> don’t understand doxing

No, it's that people keep misusing that word for a broader and broader class of things. Pushing back on dilution of meaning isn't a lack of understanding.

What’s the utility of narrow definition of doxing? It’s a form of harassment. Who benefits from a narrow definition, aside from harassers?

I think we’re pretty far away from “falsely accused of doxing”. What’s it going to be? “I was just writing a research paper!”

It's certainly entertaining to read about ancient industry history, with people on DARPA grants objecting to military interest in the stuff the military was paying them to do.

> It doesn't tell anything the service those people are members of, and it doesn't tell what kind of work they do.

I'm pretty sure that term could even work for the Pods in some of my Deployments.

> why this is so huge is fascinating. i suspect it is not really about the age gap, but rather

Alternate theory: it's a genre tag that implies a whole pile of arbitrary features. Kind of along similar lines as how calling a movie a "space western" tells you quite a lot about it, despite making absolutely no sense if you try to take it strictly literally.

> In this case, it feels natural to me that the line for images should be aligned with the line for the act itself.

Why? Things are made illegal because someone involved is (presumed to be) harmed. That assumption doesn't hold if everyone involved was hired to pretend for the camera, or at least not in the same way. Maybe ban the movie industry as a whole over it's reputation for chewing people up?

We don't use standard time because it works best, we use it because it's "correct" relative to the position of the sun.

Now, standard business hours (9-5 or whatever) were probably chosen for working well in the circumstances where they became standard, and it might be interesting to watch for whether tweaking the clocks leads to tweaking the nominal time of things...

Sure it uses a few GB just like everything else these days, but some of the comments also mention it being slow?

The GitHub issue is AI generated. In my experience triaging these in other projects, you can’t really trust anything in them without verifying. The users will make claims and then the AI will embellish to make them sound more important and accurate.

> AI will embellish to make them sound more important and accurate.

Did you mean than accurate rather than and accurate? Having a more accurate issue description only sounds like a good thing to me

Making them look more accurate is not the same as being more accurate, and llms are pretty good at the former.

Imagine a user had a vague idea or something that is broken, then the LLM will choose to interpret his comment for what it thinks is the most likely actual underneath problem, without actually checking anything.

“Seem important and accurate” is correct. It doesn’t imply actual accuracy, the llm will just use figures that resemble an actual calculation, hiding they are wild guesses.

I’ve run into the issue trying to use Claude to instrument and analyze some code for performance. It would make claims like “around 500mb ram are being used in this allocation” without evidence.

I read that as "make them sound more important and accurate than they actually are".

To make them sound more accurate.

Hard /intractable is on an axis orthogonal to philosophical stuff like meaning.

> is solid and well-defined, but may feel unintuitive

I'm thinking that the nature of intuition is about training your neurons to approximate stuff without needing to detour through conscious calculation.

And QM is in too high of a complexity class for this to be a thing.

> but given the situation, How does that prevent the situation from happening again

You don't. Instead, you make sure your failover or DR setup is regularly tested and works.