djx22

12 ms·

1.
by djx22 19d ago
Sorry about that, didn't mean to attack the person behind it. But anyone can build such an app within a day by prompting Claude. I think what I was more alluding to was the engineering value such a project brings. But once again, sorry
2.
by djx22 19d ago
It's because vibe coded apps have flooded the internet. This one is no exception. The feedback loop is now real: LLMs train from github on their own produced slop which they feed into the apps people build and publish on github to show
3.
by djx22 20d ago
You may want to look into different models that are more accurate and maybe an AEC layer to remove background noise. Or at the very least a RNN de-noiser on the mic channel. Also, you may want to stream audio to the model instead of holding
4.
by djx22 2mo ago
Actually, this paper shows that the LLMs create a lot more slop and degradation of the code after the first prompt. https://arxiv.org/html/2603.24755v1 . So iterating with the LLM will simply make it to produce worse an
5.
by djx22 2mo ago
yes, I understand the usecase. Where I'm coming from is quantized vs. unquantized. 4bit quants are lobotomizing the model heavily to the point that it's better to invest in some capable hardware than keep fighting the limitation.
6.
by djx22 2mo ago
similar experience, yes. I cancelled my subscription.
7.
by djx22 2mo ago
Not sure what everyone's experience is but I find 5.6 Sol to be a great liar. Reported success on a half done job and left things in a broken state after having quite a few back & forth followups on the initial prompt to clarify th
8.
by djx22 3mo ago
in my experience running models that have been heavily quantized(q4) or altered to some extent has never made me say “wow, this is so amazing”. On the contrary, the model ended up in the thrash bin after a few prompts. I have an RTX 6000 PR
9.
by djx22 7mo ago
Don't let AI write code for you unless it's something trivial. Instead use it to plan things, high level stuff, discuss architecture, ask it to explain concepts. Use it as a research tool. It's great at that. It's bad at