You have to be more specific with the timeline. Transistors were invented in 1925 but received little interests due to many technical problems. It took three decades of research before the first commercial transistors were produced by Texas Instruments in 1954.

Gordon Moore formulated his eponymous law in 1965, while he was director of R&D at Fairchild Semiconductor, a company whose entire business consisted in the manufacture of transistors and integrated circuits. By that time, tens of thousands transistor-based computers were in active commercial use.

I don't have a source on this, but I remember an anecdote from Kurzweil that scientists who worked on early transistors were extremely skeptical about the future of the technology. They were so focused on solving specific technical problems that they didn't see the big picture. Whereas an outside could have just looked at the general trend and predicted a doubling every 18 months, and they would have been accurate for at least 50 years.

So that's why I wouldn't trust various ML experts like Ng that have said not to worry about AGI. No, the specific algorithms they work on are not anywhere near human level. But the general trend, and the proof that humans aren't really that special, is concerning.

I'm not saying that you should just trust Yudkowsky or me instead. And expert opinion still has value. But maybe pick an expert that is more "big picture" focused? Perhaps Jürgen Schmidhuber, who has done a lot of notable work on deep learning and ML, but also has an interest in general intelligence and self improving AIs.

And I don't have any specific prediction from him on when we will reach AGI. But he did say last year that he believes we will reach monkey level intelligence in 10 years. Which is quite a huge milestone.

Another candidate might be the group being discussed in this thread, Deepmind. They are focused on reaching general AI instead of just typical machine vision work. That's why they have such a strong interest in game playing. I don't have any specific predictions from them either, but I do get the impression they are very optimistic.

"Dancing bear" is a term. It doesn't literally indicate that he's comparing black people to animals.

I thought the heuristic was "if I think I passed the hotel, I was going too fast to notice. I better slow down so I see it when I come up on it, or so I might recognize a landmark/road that indicates I went too far." We slow down not because we are splitting the difference between turning around and continuing on. We slow down to make it easier to gather more information, a perfectly rational response.

Interesting point. Can you give an example of this knowledge?

I'm working on a PhD myself (in engineering), but the main things I feel I get from this are access to top scholars, mentoring, structure, and the chance to talk with others who are interested in learning more and research. One could also have access to difficult to obtain equipment in academia, but a large corporation could also provide such equipment. In principle I don't think these things are unique to academia.

Yeah, I am sure enough about this not happening that I am willing to place bets. There is an enormous amount of intangibles Coursera can't give you (I agree it can be useful for a certain type of person for certain types of aims).

Agree that being inside academia is probably a lot bigger deal than people outside it really appreciate. We're about to see the first generation that grew up with a really ubiquitous internet come to grad school age though. Currently in addition to the assumption that generally clever people will want to go to university, we've treated it as obvious that the Nobel prize winning clever people will have an academic background. Which has been pretty much mandatory, since that used to be the only way you got to talk with other academicians and to access academic publications.

What I'm interested in now is whether in the next couple decades we're going to see a Grigori Perelman or Shinichi Mochizuki style extreme outlier produce some result that ends up widely acknowledged to be an equally big deal as what Perelman did, without ever having seen the inside of an university. You can read pretty much any textbook or article you want over an internet connection now, and it's probably not impossible to get professional mathematicians talking with you even when they have no idea who you are if it's evident from the start that you have some idea what their research is about. And an extreme outlier might be clever enough to figure things on their own, obsessive enough to keep working on them on their own for years, and somewhat eccentric so that they take a dim view on academia and decline to play along out of principle.

It'd basically be a fluke statistically, but it would put a brand new spin on the narrative about academia. Academia wouldn't be the obvious one source of higher learning anymore, it'd be the place where you go when you're pretty smart but not quite good and original enough to go it alone.

By this line of reasoning almost all past theories can the discredited. People use a theory to make predictions and act on them. Only later do you learn the shortcomings. If you don't have empiricism you don't even have a tool to systematically notice your error. I think this is a fully general counter argument.

Quantum theories are responsible for a lot of the quack ideas too. I fear this isn't enough to make an idea ridiculous.

It's not ridiculous because it's a concept that has been used to advance science. For many practical applications it makes sense to treat living entities different from non-living one's just as for many practical applications Newton's physics is useful. The fact that modern physics showed Newton's physics to be inaccurate doesn't make it ridiculous.

.If being majority Christian means being tyrannical, the USA is currently a tyranny, and so is every other Western country.

The US is majority Christian, but not majority alieving-Christians.