The post at the top of the thread was about "AI". The following posts were about AI. Don't be blinded by the current hype into thinking that;s the whole picture. Just because other developments get less press doesn't mean they aren't happening and aren't important. In the field of biochem, most AI is *related* to LLMs, but is significantly different.

LLMs are not equivalent to AIs, they are a subset. Don't take LLMs as a complete model of the capabilities of AIs.

Yes. I went to check out buying an Apple recently, after an appointment with my ophthalmologist. I wanted a computer that would run reasonably with voice control, as the ads suggested was possible. I decided not to, or at least to wait another year.

Now I have no idea how many people are affected this way, but that is a sign that the deficiencies have caused at least *some* damage to Apple.

The AI to develop drugs is a fantasy, because the data is too corrupt. There already exist AIs that aid in suggesting possibilities, and they will improve, but one that would do the development cycle would require cleaner data (or better robots).

But a large part of why X Window is the way it is, is that it was designed when computers were EXPECTED to have a lot less memory and disk space. It's always easier to expand something than to trim it back.

One of our engineers did this as a side project back in 2015 in an afternoon, setup a web scraper on aws and the next day we could visit all these things. I'm pretty sure the company did a new article on this... ten years ago.

My guess is phones and silicon will improve to make 4b on mobile by 2030. If not then those requests will get forwarded to xyz cloud service. I can see a world where 7-12b cloud models are ad supported free tier and you either pay or self host 70-600b yourself. I expect processing requirements to drop by half due to whatever breakthrough comes next and then there's a long tail of improvement after that. Token verification was a major improvement.

Yep I login to some of these sites and I see 3-4 tangentally-related things that are clearly algorithm rage-bait, designed to drive user interaction. I'm so tired of this. I login for 10-15 minutes a handful of times a week to check in on friends and family for updates, and then promptly uninstall the app.

Probably in 3-10 years there will be a handful of open, legally copyright free training sets anyone can use to train their own ~600b class model with whatever architecture is current state of the art. Researchers are already putting together 7b training sets like this. And LLMs can use tools like search now so they won't always need the most up to date news or info - they can use tools for that instead. Most of finance is analysis of documents, which LLMs have been excellent at for a while now.

Well, but it *was* designed for them. That it didn't stay fixed at the original limits doesn't mean that isn't how it was designed.

(And FWIW, I think a system designed for minimal requirements is REALLY desirable.)

Sorry, but this isn't evidence about the quality of the graduates. If they're just out of school you can't tell whether they're good or bad. I trained an astrologer to be a good programmer in less than a year. (Well, he soon moved into management, but he was capable.) HR hired a different astrologer, who was skilled at C. More skilled in the techniques than I was. But he was in love with macros, and used them everywhere, so nobody else could understand his code. It was the second one that had a high SAT score.

What it tells me is that $15/hour probably isn't enough to pay the rent and buy groceries.

You didn't suggest what solution to apply. (Or, indeed, precisely what you consider the actual problem...there were at least 3 mentioned in the comment chain.)

No. Intelligence cannot define goals, only "sub-goals", i.e. things you need to do in order to move closer to achieving your goal. Intelligence selects means to achieve goals, but it can't define the goals themselves.

You're confusing "intelligence" with "goals". That's like confusing theorems with axioms. You can challenge the theorems. Say, for instance, the the proof is invalid. You can't challenge axioms (within the system). And you can't challenge the goals of the AI. You can challenge the plans it has to achieve them.