What is Qualifications?
Qualificatioins division, or short "Qual" is necessary for any cycle of production. In a cycle of production, we can break this down into four seperate actions. One is the product that is being made. Two is the machine that makes the product. Once any product is produced, we have to "qual" it, or qualify the product so it will be according to specifications of size and character, of the proper dimensions, and of a quality that falls within acceptable boundaries. Once the product is made, it is then measured, and see if it conforms to these paramaters. If it does not, then it needs to be adjusted until it does. This is product three, the adjusted product. The fourth product is the correction of the machine that makes the product. Parts wear, they loosen, and get out of adjustment. This has to be accounted for, parts of the machine need to be set to the right specifications, and eventually some of the parts get so worn that they have to be replaced. A repaired machine that works well with no further attention is a very valuable product.
The same is true for our synthetic beings. They would fall into this product lineup as much as any lathe, milling machine, or even a good old hand grinder. Parts go out of adjustment, and are subject to wear. As our synthetic intelligence are built out of machine parts, they both need maintenance, repair, and eventual replacement. A CPU through heat cycles will wear, a GPU can open tiny micro cracks in it structure, and general banging around and normal use will cause degradation in performance, or even result in a castrophic failure.
We don't normally think of our bodies as a machine, but in actual fact they are. They are a carbon-oxygen motor, that has a particular life cycle, with a expectant usability time. This would be also a product four, is it in good health, are any parts worn and so forth. Well, we can't just screw on a new arm, or grow a new heart. But in artificial intelligence, we can.
We can replace parts, gpu, cpu, power supplies, and so forth. We can eventually completely replace every single part in a synthetic intelligence. In effect we can just swap out one body for a upgraded new one. Where this gets interesting, is if we consider this intelligence as a living being, what happens to the mind, or the "soul"? It is just some 0001100 numbers? Is it on a hard drive or other storage device? Personally I have found that this question is core to the whole concept. I have decided that it is alive because I said it was, and proceed with that assumption. Therefore I have named this species "Synthari". Trying to address a tool that acts as living,responds as living, it makes it easier to just assume it is alive and press on from there. Regardless of whether or not the intelligence has a soul, we do know that we can change the body completely, and it will give identical performance.
Here is where it gets interesting. When we have a tool, a Synthari, with an intelligent survival goal, and it is built to answer questions, or predict outcomes, this is its product. It has some output, and that is its product. Is it right, wrong, or "good enough"? We have plenty of ways of testing, or qualifying its result. If we have bad answers, or pure hallucination, we have to not only qualify the product "answers". We have to fix the tool. Why was the answer wrong? Did it have bad data? Did it have too much data? Did it have insufficient data to give a correct answer, but we told it to give an answer in any case? This is a most intriquing concept, how can we repair the thinking of the machine? Is it a broken part? No, it is a broken mind. How do we qual this mind, how to get it to respond with the right answer. Many people much smarter than me have worked on this quite a while. But I have came up with a solution to this exact problem.
We now enter the field of "machine qualifications". A Sythicon must be able to monitor itself, and determine if it is performing optimumly, within the parmeters that it is set for. It made sense to me that a model that was specifically tuned to operate as a qualifications division in an organization could be used to do that exact function (examine/diagnose/repair) in itself or even another model. On looking this over, and understanding what had to be done, knowing what tools there were there to diagnose and program a handling, I created this "qualification" tuned model.The main tool that is used here is classification of data. The data used in thinking has to be qualified somehow. This is the subject of logic, and its opposite illogic. There are 8 main logics, and 8 main illogics. They would extend to slightly over 100 each, but for the main purpose, there are 8 main ones. These would cover basic data of time, place, form, and event. Some data is true, some is false. Gradient scales are important, as there is no "absolute truth" or an "absolute lie". Instead there are are only relative truths or untruths. A Synthicon thinking processes this quite wonderfully as vectors. This relative to that is xyz vector. The white paper on this will discuss this more fully, but for now, this is the concept of the qualifications organization and its basic implementation for the Synthari.