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Kurzweil's rebuttal to Paul Allen

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Re: Kurzweil's rebuttal to Paul Allen

#111
post #29

What about energy? It's true that if you look at most areas of technology they are advancing rapidly. Except energy. Energy has stagnated since the 1950s. I'm on the fence on this issue, but there are many very intelligent and knowledgeable people who are predicting a kind of anti-singularity: in the 21st century, fossil fuel depletion will send us way back, perhaps even de-industrialize most societies. Is our civili…

The energy problem was solved by Freeman Dyson et. al. in the 50s at Los Alamos [1]. Here are his paraphrased proposals:

Kardashev Level I (http://en.wikipedia.org/wiki/Kardashev_scale)

Dyson fusion engines.

He's not talking about unviable Tokamak designs (http://en.wikipedia.org/wiki/Tokamak), but something much simpler. Basically use H-bombs (which are the only tried and tested fusion technology) to drive a large internal combustion engine. The energy released by each explosion is stored by using it to lift water back into hydraulic dams.

Kardashev Level II

Dyson rings and shells (http://en.wikipedia.org/wiki/Dyson_shell).

Kardashev Level III

"Lather, rinse and repeat" with Dyson shells.

[1] Just as all problems in computer science were solved (in principle) at Xerox PARC in the 70s, all energy problems were solved (in principle) at Los Alamos in the 50s.

Re: Kurzweil's rebuttal to Paul Allen

#112
post #29

What about energy? It's true that if you look at most areas of technology they are advancing rapidly. Except energy. Energy has stagnated since the 1950s. I'm on the fence on this issue, but there are many very intelligent and knowledgeable people who are predicting a kind of anti-singularity: in the 21st century, fossil fuel depletion will send us way back, perhaps even de-industrialize most societies. Is our civili…

> What about energy? >It's true that if you look at most areas of technology they are advancing rapidly. Except energy. Energy has stagnated since the 1950s. This is demonstrably false. Solar power generation, for example, has been enjoyinging the same kind of Moore's Law exponential price/power over the past 15 years that computer processing power has. This is hardly surprising due to the fact that silicon wafer sol…

OK, but this is not "real" until you have end-to-end solar, as in starting from sand and ending up with installed solar panels, with every step along the way solar-powered, no fossil fuels, not even in the truck to deliver them to the end user. Because what we do have right now is end-to-end fossil. The main use of fossil fuels now should be bootstrapping the next level, not everyday use.

Re: Kurzweil's rebuttal to Paul Allen

#113
post #14

It's startling to me that everything I do comes from 50 megabytes of source code.

It hasn't been so since before you were born. Your experiences in your mother's womb have shaped your brain. All that your DNA contains is the basic rules on how to assemble a generic human brain. What happens to it has far greater consequence on what you become.

I like to joke I was born an engineer. While it's true I have always been curious towards all things technological (I was born during the height of the Apollo program and, as a kid, wanted to be an astronaut) but parental support (getting lego-like kits with transmissions, gears, motors, good books and a good school) landed me on one of the most prestigious engineering schools in Brazil where I was further "perfected" by some good teachers (and some awful ones - you have to learn to avoid them, after all).

Re: Kurzweil's rebuttal to Paul Allen

#114
post #6

Earlier quoted context omitted.

> Even so, I fully expect memristors to deliver strong AI. Why would they? Is strong AI a function of storage capacity or speed? An AI running at 1/100th of what a future AI may be capable of is still an AI and I can't see how a mere improvement of a couple of orders of magnitude would do what decades of Moore's law have failed to do so far. If strong AI was just a matter of speed then we could theoretically take any…

I would say that strong AI could appear sooner than otherwise with faster hardware. This is because, the earliest algorithms for strong AI are likely to be flawed and imperfect. These imperfections can be compensated for by faster processing. Think of the earlier chess playing algorithms. Although Deep Blue was able to defeat Gary Kasparov, the algorithms themselves were relatively primitive compared to modern chess…

You make an excellent point about how early imperfections in the algorithms could be fixed as they evolve through feedback, and that this step-process running faster would get us the desired (evolved) algorithms quicker.

But couldn't we accomplish this with distributed processing rather than faster hardware?

Re: Kurzweil's rebuttal to Paul Allen

#115
post #6

Earlier quoted context omitted.

> Even so, I fully expect memristors to deliver strong AI. Why would they? Is strong AI a function of storage capacity or speed? An AI running at 1/100th of what a future AI may be capable of is still an AI and I can't see how a mere improvement of a couple of orders of magnitude would do what decades of Moore's law have failed to do so far. If strong AI was just a matter of speed then we could theoretically take any…

Is strong AI a function of storage capacity or speed? Yes, absolutely! I actually think the most appropriate benchmark is memory bandwidth, which hasn't been improving as fast as FLOPS or storage capacity. It's not a matter of running a strong AI at 1/100 speed on today's fastest supercomputer. It would be more like 1 billionth or trillionth speed. The reason for our disappointingly slow progress in AI over the years…

I'd really appreciate it if you could suggest why we couldn't implement similar algorithms as the brain, that possibly require a massive number of fetches & executions simultaneously (guessing this is where memory bandwidth plays in), but have the results show up much slower.

Shouldn't it be possible to have artificial AI mimicking human brain algorithms at 1/100th the speed, where perhaps a single thought based on learned information takes hours, instead of seconds?

Re: Kurzweil's rebuttal to Paul Allen

#116
post #110

Earlier quoted context omitted.

> What about energy? >It's true that if you look at most areas of technology they are advancing rapidly. Except energy. Energy has stagnated since the 1950s. This is demonstrably false. Solar power generation, for example, has been enjoyinging the same kind of Moore's Law exponential price/power over the past 15 years that computer processing power has. This is hardly surprising due to the fact that silicon wafer sol…

Newer thin-film solar panels represent a jump in paradigm isn't this what Allen said in his critique? scientific achievement doesn't just grow exponentially - there are those "jumps in paradigm" that move us forward, but they're relatively rare and unpredictable.

As Kurzweil pointed out, Allen hadn't even read his book. In it Kurzweil provides copious volumes of data to support his claim that the overall trend is still exponential. As one paradigm starts to run out of steam, there is greater and greater research pressure to find the next. Much as vacuum tubes improved exponentially until nearing their limit upon which transistors and then later ICs took over, the same has been happening with energy.

For the past 400 years human energy consumption per person has been growing at a relatively smooth exponential curve, despite changes from wood-burning to coal to whale oil to petroleum. Even a cursory unbiased study on the subject will show that. Interestingly, for nearly the entire time, malthusian doomsday prophets have enjoyed more popularity than more rigorous analysts.

Re: Kurzweil's rebuttal to Paul Allen

#117
post #87

Earlier quoted context omitted.

It seems to me that Kurzweil is on rather strong grounds when he argues in effect that 25Mbytes is a safe conservative upper bound on the information needed to specify a human infant brain. This is the best I could do: http://www.sciencedaily.com/releases/2005/01/050111115721.ht... I can't find the actual scientific papers. Anyway, form the article above: The lack of correlation between genome size and an organism’s…

You're saying a lot there, so rather than create a wall of text in response I'd like to boil it down a bit - assume N=25Mb, give or take an order of magnitude: Are you making the claim that the N bits of DNA involved in coding the brain can encode more than 2^N neural algorithms? Or do you think that the particular set of 2^N (assuming no redundancy, which is generous...) neural algorithms that N bits of DNA can enco…

Are you making the claim that the N bits of DNA involved in coding the brain can encode more than 2^N neural algorithms?

That's exactly what the article above explains. Did you read it?

Or do you think that the particular set of 2^N (assuming no redundancy, which is generous...) neural algorithms that N bits of DNA can encode are more likely to result in intelligence than a random sampling of algorithms of equivalent Kolmogorov complexity?

I am not sure I understand the question. Are you asking if I believe the brain is a large but mostly simply designed neural network? If that is the question, then no.

Or are you claiming that epigenetic factors are able to reliably transmit significantly more than N bits of mission-critical data across the generations

I am claiming that do get a human you must "host" the human genome in a pre-existing human. Sticking it in a mouse will not result in a human. What does that imply?

that epigenetic evolution is likely to thank for devising the human intelligence algorithm rather than evolution of DNA?

I don't see two kind of evolutions there. It's all just human evolution genome and all. After all, it's not like human dna is out there evolving in something else besides humans.

In humans the difference is muddled because the spec goes through such ridiculously complicated machinery to become the product

Yes!

but when it comes to designing algorithms, that complicated machinery might as well be a random shuffle for all it matters to the algorithm's proper functioning

What implies that? How do you go form yes a hugely complex compiler is necessary, to no we can just randomly shuffle the code and it'll be just as good?

How many bits does it take to describe the string "aaaaaaa"? Not many. How many bits to describe the human genome to a scientist? I'll just gzip it and email it and were done, awesome!

How many bits to describe a human brain or how to turn that genome into a human brain? Well lets see, its a complex self-modifying process, the human brain expands the number of sequence products exponentially and interestingly the mouse brain does not do this.

In mice the complexity difference between their brain and their genome is linear. In humans it is not.

In mice the Kolmogorov complexity of their brain is equal to the Kolmogorov complexity of their genome + some linear factor.

In humans it's the Kolmogorov complexity of our genome + a lot more.

How much is "a lot more"? No idea.

Is all of this inherited? Yes, partly through the genome, partly through the fact that that genome must be planted in a pre-existing human. Again, if you swap it out with a mice genome humans won't be giving birth to healthy mice and mice won't be producing humans.

You can move a simple sequence across species, like a glowing protein form jellyfish to rabbits for example. You can not move whole genomes in higher order life forms.

I think the disagreement between early and late singularity people often comes down to is the human brain mostly a large but simple mass of neurons or not.

I think computer scientist are often in the it's just a large neural network camp. Brain scientists are in the it's much more complicated than that camp. As a computer scientist and software engineer who's worked in biotech for many years, I agree with the brain scientists.

Re: Kurzweil's rebuttal to Paul Allen

#118
post #101
post #82

Earlier quoted context omitted.

How much oil is in off the East Coast passive margin? 20 bboe (which is twice the best estimates of MMS)? That would make it on par with the North Slope in Alaska, an elephant field. That's 3 years or less of US consumption, or about 7 months of global consumption. BFD. And that comment about the Deepwater Horizon not being able to drill closer to the shore... that's eyepopping. The shallow-water GoM in the Mississip…

And that comment about the Deepwater Horizon not being able to drill closer to the shore... that's eyepopping. The shallow-water GoM in the Mississippi Delta has been drilled for decades. Shallow water drilling has been disincentivized in favor of deep water drilling for several years in part because of tourism and NIMBYism concerns. People do not want to see drills from the shore. This is well known in the sector. Y…

I have no incentive for further discussion with you, so I'm not sure why I'm bothering to respond.

I'll just say that I'm well aware of the politics and technical issues in the E&P sector as well as domestic and international energy consumption (across all fuel types), and that you are on the border of being completely uninformed on this issue. Frankly, it's sad. You have an opinion, and have used Google to find articles that validate it... and here I am, having read RigZone for years, participating on Oil Drum, having independently given myself an undergrad+ education in petroleum geology, having invested real money in oil companies and reading dozens if not hundreds of 10-Qs and 10-Ks for domestic small to mid cap producers (whose assets span onshore, offshore, UDW, shale, and bitumen). And nothing I can say will jolt you out of your comfortable mindset where there is abundant petroleum for the taking if only DC would step back and let capitalism run its course.

Re: Kurzweil's rebuttal to Paul Allen

#119

Earlier quoted context omitted.

Is strong AI a function of storage capacity or speed? Yes, absolutely! I actually think the most appropriate benchmark is memory bandwidth, which hasn't been improving as fast as FLOPS or storage capacity. It's not a matter of running a strong AI at 1/100 speed on today's fastest supercomputer. It would be more like 1 billionth or trillionth speed. The reason for our disappointingly slow progress in AI over the years…

I'd really appreciate it if you could suggest why we couldn't implement similar algorithms as the brain, that possibly require a massive number of fetches & executions simultaneously (guessing this is where memory bandwidth plays in), but have the results show up much slower. Shouldn't it be possible to have artificial AI mimicking human brain algorithms at 1/100th the speed, where perhaps a single thought based on l…

You misunderstand. I'm saying we could, but the slowdown wouldn't be 1/100. It would be more like 1/1 billion. At that speed, it would take years to simulate a second of brain time. Not only would that be useless, it would be impossible to know if you'd actually implemented it right without being able to test it in a reasonable timeframe. That's why we'll only be able to develop brain-like AI once our computers are much faster.

Re: Kurzweil's rebuttal to Paul Allen

#120

Earlier quoted context omitted.

I'd really appreciate it if you could suggest why we couldn't implement similar algorithms as the brain, that possibly require a massive number of fetches & executions simultaneously (guessing this is where memory bandwidth plays in), but have the results show up much slower. Shouldn't it be possible to have artificial AI mimicking human brain algorithms at 1/100th the speed, where perhaps a single thought based on l…

You misunderstand. I'm saying we could, but the slowdown wouldn't be 1/100. It would be more like 1/1 billion. At that speed, it would take years to simulate a second of brain time. Not only would that be useless, it would be impossible to know if you'd actually implemented it right without being able to test it in a reasonable timeframe. That's why we'll only be able to develop brain-like AI once our computers are m…

Appreciate the reply. Seems I did misunderstand.

I find it hard to agree, that despite the nanosecond latency times and the terabytes of throughput we can wring out of single computing devices(gpu's etc), we couldn't simulate brain-like AI faster than a billionth of what it should be.

You're probably right though.

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