Using Moores law we can postulate that it takes 17 years to increase computational power a thousand fold and 34 years to increase it a million times.
You are extrapolating Moore's law out almost as far as it's been in existence!
We could make it a million times more efficient if we trim the fat and keep the essence.
It's nice to think that, but no one understands the brain well enough to make claims like that yet.
You are extrapolating Moore's law out almost as far as it's been in existence!
Yeah.
Transistor densities can't increase much further due to fundamental physical limits. The chip makers all predict that they will not be able to continue at the same rate (and been predicting that for ages).
Interestingly the feature sizes are roughly the same order of magnitude for brains and chips now (don't look at the neuron sizes, by the way, a neuron does far, far more than a transistor).
What we can do is building chips in multiple layers, but because making a layer ...
Claim: The first human-level AIs are not likely to undergo an intelligence explosion.
1) Brains have a ton of computational power: ~86 billion neurons and trillions of connections between them. Unless there's a "shortcut" to intelligence, we won't be able to efficiently simulate a brain for a long time. http://io9.com/this-computer-took-40-minutes-to-simulate-one-second-of-1043288954 describes one of the largest computers in the world simulating 1s of brain activity in 40m (i.e. this "AI" would think 2400 times slower than you or me). The first AIs are not likely to be fast thinkers.
2) Being able to read your own source code does not mean you can self-modify. You know that you're made of DNA. You can even get your own "source code" for a few thousand dollars. No humans have successfully self-modified into an intelligence explosion; the idea seems laughable.
3) Self-improvement is not like compound interest: if an AI comes up with an idea to modify it's source code to make it smarter, that doesn't automatically mean it will have a new idea tomorrow. In fact, as it picks off low-hanging fruit, new ideas will probably be harder and harder to think of. There's no guarantee that "how smart the AI is" will keep up with "how hard it is to think of ways to make the AI smarter"; to me, it seems very unlikely.