03 March 2011

Playthings of the Gods

Technology Review

Leon Chua -- father of Amy Chua -- conceived the memristor in a paper back in 1971. The memristor is a resistor with a memory of an earlier state. It behaves differently, depending upon its history. Because inter-neuronal synapses typically also behave differently, depending upon their histories, the memristor is often seen as a building-block for creating more brain-like computers. Researchers are already simulating what a memristor-based computing system might look like:
Memristors are resistors that "remember" the state they were in, which changes according to the current passing through them. They are expected to revolutionise the design and capabilities of electronic circuits and may even make possible brain-like architectures in silicon, since neurons behave like memristors.

Today, we see one of the first revolutionary circuits thanks to Yuriy Pershin at the University of South Carolina and Massimiliano Di Ventra at the University of California, San Diego, two pioneers in this field. Their design is a memristor processor that solves mazes and it is remarkably simple.

...Pershin and Di Ventra begin by creating a kind of a universal maze in the form of a grid of memristors, in other words an array in which each node is connected to another by a memristor and a switch. This can be made to represent any regular maze by switching off certain connections within the array.

Solving this maze is then simple. Simply connect a voltage across the start and finish of the maze and wait. "The current flows only along those memristors that connect the entrance and exit points," say Pershin and Di Ventra. This changes the state of those memristors allowing them to be easily identified. The chain of these memristors is then the solution.

That's potentially much quicker than other maze solving strategies which effectively work in series. "The maze is solved in a massively parallel way, since all memristors in the network participate simultaneously in the calculation," they say. _TechnologyReview_via_NextBigFuture

One of the problems with asking a physicist, engineer, or computer scientist to devise a brain-like computer, is that persons trained strictly within these disciplines are not likely to know which elements of brain functioning should be "simplified" or "abstracted", and which elements should be closely copied.

The pursuit of artificial intelligence is rife with failed promises and predictions, over the past 60+ years. If we are not to go at least another 60 years without meaningful success, we will need researchers who are cross-trained in multiple disciplines relating to the problem.

The research described in the Technology Review article above was based upon the simulation of an array of memristors -- not on an actual memristor circuit. But even with real memristors, the circuit is simplistic in the extreme. The idea that one could assemble large numbers of simplified "synapses" into something that might behave like a biological brain -- in any meaningful way -- appears silly to anyone with even a basic understanding of how the brain works. And yet such silliness represents one of many parallel hopes for a so-far failed endeavour: artificial intelligence.

The synapse is not the basic unit of human intelligence or consciousness. The basic unit of human consciousness is something far less substantial and more ephemeral. It exists at multiple logical levels above the synaptic level. It is dependent upon the simultaneous function of trillions of synapses of distinctly multiple types, involving efferent, afferent, and re-entrant activity at multiple logical levels.

What the researchers describe in the Technology Review article is the simulation of a toy. Not the toy itself -- a simulation of the toy. The human brain is not a toy. Unless, of course, you are a god.

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Blogger Max said...

I dont think you quite understand the implication and the progress memristors bring to the field:

1) They are smaller than and more scalable than transistors up to a factor of 10^3. That by itself is huge

2) They can act as cells in neural network structures. Right now neural networks are done mostly in software.

3) They are computation and memory in one. Huge amount of energy and resources in computing is spent on moving data in and out of processors. Multi layer cashes, high speed bus and huge amounts of different kind of memory. Potential shift of paradigm in this area has enormous positive implications

p.s. And stop trying to belittle every single advancement as insignificant. and as about gods.... We have a saying "Not God but man makes pot and pan"

Thursday, 03 March, 2011  
Blogger al fin said...

Thanks for the comment, Max.

I do quite understand the implication and importance of memristors in the field of massively parallel computation and neural nets.

But that is quite a different thing than believing that memristors can be put together in large numbers (in any configuration) and be expected to behave like a brain.

Sophisticated computation is one thing. Building a machine intelligence is rather different.

That is the point being made, which too many believers in near-term human level AI find difficult to comprehend because they do not understand the only working and accessible example of an intelligent machine -- the human brain.

Thursday, 03 March, 2011  
Blogger Loren said...

They aren't quite like neurons. A neuron uses potentially dozens of chemicals as various transmitters, allowing a plethora of connections. A memristor only remembers the past resistance, which is how you store data with them. While an neural net could be built with them, it won't be nearly as nice as a proper organic brain.

Thursday, 03 March, 2011  

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