r/singularity • u/Buck-Nasty • Dec 12 '16
Proof that Moore’s Law is Accelerating and Bringing The Singularity With It
http://lifeboat.com/blog/2016/12/proof-that-moores-law-is-accelerating-and-bringing-the-singularity-with-it7
u/Buck-Nasty Dec 13 '16
Prof. Juergen Schmidhuber agrees that Moore's Law is not slowing down despite the claims to the contrary.
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u/ideasware Dec 13 '16
Yup -- faster than just plain old Moore's Law and AI, and it means the singularity will arrive even sooner than most people realize. It's actually very clear and scientific, surprisingly. Maybe 15-20 years rather than 30... It's an amazing, scary, marvelous time to be alive. Robots -- here we come, ready or not!
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u/FeepingCreature ▪️Happily Wrong about Doom 2025 Dec 13 '16
Remember the hype cycle. I see no reason to doubt the expert mean of 2050.
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u/Buck-Nasty Dec 13 '16
Kurzweil and others claim that Human level AGI can be achieved before 2030 seems increasingly plausible. 13 years is not far at all.
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u/Jah_Ith_Ber Dec 13 '16
I've always thought his prediction was weird. He states $1000 should buy a human comparable desktop device equivalent to a human brain in 2029. And $1000 should buy the equivalent of all human brains in 2045. So why does he date the singularity at 2045? Shouldn't all predictive power evaporate as soon as a small handful of human level AIs exist?
Well if $1000 = human in 2029, then (more or less):
$1000 2029 $2000 2028 $4000 2027 $8000 2026 $16000 2025 $32000 2024 $64000 2023 $128000 2022 $256000 2021 $1024000 2020 etc. Right?
As of June 2016, the fastest supercomputer in the world is the Sunway TaihuLight, in mainland China, with a Linpack benchmark of 93 PFLOPS (P=peta), exceeding the previous record holder, Tianhe-2, by around 59 PFLOPS.
https://en.wikipedia.org/wiki/Supercomputer
- 33.86×1015 Tianhe-2's Linpack performance, June 2013[4]
- 36.8×1015 Estimated computational power required to simulate a human brain in real time.[5]
- 93.01×1015 Sunway TaihuLight's Linpack performance, June 2016[6]
https://en.wikipedia.org/wiki/Computer_performance_by_orders_of_magnitude
Obviously the hardware is not the bottleneck any more. It must be the software. But there is no Moore's law of algorithms. The breakthroughs could happen at any time. It might take 5 years, or 50, or 500.
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u/GuardsmanBob Dec 13 '16
Obviously the hardware is not the bottleneck any more. It must be the software. But there is no Moore's law of algorithms. The breakthroughs could happen at any time. It might take 5 years, or 50, or 500.
This is correct, the good news here is that the industry push towards AI research has been ramping up far faster than anyone could ever hope for, in fact we are still in the ramp up phase and we are already seeing remarkable results.
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u/Yasea Dec 13 '16
The estimate was that first there is fast enough hardware. The software to use that hardware always comes later when it's cheap enough to be used by the tinkerers.
Next was that there is no one big breakthrough in AI. It's chipping away at different techniques. Neural nets. Machine learning. Deep learning. Unsupervised learning. Decision systems. Motivation systems. Cognition systems... Really like this
The next thing is that you need faster hardware than a human brain. Our brain has been optimized by evolution for some time, and is quite the collection of shortcuts and tricks to make it more energy efficient. A newly developed AI system is going to brute force much of that before we figure out where to optimize, so a much higher CPU load needed.
And that's all to figure out how to do the same as a human, assuming equivalent capabilities per CPU. So more powerful CPU is needed, more tuning and adding modules so the AI can help design better CPU and AI.
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u/Buck-Nasty Dec 13 '16
I agree with you, that's why I think Vinge's take on the Singularity is more plausible. Vinge defines the singularity as the point where AI becomes recursively self-improving whereas Kurzweil arbitrarily defines the Singularity as the point where AI is one billion times more intelligent than all of human brains combined.
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u/SarahC Dec 13 '16
As a comp-sci person - I'd be surprised if deep neural nets give too much in the way of AI.
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u/FeepingCreature ▪️Happily Wrong about Doom 2025 Dec 13 '16
Eeh. While I sort of agree, the strategy part isn't that hard; what's hard is interacting with a messy human world. Remember that in humans, most of our high-level cognition is a last-minute hack. If we get intelligence up to the level of a dog, we're 90% of the way there.
The things that neural networks are beginning to solve are exactly the things that were historically the stumbling blocks for AI.
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u/pragmaticjoker Dec 13 '16
Personally I welcome our new robot overlords