Perhaps AI is going to take away coding jobs – of those who trust this tech too much Computer scientists have evaluated how large language models (LLMs) answer Java coding questions from the Q&A site StackOverflow and, like others before them, have found the results wanting. In a preprint paper titled, "A Study on Robustness and Reliability of Large Language Model Code Generation," doctoral students Li Zhong …
There's got to be an threshold above which it's easier to code something yourself than correct all the mistakes in the AI generated code, and that threshold is way below the error rates those LLMs are making.
That's not even taking in to consideration that if by some chance it does generate seemingly working code for the immediate problem, you can understand it well enough to maintain it in the future.
Remember to push you iffy generated code to GitHub so that the bots can get it from there to generate some code for another dev. Repeat.
Programming jobs are going to migrate to writing unit tests to check if the output from the Llama (assuming output came out of a somewhat-respectable orifice of said Llama) actually sometimes produces workable results. So brush up on your testing skills; that is where the big money will soon be.
Isn't that the reason for AI? You train your AI on Cobol and have your scant* and expensive programmers deal with the fall out.
* We had this discussion the other day. Cobol was designed as an easy language. There's no reason experienced programmers of any modern language couldn't get and up and running fairly quickly. It would not be like the major conceptual challenges of asking a Cobol programmer to manage codebase in C.
I can see the job increasingly becoming code reviewing AI code. At the moment, it might be quicker to write it yourself. It's not going to stay that way forever.
Eventually, they'll get good enough it will become writing high level specs and little more than diving into bugs the AI can't solve. We learnt to trust compilers generating the machine code, instead of doing it ourselves. Eventually, we'll trust them to generate the nuts and bolts code, too.
Full tilt to a future of code grey goo where language models hoover up scads of iffy code written by humans and puke it back out as a sequence of alphanumerics that statistically *look* like an answer to a coding question asked by another human.
It's silly on an autonomous cars are coming next week level.
I’ve found chat GPT is a useful tool for answering very specific questions. For example I’m rubbish and regex and it definitely helped me learn a few things. Having said that if I ask it more complex questions it often gives answers that just don’t work (~30%), and you need to have a very clear idea of what you want your code to do and how you want it to be structured before you get sensible answers to your questions.
I’ve tried GitHub copilot too - about half of the time it’s suggestions are really useful and half the time absolutely no use at all
Certainly it's a good way to avoid learning anything, improving your own skills, or serendipitously encountering something else of interest.
Delegating your work to a machine has essentially the same advantages and disadvantages as delegating it to a stranger of unknown capabilities and motives.
AI might be able to do this but it will take a ton of accurate specifications of the desired code to produce an accurate and complete result. I have used AI for a few relatively simple coding exercises and it has improved my code, but to produce a complete solution is still far out of reach.
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