Fluid Mechanics

John Searle's Chinese Room argument has been criticised as an "absurd thought experiment that panders to false intuitions, and has done nothing but sidetrack philosophers for decades".

He asserted that computers may very well be able to emulate human thought in such a way that people will not be able to distinguish the two; but they will never be anything more than a counterfeit in this respect as it is beyond the talents of a human creator to invest a machine with semantic intelligence.

Over the last couple of days, the blogosphere has been buzzing with tales of 'wet computing', whereby researchers will aim to develop "information processing technology inspired by chemical processes in living systems".

On the face of it, this is really exciting news. It conjures up images of complex fluid neorological interplay and massive machine speed and efficiency working in perfect harmony.

Dr Maurits de Planque, a biochemist and spokesman for the project had said "Our system will copy some key features of neuronal pathways in the brain and will be capable of excitation, self-repair and self-assembly."

So far a very tantalising proposition. But it still doesn't give us any scope to belive that machine intelligence will transcend the Chinese Room... yet. In fact it seems to echo some of the oldest science fiction, namely Frankenstein, where a human's attempts to create life end up flawed... producing only a sum of many parts, composite as opposed to complete.

There may of course be problems associated with trying to build a new and improved model when the spec is based on an imperfect and very breakable, albeit wonderfully elaborate, source design.

It's likely that we will see this story repeat itself in different forms over the next years as we enter the age of replication, where syntax doggedly gains on semantics but does not yet have the capacity to make the next leap forward. There may indeed be many convincing replications in the near future and you may find yourself quick to declare that we are at the tipping point. Given our present position though, it might be wiser to accept this stage as intemediary... but very possibly antecedent to the escape from the Chinese Room.

Machine Learning with Quantum Algorithms

Posted by Hartmut Neven on Google Research Blog:

Many Google services we offer depend on sophisticated artificial intelligence technologies such as machine learning or pattern recognition. If one takes a closer look at such capabilities one realizes that they often require the solution of what mathematicians call hard combinatorial optimization problems. It turns out that solving the hardest of such problems requires server farms so large that they can never be built.

A new type of machine, a so-called quantum computer, can help here. Quantum computers take advantage of the laws of quantum physics to provide new computational capabilities. While quantum mechanics has been foundational to the theories of physics for about a hundred years the picture of reality it paints remains enigmatic. This is largely because at the scale of our every day experience quantum effects are vanishingly small and can usually not be observed directly. Consequently, quantum computers astonish us with their abilities. Let’s take unstructured search as an example. Assume I hide a ball in a cabinet with a million drawers. How many drawers do you have to open to find the ball? Sometimes you may get lucky and find the ball in the first few drawers but at other times you have to inspect almost all of them. So on average it will take you 500,000 peeks to find the ball. Now a quantum computer can perform such a search looking only into 1000 drawers.

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The Future of The Supercomputers

In mid-November Jaguar, located at the US Department of Energy’s Oak Ridge Leadership Computing Facility, was named as the world's fastest supercomputer. Recording a performance speed of 1.8 petaflops (One petaflop refers to one quadrillion calculations per second), it took the title away from former champion Roadrunner, at Los Alamos.

In under two years from now, we can expect the Blue Waters system to be be fully operational which, according to the NCSA, will mean:

... breakthroughs in nearly all fields of science using Blue Waters. They will predict the behavior of complex biological systems, understand how the cosmos evolved after the Big Bang, design new materials at the atomic level, predict the behavior of hurricanes and tornadoes, and simulate complex engineered systems like the power distribution system and airplanes and automobiles.

And predictions for the future currently look something like this (from Wikipedia):

Given the current speed of progress, supercomputers are projected to reach 1 exaflops (one quintillion FLOPS) in 2019. Futurist Ray Kurzweil expects supercomputers capable of human brain neural simulations, for which according to Kurzweil 10 exaflops would be required, in 2025.

Erik P. DeBenedictis of Sandia National Laboratories theorizes that a zettaflops (one sextillion FLOPS) computer is required to accomplish full weather modeling, which could cover a two week time span accurately. Such systems might be built around 2030.

Super-fast Quantum Computer Gets Ever Closer

Click here for Science Daily's article on recent breakthroughs in quantum computing