danielbln

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I mean, we're talking curl here, I don't think a lot of suffering of consequences is happening. And man pages are often also not a great resource, throw everything at you, often don't contain examples. If I'm building an app that integrates curl or libcurl, oh yes I'm reading the doc. If I just need curl to do something quickly, the LLM output is perfectly fine.

I recently watched the 3.5-hour workshop Mastering the curl command line by Daniel Stenberg, the author of curl

I commend the author for watching and subsequently summarizing this into a blog article, but in the age of LLMs like ChatGPT I cannot be arsed anymore to memorize any of the arcane command line arguments of curl, ffmpeg and the like.

I think burkinis are dumb, personally, but I don't give a damn what people wear. This is just typical ingroup-outgroup postering fueled by a proto fascist government, standard stuff really. Also, hygiene? Bro, it's the ocean, a layer of clothing extra ain't gonna make a difference.

If there's nothing good to watch, whatcha pirating then?

I just asked GPT-4:

What's 7 * 8 divided by 10, to the power of 3?

Its reply:

Let's break this down step by step:

First, multiply 7 and 8 to get 56.

Then, divide 56 by 10 to get 5.6.

Finally, raise 5.6 to the power of 3 (5.6 * 5.6 * 5.6) to get 175.616.

So, 7 * 8 divided by 10, to the power of 3 equals 175.616

Well, if I try to use Photoshop to calculate a polynomial it's not gonna work all that well either, right tool for the job and all.

The fact that LLMs are terrible at knowing what they don't know should be well known by now (ironically).

These LLMs generally and GPT-4 in particular really shine if you supply enough and the right context. Give it some code to refactor, to turn hastily slapped together code into idiomatic and well written code, align a code snippet to a different design pattern etc. Platforms like https://phind.com pull in web search results as you interact with them to give you more correct and current information etc.

LLMs are by no means a panacea and have serious limitations, but they are also magic for certain tasks and something I would be very, very sad to miss in my day to day.

It's a language model, I don't know why you would expect math. Tell it to output code to perform the math, that'll work just fine.

Bard is kind of trash though. GPT-4 tends to so much better in my experience.

I'm in Germany and almost every avocado here is a bad avocado. Two things I really miss from California: avocados and dispensaries. Things I don't miss: strip malls and cars for everything.