Bob McGinley::J2Evolution

The God Particle

The Higgs Boson is a theoretical elementary particle predicted to exist in the Standard Model of particle physics.  It is called the God particle because if it exists, it explains how elementary particles with no mass can be used to construct mass in matter.  Even though it has never been observed, it is predicted to exist, thus the God reference.

In the micro-electronics field, the "God particle" is the memristor.  The concept of the memristor is based on fundamental circuit variables much like the resistor, capacitor, and inductor.  The word "memristor" is short for "memory resistor". 

A memristor works like a resistor whose resistance level is determined by an amount of electrical charge that has passed through the memristor previously, and can maintain the resistance value when uncharged (power off).  The memristor is a resistor capable of remembering a previous charge, much like the way neural cells work in our brains.

HP researchers recently announced that they had created a nanoscale version of a memristor.  In "HP Discovers Potential "God Particle" the device is touted as a possible next step for creating androids and other types of synthetic intelligence. The thought being that memristors could potentially act as simulated neural cells.

First off, I'm nothing if not a skeptic.  I think the potential of the memristor is great.  I have always been a bit bewildered by our acceptance of a purely binary transistor processing short bit (32 & 64) pathways.  I've some great discussions with my technical colleagues about a 'trinary' transistor, capable of holding a positive, negative, or neutral charge.  And I've considered processors with 1024 or even 64k bit pathways, allowing us to process more information per CPU cycle.  But I'm not a particle physicist or an electrical engineer, so the discussions are usually more science fiction.

Lets consider the memristor as a synthetic neural cell for a second.  If you've ever done any development work on artificial neural nets you should have general understanding of the basic principle.  Neural nodes, or artificial cells, connect to other nodes.  Each connection has a value or a weight assigned to it.  In most neural network patterns these weights are values between 0 and 1.  When neural input is received, the nodes transmit their weight values to their connecting neural nodes.  The neural nodes add up the weights, and determine if the signal value, and its own weight will cause the node to fire, or send its own message through the neural net.

Between 0 and 1.  Transistors are binary.  They only compute zeros and ones, not values in between, so they don't serve very well as synthetic neurons.  And they only cycle 0's and 1's when they are powered, losing any stored values with loss of electrical charge.  With a memristor these constraints are removed.  Memristors can contain values (resistance level) between 0 and 1, and they can maintain that value even while not being charged.

So by all accounts it appears that the memristor has the potential to make for a great synthetic neuron.  The HP article goes on about facial recognition, intelligent robots, androids, etc. as articles like this are notorious for doing.  But lets add a touch of reality here.  Memristors are to the human brain what the wheel is to walking.  Memristors are inanimate and unevolved.  Our brains have already been subject to centuries of natural selection and genetic mutation.  The memristor will not magically fill this gap.  It may make for some great advances in storage capabilities though.

Off Topic: Bear Stearns bailout

Some very patriotic friends of mine recently went to New York to protest the $30 bn tax payer bailout of Bear Stearns.

These guys are heros in my book, so they get a shout out for standing up and being heard, even though this has nothing to do with AI or Comp Sci.

http://homepage.mac.com/scopix/iMovieTheater6.html

Check out FedUpUSA.org

Designing Intelligence

This topic is not to be confused with the creationist anti-theory of intelligent design. 

It might be because I'm more aware than most people on this subject, but I continue to hear more about the introduction of intelligent systems into business infrastructures and applications.  Simple straightforward data applications are no longer enough to feed the demands for metadata and analytics. 

I just got my copy of the latest The MIT Press Computer Science & Intelligent Systems catalog.  To me this is like the Sears catalogs I remember when I was a child.  The MIT press inventory is full of new tomes on programming, the internet, and the usual computer science periodicals.  But the content for intelligent robotics and complex adaptive intelligent systems is very impressive.  Here are some of the books on the way to my house.

 

Neural Feedback

I've been giving the concept of neural feedback a lot of thought lately, in fact I cant get it out of my head (a little neurology humor for you).  I have been contemplating several aspects about the flow of feedback, how our brains use it, and why it exists.  When thinking about it, it becomes hard to discern what is feedback and what is memory, or if in fact they are the same thing.

For example, I went to the dentist last week to have several old fillings replaced.  I hate going to the dentist.  I am an ardent anti-dentite.  But my dentist is actually a pretty caring guy, and does a great job of minimizing the stress and the pain.  That being said, the experiences and memories I have of having work done inside my mouth are vivid.

On Intelligence - A discussion

I recently had the pleasure of spending some vacation time with my very good friend Dr. Michael Nussdorfer.  Mike is the Medical Director for Radiology at Barton Memorial Hospital in South Lake Tahoe, California.  He is an expert on the anatomy of the human brain, diagnosing brain injuries, sleep disorders, and neurology in general.  He is also a technology buff like myself, who shares some of my interests in expanding our understanding of neural processes.

Mike and I typically measure the quality of our vacations by the number of books we read.  We often bring each other books we have recently read so we can discuss the ideas and predictions.  Fiction is rare, as we usually stick to science or history subjects.  For this trip I brought along Jeff Hawkins' On Intelligence to share and get his opinion on some of the ideas presented.  The discussion made me realize some of the underlying challenges in trying to mimic the neural processes of the human brain.

Intelligent Traffic Systems

Just checking in.  Haven't been writing much lately because of my current workload and some side projects that have been stealing my time.

IBM made their top 5 technology predictions for the next few years, and Intelligent Traffic Systems made the list.  Not because of my influence I assume, but because we see a market there as traffic and congestion become more of an influence on worker productivity.  Gotta get the workers to the plant on time.

My work on intelligent traffic systems these days has been limited to some patent development.  I haven't had much chance to work on my simulation code, although I have done some work on my neural net design and my intelligent blackjack playing agent.  Helps pass the time on long flights.

Oracle is sucking up BEA.  We at IBM saw this coming a while ago, and were not that surprised.  One less competitor to knock off.  We'll see if Oracle can survive the coming economic turn down.

Intel missed earnings and warned they are not likely to improve much in 08.  Take this into account with AMD's demise, and writing couldn't be more clear.  We are headed towards recession with a serious consumer and business spending slow down.  Margins on processors are only going to decrease.  Intel needs to find a new line of growth.

Java is becoming the new Cobol if you didn't know.  I always like these articles that claim one language is falling out of favor for another. 

Simply put, developers are saying that Java slows them down. “There were big promises that Java would solve incompatibility problems [across platforms]. But now there are different versions and different downloads, creating complications,” says Peter Thoneny, CEO of Twiki.net

News flash for you programming prognosticators, you have been saying that COBOL is a dead language for the last 20 years, and every bank in the country is still running it, and will be for the coming future.  COBOL isnt even the new COBOL.

Here is the deal with Java, its a complex language, and it was not designed for HTML generation applications.  Try writing a 2D graphics program with geometric equations and real-time event management with Ruby/Rails.  You cant.  Cant do it with PHP either.  So this is not an apples to apples comparison.

By the way, the most popular programming language in the world is C, I wonder when it becomes the new COBOL, if it hasnt already.