For coding it heavily depends on the language. For example, it's quite decent at writing C#, but whenever I try to ask it any question about rust, it's either flat out wrong or doesn't even fucking compile.

Also found it most useful when I know exactly what I want, just don't know the syntax. Like when I was writing C# code generation for the first time. Also unsurprisingly sucks at working with libraries.

I used it today to find out how to do something on my Juniper that would have taken 45 minutes of sifting bullshit documentation. One question and I figured it out in 2 minutes.

This is similar to gabe Newell's idea of piracy. This is a convenience issue. And GPT solves some of it.

Report up the chain, if it's safe to do so and they are likely to understand.

Also, check what your company's rules regarding data security and LLM use are. My understanding is that at many places putting private company or customer data into an outside LLM is seen as shouting company secrets out to the open internet. At least that's the policy where I'm at. Pasting an entire project in would definitely violate things for my workplace.

In general that's rude as hell. New guy comes in, grabs an entire project they have no background with, and just chucks it at an LLM? No actual review of it themselves, just an assumption that your code is so shit that a general use text generator will do better? Doesn't sound like a "team player" to me (management eats that kind of talk up).

Maybe couch it as "I want to make sure that as a team, we're utilizing the tools available to us in the best way possible to multiply our strengths. That said, I'm concerned the approach that [LLM idiot] is using will only result in more work for the team. Using chatGPT as he has is an explosive approach, when I feel that a more scalpel-like approach to address specific areas for improvement would be the best method moving forward. We should be using these tools to address specific concerns, not chucking everything at the wall in some never ending chase of an undefined idea of 'more optimized'."

Perhaps frame it in terms of man hours? The immediateness of 5 minutes in chatGPT can cost the team multiple workdays in reviewing the output, whereas more focused code review up front can reduce the man hour cost significantly.

There's also a bunch of articles out there online about how overuse of LLMs is leading to a measurable decrease in code quality and increase in security issues in code bases.

Or docs are far too extensive... reading imagemagick docs is like reading through some old tech wizard's personal diary.. "i was inspired to shape this spell like this because of such and such...." like, bro.. come on, I just want the command, the args, and some examples... 🤷‍♂️

The reason why string[5] = '5' doesn't work is that strings in Python are immutable (cannot be changed). By doing list(string) you are actually creating a new list with the contents of the string and then modifying the list.

I wonder if ChatGPT explains this or just tells you to do this... as this works but can be quite inefficient.

To me this highlights the danger with using AI... sure you can complete a task, but you may not understand why or learn important concepts.

Perplexity (or open source equivalents) are much better for this.

Idk why we have to keep re-hashing this debate about whether AI is a trustworthy source or summarizer of information when it's clear that it isn't - at least not often enough to justify this level of attention.

It's not as valuable as the marketing suggests, but it does have some applications where it may be helpful, especially if given a conscious effort to direct it well. It's better understood as a mild curiosity and a proof of concept for transformer-based machine learning that might eventually lead to something more profound down the road but certainly not as it exists now.

What is really un-compelling, though, is the constant stream of anecdotes about how easy it is to fool into errors. It's like listening to an adult brag about tricking a kid into thinking chocolate milk comes from brown cows. It makes it seem like there's some marketing battle being fought over public perception of its value as a product that's completely detached from how anyone actually uses or understands it as a novel piece of software.

copilot did the same with basic math. just to test it I said "let's say I have a 10x6 rectangle. what number would I have to divide width and height by, in order to end up with a rectangle that's half the area?"

it said "in order to make it half, you should divide them by 2. so [pointlessly lengthy steps explaining the divisions]"

I said "but that would make the area 5x3 = 15 units which is not half the area of 60"

it said "you're right! in order to ... [fixing the answer to √2 using approximation"

I don't know if I said it then, or after some other fucking nonsense but when I said "you're useless" it had the fucking audacity to take offense and end the conversation!

like fuck off, you don't get to have fake pride if you don't have basic fake intelligence but use it in your description.

Cool, not really what I asked. Then command ‘write an implementation of bogo sort in python 3.’

… and then it does that.

Alright, but... it did the thing. That's a feature older search engines couldn't reliably perform. The output is wonky and the conversational style is misleading. But its not materially worse than sifting through wrong answers on StackExchange or digging through a stack of physical textbooks looking for Python 3 Bogo Sort IRL.

I agree AI has annoying flaws and flubs. And it does appear we're spending vast resources doing what a marginal improvement to Google five years ago could have done better. But this is better than previous implementations of search, because it gives you discrete applicable answers rather than a collection of dubiously associated web links.

There are ways of doing that which dont require burning an acre of rainforest

Depends. I asked it to add missing props to a react component just yesterday and it generated a bunch of code that looked pretty good but then I discovered it just made up some props that didn't even exist and passed those in too lol. Like wtf that's super annoying. I guess it still saved me time though.

The FuckAI people are valid for their concerns.

Unfortunately, their anger seems to constantly be misdirected at the weirdest things, instead of root issues.

"Give me a vegan recipe using " has been flawless. The recipes are decent, although they tend to use the same spices over and over.