201–210 of 827 posts
I'd like to hear from Linux kernel developers. There is no significant software that has been written (plagiarized) by "AI". Why not ask the actual experts who deliver instead of talk? This whole thing is a religion.
What counts as "significant software"? Only kernels I guess?
I'd like to hear from Linux kernel developers. There is no significant software that has been written (plagiarized) by "AI". Why not ask the actual experts who deliver instead of talk? This whole thing is a religion.
What counts as "significant software"? Only kernels I guess?
As an actual open source developer I'm not seeing anything. I am getting bogus pull requests full of AI slop that are causing problems though.
I'd like to hear from Linux kernel developers. There is no significant software that has been written (plagiarized) by "AI". Why not ask the actual experts who deliver instead of talk? This whole thing is a religion.
There is no significant software that has been written (plagiarized) by "AI". How do you know? As you haven't evidenced your claim, you could start by providing explicit examples of what is significant. Even if you are correct, the amount of llm-assisted code is increasing all the time, and we are still only a couple of years in - give it time. Why not ask the actual experts Many would regard Karpathy in the expert c…
Meanwhile, I asked this morning Claude 4 to write a simple EXIF normalizer. After two rounds of prompting it to double-check its code, I still had to point out that it makes no sense to load the entire image for re-orientating if the EXIF orientation is fine in the first place. Vibe vs reality, and anyone actually working in the space daily can attest how brittle these systems are. Maybe this changes in SWE with more…
The real question is how long it'll take until they're not brittle
Where do these analogies break down? 1. Similar cost structure to electricity, but non-essential utility (currently)? 2. Like an operating system, but with non-determinism? 3. Like programming, but ...? Where does the programming analogy break down?
> programming The programming analogy is convenient but off. The joke has always been “the computer only does exactly what you tell it to do!” regarding logic bugs. Prompts and LLMs most certainly do not work like that. I loved the parallels with modern LLMs and time sharing he presented though.
It quite literally works like that. The computer is now OS + user-land + LLM runner + ML architecture + weights + system prompt + user prompt.
Taken together, and since you're adding in probabilities (by using ML/LLMs), you're quite literally getting "the computer only does exactly what you tell it to do!", it's just that we have added "but make slight variations to what tokens you select next" (temperature>0.0) sometimes, but it's still the same thing.
Just like when you tell the computer to create encrypted content by using some seed. You're getting exactly what you asked for.
Earlier quoted context omitted.
I don't think the human is the problem here, but the time it takes to run the full testing suite.
It is kind of a human problem too, although that the full testing suite takes X hours to run is also not fun, but it makes the human problem larger. Say you're Human A, working on a feature. Running the full testing suite takes 2 hours from start to finish. Every change you do to existing code needs to be confirmed to not break existing stuff with the full testing suite, so some changes it takes 2 hours before you ha…
Where do these analogies break down? 1. Similar cost structure to electricity, but non-essential utility (currently)? 2. Like an operating system, but with non-determinism? 3. Like programming, but ...? Where does the programming analogy break down?
Define non-essenti The way I see dependency in office ("knowledge") work: - pre-(computing) history. We are at the office, we work - dawn of the pc: my computer is down, work halts - dawn of the lan: the network is down, work halts - dawn of the Internet: the Internet connection is down, work halts ( - dawn of the LLM: ChatGPT is down, work halts (<- for many, we are here already)
Tight feedback loops are the key in working productively with software. I see that in codebases up to 700k lines of code (legacy 30yo 4GL ERP systems). The best part is that AI-driven systems are fine with running even more tight loops than what a sane human would tolerate. Eg. running full linting, testing and E2E/simulation suite after any minor change. Or generating 4 versions of PR for the same task so that the h…
I don't think the human is the problem here, but the time it takes to run the full testing suite.
It's fascinating to see his gears grinding at 22:55 when acknowledging that a human still has to review the thousand lines of LLM-generated code for bugs and security issues if they're "actually trying to get work done". Yet these are the tools that are supposed to make us hyperproductive? This is "Software 3.0"? Give me a break.