this post was submitted on 23 Nov 2024
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I'm usually the one saying "AI is already as good as it's gonna get, for a long while."

This article, in contrast, is quotes from folks making the next AI generation - saying the same.

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[–] [email protected] 16 points 7 hours ago (2 children)

It's pretty obvious that they will hit a ceiling.

Quick buck is over. And now it's time again for base research to create better approach.

I really wish we had a really advanced AI with reasonable resource consumption within my lifetime. I don't think it's unreasonable as we have got really far in the last 30 years of computational technology.

[–] [email protected] 4 points 3 hours ago (1 children)

We've come a long way in computing, but the computational power difference between a human brain and a computer is significant. LLMs were just a smart way to have computers learn pattern recognition. While important, it isn't anything close to artificial general intelligence (AGI), which is what the term AI usually means.

[–] [email protected] 3 points 19 minutes ago

Yeah.   AI may grind for a while but hardly anyone has put the current stuff to work, yet.   We will be feeling the benefits of what is released right now for a decade to come.   I am working on a very rudimentary application that will use ML at work and it won't come out for 12 more months, and it hardly does anything but make the most obvious decisions 10m times faster than I can.   But it's going to fundamentally change our labor model.    

There are regular folks applying amazing technologies that go way beyond content generation.      

The tech may grind but the application of that tech is barely getting its feet and should run hard for a decade.

[–] [email protected] 2 points 4 hours ago (1 children)

This cycle was really fast

[–] [email protected] -1 points 3 hours ago

They might be right but I read some of the linked articles on this blog (?), the authors just come off as not really knowing much about current AI technologies, and at the same time very very arrogant.

[–] [email protected] 60 points 23 hours ago (2 children)

I understand folks don't like AI but this "article" is like a reddit post with lots of links to subjects which are vague and need the link text to tell us what is important, instead of relying on the actual article.

[–] [email protected] 1 points 20 minutes ago

I see a lot of links here and there to this domain but I haven’t really read anything from there. I’m literally just scrolling through these comments to see if anyone has a comment like yours.

My impression was that it’s just a blog but you calling it “a reddit post” is also interesting. What’s with this site? It looks like a decent amount of people think these takes are interesting. I have to deal with a lot of management people who love AI buzzwords, so a whole blog just ripping into it really speaks to me.

[–] [email protected] 29 points 23 hours ago* (last edited 23 hours ago)

What the fuck you aren't kidding. I have comment replies to trolls that are longer than that article. The over the top citations also makes me think this was entirely written by an actual AI bot that was lrompted to supply x amoint of sources in their article. Lol

[–] [email protected] 73 points 1 day ago (3 children)

It's absurd that some of the larger LLMs now use hundreds of billions of parameters (e.g. llama3.1 with 405B).

This doesn't really seem like a smart usage of ressources if you need several of the largest GPUs available to even run one conversation.

[–] [email protected] 6 points 13 hours ago

That's capitalism

[–] [email protected] 14 points 22 hours ago

Seeing as how the full unquantized FP16 for Llama 3.1 405B requires around a terabyte of VRAM (16 bits per parameter + context), I'd say way more than several.

[–] [email protected] 21 points 1 day ago (3 children)

I wonder how many GPUs my brain is

[–] [email protected] 47 points 23 hours ago (1 children)

It's a lot. Like a lot a lot. GPUs have about 150 billion transistors but those transistors only make 1 connection in what is essentially printed in a 2d space on silicon.

Each neuron makes dozens of connections, and there's on the order of almost 100 billion neurons in a blobby lump of fat and neurons that takes up 3d space. And then combine the fact that multiple neurons in patterns firing is how everything actually functions and you have such absurdly high number of potential for how powerful human brains are.

At this point, I'm not sure there's enough gpus in the world to mimic what a human brain can do.

[–] [email protected] 10 points 6 hours ago

That's also just the electrical portion of our mind. There are whole levels of chemical, and chemical potentials at work. Neurones will fire differently depending on the chemical soup around them. Most of our moods are chemically based. E.g. adrenaline and testosterone making us more aggressive.

Our mind also extends out of our heads. Organ transplant recipricants have noted personality changes. Food preferences being the most prevailant.

The neurons only deal with 'fast' thinking. 'slow' thinking is far more complex and distributed.

[–] [email protected] 19 points 1 day ago (2 children)
[–] [email protected] 2 points 12 hours ago (1 children)
[–] [email protected] 1 points 12 hours ago

You said GPUs, not CPUs and threading capabilities

[–] [email protected] 2 points 16 hours ago

The Answer to the Ultimate Question of Life, The Universe, and Everything

[–] [email protected] 9 points 1 day ago (1 children)

I don't think your brain can be reasonably compared with an LLM, just like it can't be compared with a calculator.

[–] GetOffMyLan 17 points 22 hours ago (1 children)

LLMs are based on neural networks which are a massively simplified model of how our brain works. So you kind of can as long as you keep in mind they are orders of magnitude more simple.

[–] [email protected] 1 points 1 hour ago

At some point it becomes so “simplified” it’s arguably just not the same thing, even conceptually.

[–] [email protected] 32 points 1 day ago (2 children)

OpenAI, Google, Anthropic admit they can’t scale up their chatbots any further

Lol, no they didn't. The quotes this articles are using are talking about LLMs not chatbots. This is yet another stupid article from someone who doesn't understand the technology. There is a lot of legitimate criticism for the way this technology is being implemented but FFS get the basics right at least.

[–] [email protected] 6 points 14 hours ago (1 children)

Claiming that David Gerrard an Amy Castor "don't understand the technology" is uh.... Hoo boy... Well it sure is a take.

[–] [email protected] 0 points 4 hours ago (1 children)

The title of the article is literally a lie which is easily fact checked. Follow the links to quotes in the article to see what the quoted individuals actually said about the topic.

[–] [email protected] -1 points 2 hours ago* (last edited 2 hours ago) (1 children)

Please learn the difference between "lying" and "presenting a conclusion."

[–] [email protected] 1 points 28 minutes ago

I know the difference. Neither OpenAI, Google, or Anthropic have admitted they can't scale up their chat bots. That statement is not true.

[–] MajorHavoc 16 points 22 hours ago (4 children)

Are you asserting that chatbots are so fundamentally different from LLMs that "oh shit we can't just throw more CPU and data at this anymore" doesn't apply to roughly the same degree?

[–] [email protected] 7 points 19 hours ago (5 children)

I feel like people are using those terms pretty well interchangeably lately anyway

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[–] [email protected] 26 points 1 day ago (1 children)

A 4 paragraph "article" lol

[–] [email protected] 38 points 1 day ago* (last edited 1 day ago) (1 children)

Are you suggesting “pivot-to-ai.com” isn’t the pinnacle of journalism?

[–] [email protected] 1 points 1 hour ago

Lol, I didn't even notice the name

[–] [email protected] 9 points 1 day ago* (last edited 1 day ago) (1 children)

Though, I don't think that means they won't get any better. It just means they don't scale by feeding in more training data. But that's why OpenAI changed their approach and added some reasoning abilities. And we're developing/researching things like multimodality etc... There's still quite some room for improvements.

[–] MajorHavoc 3 points 22 hours ago

Though, I don't think that means they won't get any better. It just means they don't scale by feeding in more training data.

Agreed. There's plenty of improvement to be had, but the gravy train of "more CPU or more data == better results" sounds like it's ending.

[–] [email protected] 8 points 1 day ago (2 children)

I smell a sentient AI trying to throw us off it's plans for world domination..

[–] MajorHavoc 4 points 22 hours ago* (last edited 20 hours ago)

Everyone ignore this comment please. I'm quite human. I have the normal 7 fingers (edit: on each of my three hands!) and everything.

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[–] [email protected] 7 points 1 day ago* (last edited 1 day ago)

It's a known problem - though of course, because these companies are trying to push AI into everything and oversell it to build hype and please investors, they usually try to avoid recognizing its limitations.

Frankly I think that now they should focus on making these models smaller and more efficient instead of just throwing more compute at the wall, and actually train them to completion so they'll generalize properly and be more useful.

[–] [email protected] 5 points 22 hours ago (2 children)

Looks, like AI buble is slowly coming to end just like what happned to crypto and NFT buble.

[–] [email protected] 5 points 14 hours ago

When did the crypto bubble end? Bitcoin is at an all time high....

[–] [email protected] 11 points 22 hours ago (2 children)

Sure, except for the thousands of products working pretty well with current gen. And it's not like it's over, now we've hit the limit of "just throw more data at the thing".

Now there aren't gonna be as many breakthroughs that make it better every few months, instead there's gonna be thousand small improvements that make it more capable slowly and steadily. AI is here to stay.

[–] [email protected] 2 points 13 hours ago

Getting the GPU memory requirements down would be huge as well.

[–] [email protected] 6 points 22 hours ago

The bubble popping doesn't have to do with its staying power, just that the days of, "Hey, I invented this brand new AI ~~that's totally not just a wrapper for ChatGPT~~. Want to invest a billion dollars‽" are over. AGI is not "just out of reach."

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