Who would have thought that an artificial intelligence trained on human intelligence would be just as dumb

“Major new Technology still in Infancy Needs Improvements”

-- headline every fucking day

You have no idea how many times I mentioned this observation from my own experience and people attacked me like I called their baby ugly

ChatGPT in its current form is good help, but nowhere ready to actually replace anyone

GPT-2 came out a little more than 5 years ago, it answered 0% of questions accurately and couldn't string a sentence together.

GPT-3 came out a little less than 4 years ago and was kind of a neat party trick, but I'm pretty sure answered ~0% of programming questions correctly.

GPT-4 came out a little less than 2 years ago and can answer 48% of programming questions accurately.

I'm not talking about mortality, or creativity, or good/bad for humanity, but if you don't see a trajectory here, I don't know what to tell you.

So this issue for me is this:

If these technologies still require large amounts of human intervention to make them usable then why are we expending so much energy on solutions that still require human intervention to make them usable?

Why not skip the burning the planet to a crisp for half-formed technology that can't give consistent results and instead just pay people a living fucking wage to do the job in the first place?

Seriously, one of the biggest jokes in computer science is that debugging other people's code gives you worse headaches than migraines.

So now we're supposed to dump insane amounts of money and energy (as in burning fossil fuels and needing so much energy they're pushing for a nuclear resurgence) into a tool that results in... having to debug other people's code?

They've literally turned all of programming into the worst aspect of programming for barely any fucking improvement over just letting humans do it.

Why do we think it's important to burn the planet to a crisp in pursuit of this when humans can already fucking make art and code? Especially when we still need humans to fix the fucking AIs work to make it functionally usable. That's still a lot of fucking work expected of humans for a "tool" that's demanding more energy sources than currently exists.

I will resort to ChatGPT for coding help every so often. I'm a fairly experienced programmer, so my questions usually tend to be somewhat complex. I've found that's it's extremely useful for those problems that fall into the category of "I could solve this myself in 2 hours, or I could ask AI to solve it for me in seconds." Usually, I'll get a working solution, but almost every single time, it's not a good solution. It provides a great starting-off point to write my own code.

Some of the issues I've found (speaking as a C++ developer) are: Variables not declared "const," extremely inefficient use of data structures, ignoring modern language features, ignoring parallelism, using an improper data type, etc.

ChatGPT is great for generating ideas, but it's going to be a while before it can actually replace a human developer. Producing code that works isn't hard; producing code that's good requires experience.

Yeah it's wrong a lot but as a developer, damn it's useful. I use Gemini for asking questions and Copilot in my IDE personally, and it's really good at doing mundane text editing bullshit quickly and writing boilerplate, which is a massive time saver. Gemini has at least pointed me in the right direction with quite obscure issues or helped pinpoint the cause of hidden bugs many times. I treat it like an intelligent rubber duck rather than expecting it to just solve everything for me outright.

My experience with an AI coding tool today.

Me: Can you optimize this method.

AI: Okay, here's an optimized method.

Me seeing the AI completely removed a critical conditional check.

Me: Hey, you completely removed this check with variable xyz

Ai: oops you're right, here you go I fixed it.

It did this 3 times on 3 different optimization requests.

It was 0 for 3

Although there was some good suggestions in the suggestions once you get past the blatant first error

ChatGPT and github copilot are great tools, but they're like a chainsaw: if you apply them incorrectly or become too casual and careless with them, they will kickback at you and fuck your day up.

If you don't know what you are doing, and you give it a vague request hoping it will automatically solve your problem, then you will just have to spend even more time to debug its given code.

However, if you know exactly what needs do do, and give it a good prompt, then it will reward you with a very well written code, clean implementation and comments. Consider it an intern or junior developer.

Example of bad prompt: My code won't work [paste the code], I keep having this error [paste the error log], please help me

Example of (reasonably) good prompt: This code introduces deep recursion and can sometimes cause a "maximum stack size exceeded" error in certain cases. Please help me convert it to use a while loop instead.

What drives me crazy about its programming responses is how awful the html it suggests is. Vast majority of its answers are inaccessible. If anything, a LLM should be able to process and reconcile the correct choices for semantic html better than a human... but it doesnt because its not trained on WIA-ARIA... its trained on random reddit and stack overflow results and packages those up in nice sounding words. And its not entirely that the training data wants to be inaccessible... a lot of it is just example code wothout any intent to be accessible anyway. Which is the problem. LLM's dont know what the context is for something presented as a minimal example vs something presented as an ideal solution, at least, not without careful training. These generalized models dont spend a lot of time on the tuned training for a particular task because that would counteract the "generalized" capabilities.

Sure, its annoying if it doesnt give a fully formed solution of some python or js or whatever to perform a task. Sometimes it'll go way overboard (it loves to tell you to extend js object methods with slight tweaks, rather than use built in methods, for instance, which is a really bad practice but will get the job done)

We already have a massive issue with inaccessible web sites and this tech is just pushing a bunch of people who may already be unaware of accessible html best practices to write even more inaccessible html, confidently.

But hey, thats what capitalism is good for right? Making money on half-baked promises and screwing over the disabled. they arent profitable, anyway.

I just use it to get ideas about how to do something or ask it to write short functions for stuff i wouldnt know that well. I tried using it to create graphical ui for script but that was constant struggle to keep it on track. It managed to create something that kind of worked but it was like trying to hold 2 magnets of opposing polarity together and I had to constantly reset the conversation after it got "corrupted".

Its useful tool if you dont rely on it, use it correctly and dont trust it too much.

I guess it depends on the programming language.. With python, I got very fast great results. But python is all about quick and dirty 😂

People down vote me when I point this out in response to "AI will take our jobs" doomerism.

Rookey numbers! If we can't get those numbers up to at least 75% by next quarter, then the whippings will occur until misinformation increases!

I always thought of it as a tool to write boilerplate faster, so no surprises for me

They’ve done studies: 48% of the time, it works every time.

Sure does, but even when wrong it still gives a good start. Meaning in writing less syntax.

Particularly for boring stuff.

Example: My boss is a fan of useMemo in react, not bothered about the overhead, so I just write a comment for the repetitive stuff like sorting easier to write

// Sort members by last name ascending

And then pressing return a few times. Plus with integration in to Visual Studio Professional it will learn from your other files so if you have coding standards it’s great for that.

Is it perfect? No. Does it same time and allow us to actually solve complex problems? Yes.