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The difference this time is we're already there. Sure, the only physical limit to computing I'm willing to give with current research is Bremmermann's limit [1]

The difference this time is we're already there. Sure, the only physical limit to computing I'm willing to give with current research is Bremmermann's limit [1], but it doesn't mean we'll ever reach it. Our brain is awesome with a merely few 10's of billions of elements. We sure can do better than what we have with cpus with a few billions of transistors -- the problem must be we don't have a clue of what to do with them. A hint to that is even the most powerful supercomputers with 100's of trillions of transistors still can't do better than our brain in some tasks. [1] http://en.wikipedia.org/wiki/Bremermann%27s_limit http://en.wikipedia.org/wiki/Bremermann%27s_limit

simple_logic 12y ago
A single transistor can't do the job of a neuron and 500 synapses.
- stcredzero 12y ago
  Synapses turned out to be more complicated than we thought. Single cell organisms did all of their sensing and data processing through their membranes. Guess what synapses evolved from?
- PeterisP 12y ago
  A couple transistors may be enough to do the job of a synapse - and it would do that "job" many orders of magnitude faster. A modern CPU has some 100000 times less transistors than we have synapses, but it's effective frequency is at at least 1000000 faster than synapse firing rates. So on "volume" ratio our CPUs are already more powerful than our brains, we just don't know how to wire those transistors properly. It may well be that the power of such a neural network is nonlinear to its size, and a tenfold smaller/tenfold faster network is much weaker. But we do already have supercomputers that have a similar number of transistors than our brains have synapses, while still having the millionfold speed advantage. Our limit is in our [lack of] ability to build brains. If we knew how, then our current silicon tech would be enough to run ubiquitous stronger-than-human AIs - but we don't; and "bruteforcing" a brain emulation without a better understanding is so inefficient that it requires currently unfeasible resources.

simple_logic 12y ago

A single transistor can't do the job of a neuron and 500 synapses.

stcredzero 12y ago
Synapses turned out to be more complicated than we thought. Single cell organisms did all of their sensing and data processing through their membranes. Guess what synapses evolved from?
PeterisP 12y ago
A couple transistors may be enough to do the job of a synapse - and it would do that "job" many orders of magnitude faster. A modern CPU has some 100000 times less transistors than we have synapses, but it's effective frequency is at at least 1000000 faster than synapse firing rates. So on "volume" ratio our CPUs are already more powerful than our brains, we just don't know how to wire those transistors properly. It may well be that the power of such a neural network is nonlinear to its size, and a tenfold smaller/tenfold faster network is much weaker. But we do already have supercomputers that have a similar number of transistors than our brains have synapses, while still having the millionfold speed advantage. Our limit is in our [lack of] ability to build brains. If we knew how, then our current silicon tech would be enough to run ubiquitous stronger-than-human AIs - but we don't; and "bruteforcing" a brain emulation without a better understanding is so inefficient that it requires currently unfeasible resources.