Comment by almost1337@lemm.ee on How it started vs. How it's going

I mean, the proof is sitting there wearing your clothes. General intelligence exists all around us. If it can exist naturally, we can eventually do it through technology. Maybe there needs to be more breakthroughs before it happens.

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MadhuGururajan@programming.dev

11 points

14 days ago

“more breakthroughs” spoken like we get these once everyday like milk delivery.

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mindbleach@sh.itjust.works

-3 points

13 days ago

I mean - have you followed AI news? This whole thing kicked off maybe three years ago, and now local models can render video and do half-decent reasoning.

None of it’s perfect, but a lot of it’s fuckin’ spooky, and any form of “well it can’t do [blank]” has a half-life.

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Korhaka@sopuli.xyz

4 points

13 days ago

Seen a few YouTube channels now that just print out AI generated content. Usually audio only with a generated picture on screen. Vast amounts could be made so cheaply like that, Google is going to have fun storing all that when each only gets like 25 views. I think at some point they are going to have to delete stuff.

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mindbleach@sh.itjust.works

0 points

13 days ago

Dipshits going “I made this!” is not indicative of what this makes possible.

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MadhuGururajan@programming.dev

2 points

12 days ago

I kid you not, I took ML back in 2014 as a extra semester in my undergrad. The complaints then were the same as complaints now: too much power requirement, too many false positives. The latter of the two has evolved into hallucinations.

If normal people going “I made this!” is not convincing enough that it is easily identified then who is this going to replace? you still need the right expert right? all it creates is more work for experts to come and fix broken AI output.

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2 points

13 days ago

If you follow AI news you should know that it’s basically out of training data, that extra training is inversely exponential and so extra training data would only have limited impact anyway, that companies are starting to train AI on AI generated data -both intentionally and unintentionally, and that hallucinations and unreliability are baked-in to the technology.

You also shouldn’t take improvements at face value. The latest chatGPT is better than the previous version, for sure. But its achievements are exaggerated (for example, it already knew the answers ahead of time for the specific maths questions that it was denoted answering, and isn’t better than before or other LLMs at solving maths problems that it doesn’t have the answers already hardcoded), and the way it operates is to have a second LLM check its outputs. Which means it takes,IIRC, 4-5 times the energy (and therefore cost) for each answer, for a marginal improvement of functionality.

The idea that “they’ve come on in leaps and bounds over the Last 3 years therefore they will continue to improve at that rate isn’t really supported by the evidence.

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mindbleach@sh.itjust.works

2 points

13 days ago

*

We don’t need leaps and bounds, from here. We’re already in science fiction territory. Incremental improvement has silenced a wide variety of naysaying.

And this is with LLMs - which are stupid. We didn’t design them with logic units or factoid databases. Anything they get right is an emergent property from guessing plausible words, and they get a shocking amount of things right. Smaller models and faster training will encourage experimentation for better fundamental goals. Like a model that can only say yes, no, or mu. A decade ago that would have been an impossible sell - but now we know data alone can produce a network that’ll fake its way through explaining why the answer is yes or no. If we’re only interested in the accuracy of that answer, then we’re wasting effort on the quality of the faking.

Even with this level of intelligence, where people still bicker about whether it is any level of intelligence, dumb tricks keep working. Like telling the model to think out loud. Or having it check its work. These are solutions an author would propose as comedy. And yet: it helps. It narrows the gap between “but right now it sucks at [blank]” and having to find a new [blank]. If that never lets it do math properly, well, buy a calculator.

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SaraTonin@lemm.ee

2 points

12 days ago

I’m not saying they don’t have applications. But the idea of them being a one size fits all solution to everything is something being sold to VC investors and shareholders.

As you say - the issue is accuracy. And, as you also say - that’s not what these things do, and instead they make predictions about what comes next and present that confidently. Hallucinations aren’t errors, they’re what they were built to do.

If you want something which can set an alarm for you or find search results then something that responds to set inputs correctly 100% of the time is better than something more natural-seeming which is right 99%of the time.

Maybe along the line there will be a new approach, but what is currently branded as AI is never going to be what it’s being sold as.

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