You should give Claude Code a shot if you have a Claude subscription. I'd say this is where AI actually does a decent job: picking up human slack, under supervision, not replacing humans at anything. AI tools won't suddenly be productive enough to employ, but I as a professional can use it to accelerate my own workflow. It's actually where the risk of them taking jobs is real: for example, instead of 10 support people you can have 2 who just supervise the responses of an AI.
But of course, the Devil's in the detail. The only reason this is cost effective is because of VC money subsidizing and hiding the real cost of running these models.
It's almost like OP had learned about AI impressions before hearing that impressions have been a thing for far longer than we've had AI to imitate voices. No judgement here, just fascinating.
Compilation is CPU bound and, depending on what language mostly single core per compilation unit (I.e. in LLVM that's roughly per file, but incremental compilations will probably only touch a file or two at a time, so the highest benefit will be from higher single core clock speed, not higher core count). So you want to focus on higher clock speed CPUs.
Also, high speed disks (NVME or at least a regular SSD) gives you performance gains for larger codebases.
I suppose you can't blame your earlier dentists, though. How were they supposed to know? And if they automatically treated redheads differently, would that be racism?
I occasionally lecture my 3DPD wife about science facts and she hates it. She'll say things like "what?" And "I was just asking what we should do for dinner"
I think the main barriers are context length (useful context. GPT-4o has "128k context" but it's mostly sensitive to the beginning and end of the context and blurry in the middle. This is consistent with other LLMs), and just data not really existing. How many large scale, well written, well maintained projects are really out there? Orders of magnitude less than there are examples of "how to split a string in bash" or "how to set up validation in spring boot". We might "get there", but it'll take a whole lot of well written projects first, written by real humans, maybe with the help of AI here and there. Unless, that is, we build it with the ability to somehow learn and understand faster than humans.
Do you not reuse any part of your outfit from day to day? Like do you have at least 7 different pairs of pants that you cycle through? Cause that's why I wouldn't do this, I'd rather not go out with some clothes then bring all that outside dirt into my bed.
I don't mind a whoops somebody fucked right up error message if you let me click a button for more details. Or at the very least, give me a reference number I can tell somebody about. Some "software companies" don't even properly log things on their end so nobody can solve shit.
Huh, I had never considered this solution to fizzbuzz to be honest. I usually go for string concatenation, or (i % 3 == 0 && i % 5 == 0), but yeah i % 15 == 0 is certainly a clever simplification
You should give Claude Code a shot if you have a Claude subscription. I'd say this is where AI actually does a decent job: picking up human slack, under supervision, not replacing humans at anything. AI tools won't suddenly be productive enough to employ, but I as a professional can use it to accelerate my own workflow. It's actually where the risk of them taking jobs is real: for example, instead of 10 support people you can have 2 who just supervise the responses of an AI.
But of course, the Devil's in the detail. The only reason this is cost effective is because of VC money subsidizing and hiding the real cost of running these models.