
Successful open source projects work because the ones who succeed have the discipline to do the coordination and supervision in a more cooperative and distributed way. Top-down programming projects are a hot mess, like if you do Waterfall management without actually writing a plan and sticking to it.
Agile ta
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Like semi decent, not to be trusted much AI.
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In just the Linux example, it is most certainly not the "one guy model". There have been countless thousands of contributors.
Linus is great and all, but he's currently just doing coordination between the members of a very large hierarchical team. No one human could possibly do all of that work.
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These models aren't parallel in their nature, so spinning up multiple 'agents' is just how you manage concurrency. Just like forking a process. I think it's a bit werd to call each instance a distinct 'agent', it is trying too hard to humanize this very synthetic thing...
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Different agents have different task descriptions. Think for example of a planner, a coder, a reviewer, a critic and a debugger, which alternate and can request each other to take over.
Re: why multiple agents? (Score:2)
The longer an agent works on its own, the more likely it is to suffer from its own hallucinations. Using different agents likely helps mitigate this by not allowing a single agent to go off on its own for too long
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ClippyAI: Pair programming is an agile software development technique where two developers work together at one workstation, with one acting as the "driver" (writing code) and the other as the "navigator"
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Yeah that doesn't work well either.
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Why, do explain.
Congratulations (Score:4, Insightful)
Congratulations on reimplementing the wheel with a new set of bugs and security issues, useless tools, and no support, all while wasting time, money, and energy.
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Re:Congratulations (Score:4, Interesting)
It's a neat demonstration. I think if I had $20k to throw around, I'd do the opposite. Make a new 16-bit C compiler to support UZI or Fuzix [fuzix.org]. (maybe not, might be more fun to write myself)
I've seen some decent results for retro programming, such as this vid Let's Create a Commodore C64 BASIC Interpreter in VSCode! [youtube.com]. Where the presenter gets a Commodore/Microsoft BASIC in C, and not only that with some hand holding gets it to output something capable of working on 2.11BSD for PDP-11.
Re:Congratulations (Score:4, Funny)
Writing a C compiler isn't what I would call fun. Debugging generated code and then debugging why you generated that broken generated code is a whole different circle of hell.
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It was pretty fun writing a Pascal for the pcode machine back in the day. And fun to make a couple of pcode to assembler translators, which shows the rather tricky problem of optimizing register allocation in a stack machine, but fun.
Porting and updating existing compilers like PCC and the Plan9 C compilers is also not too bad, rather enjoyable really. Because much of the hair pulling and crying is over. But these days I just patch LLVM, which is so huge and complex that I'm unlikely to understand more than
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It was pretty fun writing a Pascal for the pcode machine back in the day. And fun to make a couple of pcode to assembler translators, which shows the rather tricky problem of optimizing register allocation in a stack machine, but fun.
You're cut from a different cloth than me, that's for sure.
Porting and updating existing compilers like PCC and the Plan9 C compilers is also not too bad, rather enjoyable really. Because much of the hair pulling and crying is over. But these days I just patch LLVM, which is so huge and complex that I'm unlikely to understand more than the tiny little piece I need for my job.
PCC is a fantastic learning tool for anyone interested in writing a compiler. I wish it had been available to me at the time.
LLVM.... I don't even want to think about.
It's been a decade and a half since I had to deal with anything on the compiler side of things. These days, I'm just happy if the always-in-flux kernel API doesn't break a module I have to maintain.
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Every write anything for the PERQ?
Re: Congratulations (Score:2)
Never even seen one in person. A bit before my time. Closed this to that I have used is UCSD Pascal at a neighbor's house a bit one summer before buying Turbo Pascal.
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Don't forget that a huge amount of work for a competent compiler is performance enhancements for different CPUs. I'm guessing it probably doesn't have those.
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Re:Congratulations (Score:5, Funny)
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LLM got interesting in the last 3 years. Now they build working C compilers. Even if the compiler would inject a bug in every binary it would still be impressive and you expect perfection from a technology that is still in its infancy. And if the Linux kernel boots, the compiler cannot be that bad either ... so what do you think will be possible in let's say ten years?
Also humans still exist and you can and probably should have one who reads the code produced by the AI. It's not like these tools exist in a
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I think it's interesting. C compilers aren't that complicated but C is just enough "uncooperative" that neither is it "feed the right file into lex/yacc and it will work". 20K seems cheap.
What I'd really like to see though is what they can do with reverse engineering, binary to C seems eminently sensible, C is low enough level that it can easily reflect the binary code without artificial constructs, but it's also expressive enough that it can express the semantic meaning of the code. And unlike compiling, w
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For architectures that lack working hardware, wouldn't it make more sense to take an existing front-end like gcc or clang and just generate a back-end for the targeted hardware?
Re:Congratulations (Score:4, Informative)
Who is 'we'? I don't think the LLM is up to the task of making a C compiler that can target an architecture with at most 256k of RAM and without a reference C compiler to work with, like it did for this. The LLM basically got told to write a knock off of gcc, and based on some of what happened, it absolutely needed a working gcc to work from to create the sort-of knock off.
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I mean, what next iteration?
I would also say that this seems the opposite of useful for no longer working hardware. If the hardware existed, then we still have a C compiler for it. If you say you want to modernize that compiler, but the hardware is a dead platform, why are you trying to modernize for it anyway?
Let me extrapolate to the point that maybe you are talking about a compiler for some future architecture. Problem is this example needed:
- A human to carefully craft test cases and rescue the LLM w
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The functionality you describe used to fit on a single floppy.
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That was a version of Word which did a lot less, though granted the number of lines of code per feature has surely increased very much since.
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Sure, they carefully spend weeks crafting the test cases with test data and then spend tens of thousands and probably have to buy it a license of Word to use as a reference to compare test execution on the LLM output versus reference implementation...
Or they could just stop at having bought Word....
The problem here is that this example leaned *heavily* on the software desired already existing and the LLM having access to run the original software as it endeavored to make a knock-off. And then per analysis a
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Libre Office exists. What is the benefit of thousands of people "vibing" their own versions?
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It seems the intent of my original post was not clear.
Yes I know Libre Office exists, it's the one I use at home. My point was that Big Tech is "all in" on AI across the board, driven by an obvious eagerness to eliminate human software developers from the creation process. They see only the money they can save.
But the consequences of actually achieving such a goal would undermine their own business models. The reason why they would no longer need programmers is the same reason why no one would need their
Re: Congratulations (Score:2)
Also creating a c compiler isn't really an impressive feat. It incorporates very little human requirements in its design. All it has to do is parse the very well known token patterns of C and create a matching program. It is hard for a human just because it is a lot of work, not because it is technically difficult. It looks hard from the outside, but if you have studied it, it is logically simple. Putting it in the words of my compiler instructor, we can create a compiler in one class but if we wanted
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When will 16 AI agents be able to code me up a Word processor with features equivalent to Microsoft Word?
No chance at all. Doing crappy C compilers is very easy. It is one reason why basically any platform has one. And all steps will have been in the training data, up to and including working source code. Writing even a text-editor is a lot harder because it requires actual understanding of where you want to go with things.
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Doing a crappy C compiler was basically a semester course I took in college. Everyone more or less finished, while taking 3-5 other courses at the same time. So yeah, if it can be done by 1 engineer in training in a similar amount of time to it being done by 1 agent, while it's kind of cool I don't see this as a major accomplishment.
Really you can use lex/yacc for parsing and tokenization. You can find the C grammars online. C is a very simple language, if you aren't looking to optimize you can map each
Re: Congratulations (Score:2)
I just commented essentially the same thing. Once you know how to do it, making a compiler isn't hard. It's all following syntax rules.
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Yes, about that level of difficulty. Nice stunt or exercise, does not mean anything for complex software.
I know a guy that did that over a weekend (Score:2)
And all he needed were a couple of pizzas.
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Nah, he was just bored and didn't have anything better to do.
Cannot not even build hello world (Score:2)
https://github.com/anthropics/... [github.com]
Doesn't sound like "from scratch" to me! (Score:5, Insightful)
From TFA:
When all 16 agents got stuck trying to fix the same Linux kernel bug simultaneously, he used GCC as a reference oracle, randomly compiling most kernel files with GCC and only a subset with Claudeâ(TM)s compiler, so each agent could work on different bugs in different files.
Not only was Claude trained on a lot of different C compilers, including the entirety of GCC, it still needed a golden model in order to finish.
If I claimed I had written my own C compiler from scratch and then this came out in an interview, I don't think I would be hired.
Re:Doesn't sound like "from scratch" to me! (Score:4, Funny)
Yeah, perhaps an extra step for the analysis would be to run comm against this "from scratch" compiler versus gcc and clang.
Re:Doesn't sound like "from scratch" to me! (Score:4, Funny)
Not only was Claude trained on a lot of different C compilers, including the entirety of GCC, it still needed a golden model in order to finish.
To be fair, they were going use the ANSI C23 specification as a basis, but nobody wanted to shell out the money to buy an official copy.
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Indeed. The thing that is utterly telling is that it could not hack the 16 bit part. There is really enough documentation on the web on 16 bit x86 code that when you got a 32/64 bit compiler going, adding a target for 16 bit should be very, very easy. Well, for a human, it would be. Not for a mindless automaton.
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Not only was Claude trained on a lot of different C compilers, including the entirety of GCC, it still needed a golden model in order to finish.
If I claimed I had written my own C compiler from scratch and then this came out in an interview, I don't think I would be hired.
Indeed. That is called "faking it". But a ton of mindless believers will be deeply impressed by this meaningless stunt nonetheless.
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One thing that LLMs are pretty good at is translation, and training on a large corpus of Rust and C code as well as numerous C compilers means that this task is utterly useless given the context of the existing compilers, and trying to prove it can make projects "from scratch" is disingenuous when you are just having it implement very well trodden territory.
Hell, someone posted an experiment in writing a C compiler in rust to github at least once before, so it even had a C compiler written in rust that was
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It's capable of combining semantic meanings in an astronomical number of ways. The decoder layer will make of that what it will.
Now I would agree that they're not normally trained to look at words in this way, so they likely aren't great at it.
More so, I'd argue that any metric by which you say an LLM can not "originate" applies to a human as well.
I saw your later comment regarding how humans learn to read, but I don't really se
Re: Doesn't sound like "from scratch" to me! (Score:2)
Making up a word is just a matter of a random number generation accented with a knowledge of where to place vowels and constenants.
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What you need is a source of entropy.
For someone like a human, with basically infinite entropy coming in from the bazillions of sensory neurons in your body, you can make up words for quite a while.
For an LLM, your entropy is fairly fixed- but still incredibly large.
Entropy is fundamentally a measure of how big of a number you need to describe the state of the "random" variable.
In both cases, it's astronomical.
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pOHtato pAHtato.
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Potayto
Potahto
Puhtaytoe
Pawtahtoe
Poteyto
LLM: 1, fluffernutter: 0
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https://github.com/anthropics/... [github.com]
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Also, because I'm old, and I've been writing software in C and assembly for a long time, and I feel like I've seen just about everything under the sun.
There is nothing new in any snippet of code written. It's all been done.
Took a look at the ELF reader. Looks serviceable.
I don't really get what the goal of the task is, though.
You said:
People are capable of writing original words in a way that LLMs are not. Covfeferetter.
Do you think an LLM is incapable of writing an original word, like Covfeferett
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How did you learn to read? Did you ingest a billion different texts? No.
How did you learn to distinguish the color red? Did you look at a million different labeled pictures and classify colors accordingly, or did someone show you a crayon and say, "this is red"? People learn concepts differently.
People don't produce words in the same way LLMs do. The reason you think they do is because you are ignorant: you haven't done your due di
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OK, you're wrong, but this should be obvious even to a genius like you.
How did you learn to read? Did you ingest a billion different texts? No.
How did you learn to distinguish the color red? Did you look at a million different labeled pictures and classify colors accordingly, or did someone show you a crayon and say, "this is red"? People learn concepts differently.
People don't produce words in the same way LLMs do. The reason you think they do is because you are ignorant: you haven't done your due diligence to understand the problem well enough to justify your strong opinion.
It's obvious and self-evident that LLMs and the human brain are entirely different in just about every way. I disagree with most of the rest of what you wrote. It's pretty clear that people do NOT learn by being told "this is red" one time. By the time the a child is in PreK or K or whatever level of school and is learning colors, that child has been seeing millions of colors for years.
That child has been heard adults talking about that red house or the white paper or the big red firetruck or the ugly purpl
Re: Doesn't sound like "from scratch" to me! (Score:2)
One only needs to note that we don't need entire nuclear power plants to run our brains to see that we are different.
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Nobody ever claimed a lack of difference- in fact, it is you and them claiming a lack of similarity, and it only takes a set of eyeballs to see that you're both wrong.
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The beginning is a variable that isn't definitive. We can make this example as absurd as you want. Does from scratch preclude the ability of using any existing libraries? Does it mean we need to do everything in assembly? Does it mean we need to first create the universe?
Doing something from scratch does not typically preclude the use of reference material. That said in this case the issue seems that it was more than just reference.
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Yes. Also note that writing bad C compilers is actually pretty easy because they are simple. That is one reason basically any platform has at least a C compiler. And there will habe been tons of examples in the training data. "How to write a C compiler" gets tons of hits on the web, with tutorials, sample code, entire books. It is a really well documented topic. And they even used GCC as an "oracle" to show the "AI" how it was done.
Oh, and look, it could not hack 16 bit code because that is a lot less well
Ok? (Score:3, Insightful)
I mean, this is impressive in the same way that turning vinyl gloves into hot sauce is impressive. Fabrice Bellard wrote TCC in a few months and it was under 30k lines of code, including an assembler and linker, and it actually worked (the Claude c compiler apparently cannot compile Hello World, so it undoubtedly has hundreds of bugs) - I am a little terrified of what that 100k lines of code actually looks like. If my past experience with coding AI is any guide, it will be disorganized, needlessly wordy, not standards-compliant, has weird unnecessary bugs around Leap Year, lacking in useful comments etc.
Which is to say while this is impressive, I am far more worried about what this means for the future of software quality than I am impressed with this achievement. Look at the crazy number of bugs Windows has had recently, coincidentally after MSFT bragged about how much code was being written by AI these days.
Yeah nah (Score:4, Insightful)
A C compiler written in Rush (Score:4, Informative)
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Please tell me why I shouldn't just commit suicide, right now?
It's a lot of work, just let time do the hard part.
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Re: A C compiler written in Rush (Score:5, Funny)
Because it has sick drumming, dude!
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Don't try suicide, nobody cares
Don't try suicide, you're just gonna hate it
Don't try suicide, nobody gives a damn
AI generated C compiler - not so great (Score:4, Insightful)
Apparently the performance of the code it produces is worse than gcc with all optimizations turned off. That's pathetic. And it is written in rust, so it can't bootstrap - And the size of it is on par with a hand-written C compiler - so no win there.
When I worked on compilers at IBM, our first bootstrap of C for x86 was a cause for celebration. A double bootstrap was a great "smoke test". But that was relatively easy. Passing the validation test suites were *way* harder - like 50x harder.
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Now it's obvious why no one did it: $20,000 of compute time.
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The result is interested in that it helps show the possibilities and limitations, the contours, of AI coding.
That is absolutely the "why", right there. I'm still on the fence on if AI is coming for developers' jobs or not, but this experiment definitely nudges me more toward the "yeah, probably" side. If I made my money slinging code I'd be making sure I knew how to do it using these tools.
Now it's obvious why no one did it: $20,000 of compute time.
Peanuts, in the corporate world.
Re: AI generated C compiler - not so great (Score:2)
Ok well clearly you have never attempted to even get a $100 piece of software from a corporation when there are free alternatives available. I have never seen a place that was willing to pay for securecrt, we always use putty.
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Putty is better, so that's the right choice.
Carlini mentors "security fellows" who receive a weekly stipend of $3850 [reddit.com], I presume he is paid more than that, he spent two weeks on this and it costs around 40% more on top of an employee's salary to employ a person on average. It might have actually cost more in payroll (especially if anyone assisted him) than it did in AI time.
Re: AI generated C compiler - not so great (Score:2)
Putty is not optimized to handle hundreds of servers, securecrt is.
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so no win there.
I mean they did it in a short time for $20k. Performance here doesn't just mean execution speed. You're comparing it against a 39 year old project that has millions of hours contributed to it. The point of this wasn't to create a high performance GCC alternative, it was to demonstrate functionality and speed.
I doubt AI coding assistants will ever produce something as performant as experts who have been optimising shit for over a decade do, but some people don't have a decade to spare.
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"That's pathetic."
Don't you think an AI building a working compiler at all is quite impressive?
When it comes to AI, it seems that people accept nothing under perfection instead of thinking about how impressive it is that a computer can now do such tasks. Most humans I know can't code a C compiler on their own, no matter how unoptimized the results are allowed to be.
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Don't you think an AI building a working compiler at all is quite impressive?
And this is why I hate AI.
AI building a kinda-sorta working compiler, albeit one with a lot of jankyness and also incomplete and leaning on numerous tools to make it work, like er gcc, is impressive.
Being oversold is what pisses me and most people here off.
Fun quote.. (Score:2, Insightful)
. But that total is a fraction of what it would cost me to produce this myself—let alone an entire team.
I'm willing to commit to provide a C compiler in a single day for a tenth of the cost:
# dnf install gcc
For a bonus, I'll even do two:
# dnf install clang
Don't know what I'll do with the other 7.99 hours of the day though...
This reminds me of how Khaby Lame mocked all those overcomplicated "life hacks" by doing the obvious simple things.
Big Deal (Score:3, Informative)
It took just one Dennis Ritchie to do that back in the 70s, and he used much less water in the process!
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It took just one Dennis Ritchie to do that back in the 70s, and he used much less water in the process!
Well, now you've done it -- we have to estimate how water Dennis Ritchie used in the process of writing his C compiler.
- According the Wikipedia, Dennis Ritchie developed the first C compiler in 1972 and 1973, so I'm going to call it two years.
- The average American uses 80-100 gallons of water per day (including drinking water, toilet flushing, showers, cooking, laundry, etc).
So that puts the water usage for Ritchie's C compiler in the ballpark of 65,700 gallons total. Dunno how that compares to the AIs'
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- According the Wikipedia, Dennis Ritchie developed the first C compiler in 1972 and 1973, so I'm going to call it two years.
Not only is that equally likely to be just over one year from the description alone, but you've also assumed he did nothing else over the same period...
Source code (Score:3)
What would Computer Scientists of the '80s think? (Score:2)
It surprises me that many in the Slashdot community are inclined to focus on the aspects that this demonstration didn't go well.
Surely, if you described this story (warts and all) to a group of Computer Scientists in the 1980s, predicting it would be a capability of AI in 2026, they would look back at their expert systems and decision trees, and be pretty skeptical.
Re: What would Computer Scientists of the '80s thi (Score:2)
I'm not so sure. A decision tree could do this, it would just need to traverse the syntax and make a decision at each token. I think what has changed is that the decision tree would not have been seen as impressive because we knew how they worked. A lot of people seem to think LLMs are magic so that makes it more impressive to them.
So? Building a crappy C compiler is pretty easy... (Score:2)
That is one of the reasons C is still around: Somebody competent can build a compiler for any target pretty easily. There is a lot of materials on how to do it on the Web and in books as well, to the "AI" did not need to understand or "invent" anything.
There is really nothing to see here. Just another meaningless stunt that may impress the clueless.
But how does it run? (Score:2)
I am really pleased. (Score:2)
more party tricks (Score:2)
So this is more AI party tricks. A person can make a coin disappear through misdirection. The misdirection here is that a c compiler seems complex but there's actuallly an exact blueprint for every compiler by just following the syntax.
Is AI a coder self sabotage project? (Score:2)
What's it like being a coder working for an AI company marketing replacing labour? Making something to replace your peers is far from the same as shooting them but it's a step in the same direction. And I've heard all the justification crap about sewing machines and tractors. But AI coders, rather than keeping the money, they are working towards making themselves redundant or less valued and giving their money to weirdos like Altman and Musk. What kind of self sabotage does that ?
Judging from the salaries,
From "scratch" (Score:2)
If by that you mean using every compiler ever made as training material, sure, I guess?
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No orchestration agent directed traffic.
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"It was the best of times, it was the blurst of times?!"