If you go that far back in the AI world you are certainly aware of selection bias, recall bias and response bias, all of which influence what you just said. So it’s not that the “majority” of experts said it would take hundreds of years.. It’s the majority of experts peopel felt like talking about on a forum you were a part of, that you happen to remember, and that people happened to respond to.

In 2013 most experts were saying “hundreds of years”?? We need a fuckin source on that one bro

Given that you already ignored one request for a source I’m guessing you’ll ignor this one too?

They certainly cannot provide a valid source for that.

This is like the drake meme. Average prediction of experts? No. Three cherry picked examples? Yes.

> Neural networks can only associate words or the equivalent in images. They don't actually know what words or images mean.

Well this begs the question of what it means to “actually know what words or images mean”.

I would posit that we don’t actually know that we are any more advanced than this.

You see an image of a computer and you know what the computer is and what it means. But that’s because your brain matches the image of the computer to computers you’ve already used and your experiences with those computers. What is different about neural networks?

I’d be curious if there’s a poll of AI experts somewhere about this specific topic so I can know if the majority of experts agree or disagree with this opinion.

That seems like an exceptionally broad definition of “pseudo-AGI” that by most people’s definitions of “phenomenally useful”, already exists and has for some time. ChatGPT is already phenomenally useful in daily life as it is.

> Also, I'm a bit skeptical that the amount of progress that's been made in AI the past year (which has been impressive, no doubt) merits THAT much of a shave-off from the February 2022 prediction. Just my thoughts.

Correct, and if anything, the mere fact that the prediction has changed by over a decade in the span of 12 months is strong evidence of exactly what you’re saying — this prediction is made by people who aren’t really in the know.

If the weather man told you it was going to be 72 and sunny tomorrow and then when you woke up tomorrow he said actually it’s going to be -15 and a blizzard you would probably think hmmm, maybe this guy doesn’t know what the fuck he’s talking about.

> Statistically, crowdsourcing does better at converging to the actual answer.

Statistician here, and this is a good example of a relatively meaningless statistic, to be honest. Crowdsourcing statistically tends to be more accurate than just asking one person, in the average case, for what should be mathematically obvious reasons.

But the “average case” isn’t applicable to literally every situation. I would posit that when we start to talk about areas of expertise that require a PhD to even begin to be taken seriously for your opinion, crowdsourcing from unverified users starts to become a whole lot more biased.

Source on that 8 years number? Would certainly be quite a compelling argument if a random sampling of exclusively well funded AI PhDs had a median prediction of 8 years.

I’d like to see a source for this.