memes

I‘m not sure I understand. At least docker containers have their own os, mostly alpine linux. Dunno if that applies to other apllications.

You think of distribution packaged rpms/deb, but the softwate developer can self publish, and you'll see plenty of self published packages in ppa, copr, flathub, and even just loose websites because it's not rocket science to make an apt or yum repository. However the distribution versions may take a little more time, but more likely to work together as a cooperative whole. Flathub has a decent shot by allowing concurrent versions of dependencies to install, while preserving the concept of updating dependencies independent of the package maintainers.

However, as you go down his chart, it's less likely that you'll reasonably update after install. You may get the latest at the second you install, but 6 months later you'll likely be stale. You may neglect to update npm in each and every project, or it may automatically dependency lock (because self publish nature results in developers having to vet dependency updates, and devs are lazy about that).

I assume he refers to npm/pip/cargo to be the multiple os option, not saying the last one is obviously better for multiple os. At least that has to be because that's the only option that is os independent.

Of course it sucks because the essentially uncurated dependency trees result in either instability on updates, or missing updates. Of course also the natural OS updater won't help you out with pip/cargo/npm, but it will help with apt, yum, snap, and flatpak.

"need"? Of course not. Though I do see it being capable of much more sophisticated autocomplete. Like a tab-complete that is aware of what you've already typed in the command and gives you only compatible remaining flags, or could tab-complete information available in the environment, like recognize it's running in Kubernetes and let you tab through running hosts or commands that'd make sense from 'here', etc, etc.

Sure, it's all things a very nice and complicated algorithm could do, but ... that's all "AI" thus far. There have been zero actual artificial intelligences created.

So I didn't do it in the CLI direct, but I had a whole lot of files in a collection that obviously had duplicates.

So I first used fdupes, which got a lot of them. But there were a lot of duplicates still. I noted a bunch were identifiable by having identical file size, but just some different metadata, so I made a quick work of presenting only files with identical stuff and went about reviewing and deleting.

Then I still see a lot of duplicates, because the metadata might be slightly different. Sizes were close, but non dupes also were close. I might have proceeded to write a little something to strip it the metadata to normalize, but decided to feed it to an LLM and ask to identify likely duplicates. It failed to find them all, and erroneously declared duplicates, but it did make the work go faster. Of course in this scenario a missed duplicate isn't a huge deal, so I had to double check their results and might have missed some things, but good enough for the effort.

Sometimes my recall isn't quite good enough for ctrl-r, but maybe an LLM could do better. Of course a better "search engine" also could do well. Also a mind numbingly obvious snippet could be generated without the tedium. Again, having to be careful to reviee because the LLMs are useful, but unreliable.

Not sure what you mean. It's already a completely superfluous and additional feature. It "should" execute completely separate of everything regardless of what integrations it has.

Though if it doesn't yet exist as a separate thing to hook in to (and it doesn't), it's got to execute somewhere. Makes sense it'd show up as a canned extension or addition to something before it'd show up as a perfectly logically integrated tool.

There are two modes of AI integrations. The first is a standard LLM in a side panel. It’s search and learning directly in the terminal, with the commands I need directly available to run where I need them. What you get is the same as if you used ChatGPT to answer your questions, then copied the part of the answer you needed to your terminal and run it.

There is also AI Command Suggestion, where you’ll start to type a command / search prefixed by # and get commands directly back to run. It’s quite different from auto-complete (there is very good auto-complete and command suggestion as well, I’m just talking about the AI specific features here).

https://www.warp.dev/warp-ai

It’s just a convenient placement of AI at your fingertips when working in the terminal.

Alas. They have said they plan to open some of the source and potentially everything, but it’s little progress.

They recently ported to Linux, which I think will give them much more negative feedback here, so hopefully with more pressure they’ll find the correct copy left license and open up their source to build trust.

Kitty is really popular. I'm using foot, as long a terminal has the basic functionality I need, best latency is what I care about.