It can't, though.

Only when connected to a harness can Claude remove files from disk.

And, at that point, it's using existing libraries or tools to do it - `rm` if it uses bash, the `remove` stdio function if it uses C or a C-implemented programming language to write a custom tool for the job, or one of many other options.

It remains true, though, that Claude cannot itself remove files - just be your proxy to guess what files it's probable you were referring to, that you likely wanted to remove them, and then use another tool to actually do so.

As you note, it will be wrong about that sometimes, and it will likely be unpleasant if you haven't prepared for the eventuality.

> When people say "AI is just a tool", I think they mostly know what they mean and we all do, too.

When I hear that phrase, I think the speaker is either too naive to live, or is intentionally trying to sidestep anyone bringing up the manifold disaster-level issues with genAI systems.

What exactly do you think

> a word of reproach

means?

I have no qualms about saying I hate it, every workday is utterly miserable, I can see my skills eroding, and I see almost nothing but downside to it.

FWIW, a past manager once dubbed me "the Luddite programmer," a badge I wore with pride.

Make no mistake, I do love computers, and writing software. Steve Jobs' metaphor of a "bicycle for the mind" captures well the role they played for me in my teens and twenties.

Alas, LLMs are like a freight train for shipping all minds to one destination, instead of freeing them to all find their individual ways to unique places.

...and also, the freight train's destination is hell.

Search this document for "Historical Note" for the canonical explanation:

https://developer.apple.com/library/archive/documentation/Co...

Its value is subjective, determined by what the market (i.e., a bunch of humans) will pay for it.

Given the gigantic pile of money that's spent on music, film, and books every year, it's quite clear that there can be large amounts of economic value in a piece of art.

That modern technology makes it easier to take an artist's with with absolutely no recompense, and that many choose to do so regardless of the maker's wishes, does not change that.

It just underlined what's been obvious since the dawn of civilization, that many humans are happy to ignore what other humans want and to enrich themselves at the expense of others.

...which brings us back full circle to the actual article, which is a clear illustration of the OpenAI executive team's conscious choice to do exactly that.

https://en.wikipedia.org/wiki/Logos

There's a lot more to it than just "language."

You need to have enough money to actually survive the lawsuit, even if it's a slam-dunk to win (and they almost never are).

There are so many variables that go into upvoting and downvoting, and we can't even see the actual scores on HN posts.

The data you refer to isn't available, AFAIK, and even if it were we'd have to account for the hundreds of confounding variables that contribute to post scores being what they are.

The camera and sketchpad are the only options we have.

Do you have any other obvious facts you'd like to pretend are somehow relevant?

You mean, they notice it's too dark right after making it, change the settings, do it again, and give you the good copy?

Because yes, that's my experience of humans.

But they do learn and improve.

The models don't (yet).

LLMs change not a whit, and there's no one to take responsibility for the failure (and thus no way to fix it).

As the new variation on the old theme has it, "A computer can never be held accountable, and so very many people are trying to get them make management decisions."

What makes you confident the Microsoft and Google software isn't vibecoded slop?

Certainly Microsoft has made a lot of noise about all their software being LLMgen these years, and also gotten into hot water with their users for Windows 11's crappiness.

What teams of people spent an entire career working together, focused entirely on Navier-Stokes or problems they suspected were related, without any "publish or perish" concerns?

I realize tenure is a thing, but my limited understanding is that a significant amount of time is spent earning it, once you account for Ph.D. program and the years of needed to be granted it.

I'm just trying to point out that economically, we have not yet reached the point where AI mathematics research is a no-brainer hands-down win, no consideration required.

It might already be a win, and certainly the ability to compress those 900,000 hours of effort into an actual week of linear time is mind-boggling and potentially a huge game-changer for all kinds of open research questions.

It's not obvious that human math research is dead yet.

Maybe soon, but not yet.