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 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 don’t think WBE is infeasible—but I do think there’s evidence that it will take longer. We already have pretty sophisticated engineered machine intelligence—while we can’t yet create a WBE of a flatworm. Engineered machine intelligence is widely used in industry; WBE does nothing and doesn’t work. Engineered machine intelligence is in the lead, and it is much better funded.
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.
Polls of “expert” opinions on when we will develop a technology are not predictors when we will actually develop them. Their opinions could all be skewed in the same direction by missing the same piece of vital information.
For example, they could all be unaware of a particular hurdle that will be difficult to solve, or of an upcoming discovery that makes it possible to bypass problems they assumed to be difficult.
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.
That seems as though it is basically my argument. Biomimetic approaches are challenging and lag behind engineering-based ones by many decades.
I don’t think WBE is infeasible—but I do think there’s evidence that it will take longer. We already have pretty sophisticated engineered machine intelligence—while we can’t yet create a WBE of a flatworm. Engineered machine intelligence is widely used in industry; WBE does nothing and doesn’t work. Engineered machine intelligence is in the lead, and it is much better funded.
If one is simpler than the other, absolute timescales matter little—but IMO, we do have some idea about timescales.
Polls of “expert” opinions on when we will develop a technology are not predictors when we will actually develop them. Their opinions could all be skewed in the same direction by missing the same piece of vital information.
For example, they could all be unaware of a particular hurdle that will be difficult to solve, or of an upcoming discovery that makes it possible to bypass problems they assumed to be difficult.