Slowing Moore's Law: Why You Might Want To and How You Would Do It

gwern

In this essay I argue the following:

Brain emulation requires enormous computing power; enormous computing power requires further progression of Moore’s law; further Moore’s law relies on large-scale production of cheap processors in ever more-advanced chip fabs; cutting-edge chip fabs are both expensive and vulnerable to state actors (but not non-state actors such as terrorists). Therefore: the advent of brain emulation can be delayed by global regulation of chip fabs.

Full essay: http://www.gwern.net/Slowing%20Moore%27s%20Law

In this essay I argue the following:

Brain emulation requires enormous computing power; enormous computing power requires further progression of Moore’s law; further Moore’s law relies on large-scale production of cheap processors in ever more-advanced chip fabs; cutting-edge chip fabs are both expensive and vulnerable to state actors (but not non-state actors such as terrorists). Therefore: the advent of brain emulation can be delayed by global regulation of chip fabs.

Full essay: http://www.gwern.net/Slowing%20Moore%27s%20Law

The existence of non-biomimetic technology does not prove that biomimetics are inherently impractical.

There's plenty of recent examples of successful biomimetics... Biomimetic solar: http://www.youtube.com/watch?v=sBpusZSzpyI Anisotropic dry adhesives: http://bdml.stanford.edu/twiki/bin/view/Rise/StickyBot Self cleaning paints: http://www.stocorp.com/blog/?tag=lotusan Genetic algorithms: http://gacs.sourceforge.net/

The reason we didn't have much historical success with biomimetics is because biological systems are far to complex to just understand with a cursory look. We need modern bioinformatics, imaging, and molecular biology techniques to begin understanding how natural systems work, and be able to manipulate things on a small enough scale to replicate them.

It's just now becoming possible. Engineers didn't look at biology before, because they didn't know anything about biology, and lacked tools to manipulate molecular systems. Bioengineering itself is a very new field, and a good portion of the academic bioengineering departments that exist now are less than 5 years old! Bioengineering now is in a similar situation as physics was in the 19th century.

I looked at your essay, and don't see that you have any evidence showing that WBE is infeasible, or will take longer to develop than de novo AI. I would argue there's no way to know how long either will take to develop, because we don't even know what the obstacles are really. WBE could be as simple as building a sufficiently large network with neuron models like the ones we have already, or we could be missing some important details that make it far more difficult than that. It's clear that you don't like WBE, and you have some interesting reasons why we might not want to use WBE.

It's just now becoming possible. Engineers didn't look at biology before, because they didn't know anything about biology, and lacked tools to manipulate molecular systems. Bioengineering itself is a very new field, and a good portion of the academic bioengineering departments that exist now are less than 5 years old! Bioengineering now is in a similar situation as physics was in the 19th century.

That seems as though it is basically my argument. Biomimetic approaches are challenging and lag behind engineering-based ones by many decades.

I looked at yo

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Slowing Moore's Law: Why You Might Want To and How You Would Do It

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Slowing Moore's Law: Why You Might Want To and How You Would Do It

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