Comment by Houshalter | Hacker News Reader

Comment by Houshalter | Hacker News Reader

And Brooks doesn't understand Musk. He's not saying current AI is a threat. He's talking about the very long term future. What AI will be like in 30 years, or even further.

Its inevitable we will eventually solve AI. And when that day comes it will be dangerous. How easy do you think it is to control a being thousands of times smarter than you? If it was invented today we would have no ability to control it. Our best AI control mechanisms are just pressing a button to reward or punish it for it's behavior. You can't imagine any way that would fail?

Our slightly larger brains made the difference between swinging in trees and walking on the moon. But we are only the very first intelligence to evolve. Its unlikely we are anywhere near the peak of what is possible.

And this will likely happen in our lifetimes. The median expected date estimated by AI researchers is in the 2040s. Sure they can't possibly predict it very well, but who else can? And there is something to the wisdom of crowds.

Why is super-human general AI inevitable?

Do you have references for this 2040 date? I'd love to see who's making this prediction.

Because there's nothing magical about the human brain. Evolution created it through just dumb mutation and selection. Under a bunch of ridiculous constraints. Like it had to use less than 10 watts of power, and weigh only a handful of pounds, and it had to be made of meat, and could only be iteratively improved from whatever happened to work at guiding locomotion in fish, etc.

Our current transistor tech is already orders of magnitude smaller, faster, and more efficient than neurons. There's no reason to expect the software stats of the brain are much better.

Here's one survey: http://www.nickbostrom.com/papers/survey.pdf

Interestingly, about 18% of the researchers said "never", but these answers didn't influence the posted CIs. Any reasonable imputation (say, "never = 2350") would both stretch those intervals by a lot and still underestimate the expert consensus.

They did account for them in the median AFAIK. Which is the number I gave and the most appropriate metric.

I don't see any mention of confidence intervals mentioned in the survey, so what are you talking about? Means and standard deviation are given. But they are mostly useless as the distribution is very skewed. They would be infinite if the "never" people were included of course.

The problem isn't just emulating the IQ of a typical human brain - which is a low bar, for the most part - but creating a transcendentally smart general intelligence.

Considering that we still have many issues with basic computing - not least working out how to write code that works reliably without constant manual updates - the suggestion that we're going to start building self-improving crash-proof hyperbrains any time soon is wishful thinking.

Realistically, we don't have the first clue how to start solving that problem. As of 2017 "Throw deep learning at it" is more of a fashion statement than a practical solution.

> Because there's nothing magical about the human brain.

Perhaps not "magical", but the human brain exists in a very unique situation because it's the only one we're trying to understand with other instances of itself.

Agreed. Also there is something "magical". Nobody understands how our consciousness works. While people will tell you it "arises from the brain" nobody has the slightest clue about how that works. It's a really hard problem when you think about it because our subjective experience has no mass , no length, no height, and is in that way not even material. Our consciousness is very important to our function, and without it, all artificial intelligence remains artificial and has no ultimate "reality check" on whether it's decisions are good or bad for it.

There's nothing "magical" about the human brain, but it's an extremely large, massively parallel device that with a clock speed of about 100 Hz.

When I say "massively parallel" I mean that a human brain (forget rest of nervous system) has about 80 G neurons. Each of which has a fan out between 10^4 and 10^5.

Architecturally this is quite different from a transistorized device with a much faster clock speed but a paucity of interconnect. Now few people say that we need to duplicate the brain (Numenta excepted -- although I have been half of a team that made a new brain and it was fun). After all an automobile does not look like a cheetah nor a plane look like an eagle. But this should give you some idea of the complexity of the problem.

(At Leela we are building something that approaches a more "brain" like computation when compared to, say, deep Q learning, and even for us, the equivalent of 2 M neurons requires about 16 TB of RAM).

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