(Click to Enlarge)
The diagram above shows the relationship between Little AI, Big Ai, and Collective Intelligence.
Micro- or Macro-processing includes memory and recollection, knowledge creation/learning (delivered or extracted from social knowledge base), knowledge compilation and integration, etc.
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Social media and ‘Web 2.0′ brings an interaction capability to the web. It is exemplified by applications such as MySpace, Facebook, and Ning. The vast majority of Web 2.0 applications today simply serve to connect or network people in their communications. These create a global shared space where people can create interest groups and become aware of one another’s interests. One way to think of Web 2.0 is as creating or organizing the ‘interest space.’
Now then, human interests can be trivial, entertaining, serve some purpose, etc., or can be some mixture of these things.
Energy (to begin)
Intention
Intelligence collection
This diagram shows the evolution of knowledge working. It unveils the errors in a strictly behavioral view of knowledge, and unveils what the singularity really is, the advent of artificial knowledge creation.
I was asked a question to this post: http://hyperadvance.com/blog/?p=129 and the answer was getting too long for comments, so I’m addressing it as a new post. Here is the full question:
Say with with use of ‘knowledge creation questions’ we create new knowledge. How does one know the usefulness of knowledge created? The usefulness of a question is about the informations/knowledge it discerns. If you mechanize this, how do you ensure that the questions are good enough to glean useful knowledge?
There are three basic categories of knowledge, 1) Science, which draws data from reality and makes conclusions about it, 2) Technology, which builds knowledge from knowledge (techno-logic) largely to support industry or making things, and 3) Spiritual knowledge, which I use as a broad category for knowledge not tied to this reality or dimension.
In the sense of science, data is gathered from reality and that data is logically assembeled with regard to the aspects of reality being investigated. Usefulness here is defined in terms of the direction of sensing or in terms of what reality is being investigated. For example, imagine that a probe was sent to another planet. The planet itself is a scientific target, or something we want to know about. A probe is simply a mechanical sensor (that can extend the 5 human senses). If that probe gathered data about that planet, and conclusions were mechanically generated from that data, then we have new knowledge about that planet, which was our scientific target or the aspect of reality we wanted to know more about.
Technology is distinct from science in purpose and knowledge usefulness. The intent of technology is to generate knowledge for industry (for profit or not for profit) and industry makes things. Knowledge here then must be based on a purpose for the thing made. Performance is what is used to make things and performance is executed against set objectives. Things can be made without setting objectives (e.g., art), but the usefulness of making things is in the objective set. A theoretical knowledge machine could encompass both objective setting and knowledge creation to reach that objective. And it could also theoretically use, e.g., robotics or molecular manufacturing to make the thing. In this way, performance and technology are inseparable. The one is not useful without the other.
It is also important to note that scientific knowledge may be a catalyst for technological advance. For example, science may discover a wormhole, but technology may be needed to travel through it.
Spiritual knowledge might seem like an entirely different proposition, but as we learn more and more about quantum physics the lines between spritual knowledge and scientific/technological knowledge are becomming much thinner. This gets into things like the validity of our own perception of reality. Or whether or not we have accurately defined what reality fundamentally is. Suffice it to say in this post that all three of these knowledge types may ultimately converge in a very powerful way.
I’ll be in Cleveland on Thursday, July 9, for a Mid-Town Brews discussion. You can join the virtual Live Show and Chat 6PM – 7PM EST here: http://www.livestream.com/midtownbrews?referrer=mogulus
We will be talking about futuring, the knowledge/question cycle, and the future of enterprise.If you would like to attend live, see the Mid-Town Brews site for details: http://www.midtownbrews.net/
Robots collaborating to overcome their environment.
People inherently think of a question as something to be asked. It is hard to even conceptualize that it needs to be defined. What is the defnition of the question?
Questions are a realized lack of knowledge structure. Knowledge is logical structure. Any time there is a realization of a lack of logic a question is formed.
Questions are at the cutting edge of things we know. There are two kinds of questions, 1) Learning Questions and 2) Knowledge Creation Questions.
Learning questions are asked about knowledge that exists. Knowledge creation questions are asked about knowledge that does not yet exist.
As such, questions are either the door to learning or the door to new knowledge and social advance.
As a door to social advance, the question is behind all human achievement, past, present, and future. By mechanizing knowledge creation questions, human achievement will explode.