Nature inventing the wheel
There are so many new things to watch on the internet. Such as this spider that transforms itself into a wheel when it wants to escape its predator! Right click on the move to watch it on Youtube itself. But this post will not describe all kind of animals that seem to come close to the ideal of "back-and-forth" metamorphosis, of temporarily body changes. No it is about building brains.

Our crappy computer designs...
The future will be defined by our abilities to make living things (gene technology), fast things (information technology), small things (nano-technology) and smart things (artificial intelligence). This story is about a marriage between the last two. It all started with the Van Neumann computer architecture. Our computers are organized according to this design principle. Namely with a separate CPU, central processor unit, and memory. A famous problem is the so-called Van Neumann bottleneck. If those two parts, the processor and the memory is housed on two different places, there will be going a lot of data between them. This "gate" forms a bottleneck, potentially constraining bandwidth. However, this is not the biggest problem. You might think that processing data costs energy, and that is true. However, what also costs energy is powering wires. The longer the wires are, the more power they consume. And then our biggest problem is our own head... We just don't have the wiring (the proper mindset) to build computers the same we are wired ourselves. In our brains there is not a part where the processing takes place, and another part where we store everything. In contrary, it is distributed all over the place. And certainly, some places are more dedicated to memory, like the place cells in the hippocampus, but it is seldom so black and white. For that reason I would like to refer you to the following talk:

Recently at HP Labs Stan Williams and his team discovered a physical representation on nano-scale of the fourth circuit element described by Chua long ago. Besides the resistor, capacitor and inductor, there is the memristor. Apply current or voltage on a memristor and it will get a new resistance value, even if you detract the source! This is awesome to create instant-on computers, which is mentioned as on of the possible killer apps on the web. However, what also can be done is solving the above mentioned crappy computer design problem. To come up with a design that integrates remembering (memory) with thinking (processing). One of the ways our brain stores events is by increasing the strength of connections (synapses) between neurons. The neurons that fire together, wire together. You can see the brain as some kind of large statistical machine that extracts a lot of information just out of the fact that things happen at the same time, or consistently slightly after each other. That is, it can do it with "images", but not with lottery tickets.

In the movie Gregory Snider (I only watched the first part) explains how the brain can be emulated using memristors to model synapses. Like as cell processors, or even more with field programmable gate arrays [FPGAs], there will have to change a lot in conventional computer programming, will computer scientists make use of the inherent reconfigurability that is possible with this hardware. VHDL (a hardware description language) is not the best horse to bet on, to win the race of reconfigurable programming. Artificial neural networks, and we have indeed better and better ones (they are not the old fashioned feed forward net with back-propagation anymore) are inherently mixing memory with processing.

The Killer App
Our robots need large-scale pattern recognition. We cannot afford to do without artificial neural networks anymore. The networks might be used in an abstract form, say as a liquid state machines or adaptive resonance theory model, but we nevertheless have them on our robots! And, in the end we will need to have hardware that can run those networks that are so like our own minds. And this is the promise of memristor-computers. Robots need memristors. And it is also the other way around. Memristors need robots. It might turn out to be virtually impossible to program "memristor-computers" without a "biological" mindset!