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Comment by posnet | Hacker News Reader

But Kurzweil is banking on the exponential growth of technology. According to his reasoning (and using Moore's Law of 2x performance every 18 months, as a guideline) we are less than 1% of the way towards the goal (assuming 100% is passing the Turing test).

Now I don't have any idea if he will be correct, or even what a machine that will pass the Turing test will be like. But if you accept the premise that technological advancement is on an exponential curve, half way in terms of progress will be much closer to 2029 than half way in time.

(Note I am not saying that technology is exponential or that it is following Moore's law or that it will be exponential forever or that 2x every 18 months is fact, its simply an extension of Kurzweil reasoning to its logical conclusion.)

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Exponential improvements aren't very helpful if you're working on exponentially hard problems.

Exponential growth of technology hasn't solved machine intelligence (by direct simulation) for essentially the same reason why it hasn't solved numerical weather prediction or made quantum computers pointless.

To expand on weather prediction: you need an order of magnitude improvement in computer speed to make weather forecasts with the same quality one day earlier. So exponential growth of computing power means linear growth in terms of subjective benefit.

To be fair, we don't understand the difficulty of modeling intelligence anywhere near as well as we understand the difficulty of modeling the weather. But, given the limits of our current abilities to simulate the brain, it seems reasonable to guess that similar principles could hold.

What's exponentially hard about it?

Talking like a human is a bounded problem, it has no margin for growing (or shrinking). Any kind of growth in capacity will help against it.

Fair enough, but that's like saying "intergalactic travel is a bounded problem"

Well, it is. You can't claim it grows in any specific way, because it does not grow (at least at the Local Group).

You can not claim that exponential growth on space travel tech isn't enough to get intergalactic travel. Any non-declining rate of progress will get us there eventually. (Whatever "exponential growth" means on this context, for computation it's very well defined. Also, whatever realist is on non-declining rate of progress, the rate for computation is clearly increasing.)

>Exponential improvements aren't very helpful if you're working on exponentially hard problems.

Sure they are! They reduce it to a problem that's only polynomially hard! :-p

>Exponential growth of technology hasn't solved machine intelligence (by direct simulation) for essentially the same reason why it hasn't solved numerical weather prediction or made quantum computers pointless.

Okay, but that's a rather high bar to judge it against. Humanity has solved many lesser machine intelligence problems, like web search, voice recognition, routing, and recommendation. Though I agree the relevant exponential growth was in the power of the algorithms, not so much the hardware.

I don't see why "weather forecasting" is similar to "brain simulation" in difficulty. The comparison would be more valid if the problem were "brain forecasting", that is to build an AI that would behave exactly the same as a particular human, but that's an even harsher measure of intelligence than the turing test that I doubt anyone would take seriously. I'm not saying the brain's easy to simulate, it's just the analogy here seems shaky. Where is the source of exponential difficulty?

If you have no idea what you are doing then doing it exponentially faster won't help much.

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