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.