Alex

Issue triage, code exploration, extracting information from disparate sources, first pass code review. There are loads of use cases that it’s potentially useful.

For me it’s a lot better at extracting the requirements for a CPU feature from a 10,000 page architecture reference manual than I am.

I have API access at work because I don’t want to be tied to a UI. I’m very aware of the cost because I’m trying to see where it offers good value for money.

Of course things like the deep research and notebooklm are covered by the Google workplace fees which while including more than the personal plans are also a fair bit more expensive.

Your making a big assumption extrapolating from one particular study involving Java code and a static analyser.

How is that patch sloppy?

I feel the term slop is being overused to cover anything an LLM has touched. If I ask an agent to re-read a mail thread for me and apply the changes to my tree to review is that slop? Would you feel better about it if I copy and paste from email to code in my editor?

I’ve just been doing a bunch of bug triage which was mostly driven by the agent although I checked the issues where it had commented. Was that slop? Ironically a lot of the issues where AI generated although for the most part more complete than a lot of the purely human submissions we get. Are those bug reports slop? What about the poorly drafted human ones?

That’s not kernel policy but LF guidance. From the kernel’s point of view patches still have a high bar to pass to get merged and I don’t think we have enough data yet to see if LLM based submissions to the kernel have a higher or lower error rate than humans.

I certainly feel the uptick in LLM reports though - one of the projects I’m working on is seeing a deluge of them at the moment.

Where you live maybe. The NHS is centrally funded through taxation.

If course you do - if the cost of treating the patient down the line is going to cost you more. Public health systems have a vested interest in healthier citizens.

The majority of my gaming is on the road too but I’ve found the Steam Deck hits that niche for me. I carry a thin Chromebook for work related things. Admittedly you don’t need as powerful a GPU for a small 720p display.

How big a niche is that - because when I think high end gaming a laptop has all sorts of trade offs to make anyway.

On the potentially bright side maybe this will make people think harder about which model to use for which task. You don’t need to feed your entire code base into Opus when a Gemini Flash sub-agent can do a perfectly fine job running grep and compiling a summary for the main agent.

Even Debian has popcon as an opt in. I can see why collecting data about hardware and package choices is useful to Ubuntu. I didn’t think they collected any personally identifying information.

If it’s finding valid vulnerabilities then it’s just another tool like static analysis, fuzzers and sanitizers. There definitely seems to be a difference in quality compared to earlier generations that were behind the sloppy avalanch of reports.

Funny 😂

They don’t have to be. They know what they asked the LLM to do. They know how much they adapted the output. You usually have to work to get the models to spit out significant chunks of memorised text.

No, that’s why the author asserts that with their signed-of-by. It’s what I do if I use any LLM content as the basis of my patches.

If the 2-10% is just boilerplate syscall number defines or trivial MIN/MAX macros then it’s just the common way to do things.

My kids are growing up in this environment and they already have an eye for ai slop. I suspect it’s the same thing that led to OpenAI’s TikSlop “product” is getting canned. After society had gotten over the sugar rush excitement of new and shiny toys I suspect the interest will fade and people will crave the connection you get from real art made by real people.

At least I hope that is what will happen. We might have to do something to hold the tech companies accountable for their dopamine trigger machines though.

Where are you seeing the 2-10% figure?

In my experience code generation is most affected by the local context (i.e. the codebase you are working on). On top of that a lot of code is purely mechanical - code generally has to have a degree of novelty to be protected by copyright.

They don’t, just like they don’t with human submitted stuff. The point of the Signed-off-by is the author attests they have the rights to submit the code.

I swear people have rose tinted glasses as to the state of the init system before the current generation of system management daemons.

If you really want to have Debian without systemd there is always Duvean but the Debian architects are free to choose the technologies that solve the very real system orchestration problems that exist.