What makes you think that? it would need some prompt engineering if so since ChatGPT won't write like that (bad capitalization, lazy quoting) unless you ask it to
Honestly, that is an understatement. `uv run` has transformed how I use Python since 99% of the time I don't need to setup or manage an environment and dependencies. A have tons of one-off Python scripts (with their dependencies in PEP 723 metadata at the top of the file) that just work with `uv run`.
I get how it might not be as useful in a production deployment where the system/container will be setup just for that Python service, but for less structured use-cases, `uv` is a silver bullet.
It is tiresome to repeat every single time the arguments that so many other cyber experts have also mentioned including here on YC. This is quite the common knowledge by now.
Kindly use the search box on the bottom of the page.
That's because there aren't really any. Yes, it's kinda maddening that the best hardware to de-Google your life is to give Google even more money and buy a Google phone, but, after having used that search box, all I could find are complaints that it's not very usable because they disabled so much shit in the name of security and privacy, but I saw nothing where it fails at the technical details in protecting privacy. There's some purist bit about the timing of updates and availability of source due to embargoes, but even they are being practical in that case. So no, unless I missed something, it's not common knowledge, and you're just pretending there is to make it seem like there is something there when there isn't.
That is the first red flaming flag, yet you dismiss it like nothing albeit so many cybersec experts point out the same thing (references you can search them on previous discussions)
The second is forgetting things like actively promoting the usage of US government developed and sponsored tech like signal and Tor.
Then let's look at that availability of source code, which for some "reason" doesn't come out. Lest but not least, don't even wonder about their financing sources and constant spamming on sites like this as if there aren't better options.
You can bot away and say none of this matters. It does matter, not everyone here is dumb and I'll keep complaining no matter how many times the other bots downvote what is obviously just another gov-sponsored operation.
In the time you've spent writing all these vague comments you could have just cleared up the confusion. I cared enough to read a comment you would write out, i really don't care enough to go research it
For the same reason anyone would: if an AI can reason to a human level after having been educated in a manner similar to a human then it is likely that we [the educators] have captured something akin to human intelligence.
I don't really understand why those things are bad? Making your server executable available for dedicated servers is common (and good!) and selling paid mods just seems like selling software to me
edit: the private server operators might be bad, but I don't see how this is Minecraft's fault (or how it doesn't apply to every game that allows dedicated servers)
The problem is the framing. Reductionism always sounds smart and is rhetorically effective but usually just loses all nuance or meaning. I've never met a parrot (stochastic or otherwise) that could write python code or rewrite my emails so what is the point of you describing it like that besides wanting to sound smug and dismissive?
The point is that next-token prediction produces output by sampling from distributions assembled by text it has seen previously (hence stochastic). The “ding” or claim is that - like a parrot - LLMs can’t produce responses which are truly novel in concept or make logical out-of-sample leaps, only repeat from words they’ve been taught explicitly in the past.
So you think stochastic parrot is an accurate term and not an attempt to be dismissive? So if someone woke up from a coma and asked what ChatGPT is you would say "stochastic parrot" and think you've explained things?
While “stochastic parrot” is obviously an over-simplification, and the way the phrase was originally coined in context was likewise obviously intended to be dismissive, I think the analogy holds. I see them as a lossy storage system.
I think the expectation that simply continuing to scale the transformer architecture is not likely to exhibit the type of “intelligence” for which _researchers_ are looking.
For my personal taste, the most interesting development of NLP in this latest AI wave (and LLMs in general) is RAG. I also have always wondered why the tokenization process hasn’t been deemed more important historically. To me, it seems like THE MOST critical part of how Deep Learning works.
