WMI, Artificial Intelligence and Talking Back

One of the most necessary elements of artificial intelligence is the ability to tell others something about oneself, not only in an ad hoc sort of way, but in order to initiallize relationships the ability to convey somewhat what one is about is important.  In fact, this would be a good feature to have installed in normal intelligence.  It would be nice if when we came upon people we might know a little bit more about their capabilities than just what their outward appearance provides.  It would be nce to know, for example, that this man sleeping in the cardboard box is really a genius programmer with a 180 IQ, and he’d like to be back to worlk and in the flow of life, but he just has lost a lot of hope on how to get there.  It would also be nice to know that that bear in the distance is not only capable of mauling people, but he is mentally disposed to do so, and covers grounds at speeds that are phenomenal even for a bear.

Similarly, it would be nice to know more about all of the hardware inside of a computer or computerized system and to know what it is capable of on every level.  This is just as important as receiving the replies one receives during execution of a program that all is going well, or all is not going well, or that the procedure completed in 3 milliseconds.  Responses that occur during execution of code are generally referred to in a generic sense as callbacks.  These responses can be asynchronous.  That means that the software is providing information not expecting or requiring a reply.  The software may, or may not be waiting for a reply.  The replies can be part of a synchronous execution of code.  That means that the code is providing a round trip.  It is going out on a mission and returning with a resp0nse.

This can become a little complicated when one considers that it is possible to have 2 asynchronous connections that almost seem synchronous, or that it is possible to have synchronous and asynchronous connections working together.

All of this is important in the actual running of the code that brings computers and robots to life.  What I have just described, however,  does not directly address the initial imparting of information that helps to make all of this communication possible.  In order for software aimed at imitating intelligence in humans and animals to work it needs to know quite alot about the hardware.  A good model for starting us off in that direction is Windows Management Instrumentation.  WMI is a standard that hardware vendors can subscribe to and comply with by providing information built, or burned into the firmware of their devices.  This ‘information’ is  able to poll the device itself anbout the device’s own current state,  which will respond to commands of a predetermined format that imparts information about that device.  That derived information can be information like: size and number of CPU’s, type of memory, amount of memory, type of disks, number and drive assignment of disks.  The information can get very detailed.

Now I stated that the ‘information’ is able to poll the device.  Whenever you have a case where information can ask about information, you have a sort of artificial intelligence in play.  This makes this entire process, developed as a confluence of activities by the manufacturers of products and the software developers helping to provide the standard, a good, though imperfect model of what must happen for artificial intelligence development to occur geometrically.  Of course, the way that hardware developers provide for the physical aspects of how their devices will tell you something about their changeless characteristics, their capabilties and their current state is not limited.

Windows Management Instrumentation is a model well worth looking at and I will talk more about it.

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How Deep does Artificial Intelligence Have to Go?

I remember when a friend repaired our family van and painted the repaired area he explained to me about the ‘depth’ of the painted surface.  If you could hold a ruler up to the side of the car and read the ruler in the reflection, the number of inches that you could read indicated the depth of the painted area.  Of course, the greater the depth, the better the paint job was.

If you can visualize a large mirror, you can realize that a good mirror has considerable depth, perhaps only measurable in many feet or meters.  Artificial Intelligence is like that.  There’s the human language level, where the language is parsed and given some meaning ‘on a computer level’, there’s the machine-level languages and the algorithms that drive them and allow them to take advantage of processing power, and then there’s the machines themselves, which have to have a model that not only reflects the possibilities of what the software is capable of and wants to do, but reflects what the various clients are capable of or will be capable of and will be headed towards being capable of.

Those clients express themselves through various shapes and forms and interfaces, and none of those are negligible.  Some of them are robotic, some are, 2-dimensional interactive, some are three-D interactive, some are remote devices, some even have biological characteristics, and some haven’t quite taken shape yet.

There is a great depth to the many levels of this topic, not the least of which is the ethical issues that pervade and surround all that artificial intelligence can come to mean and be.

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