Remembering the Future

Value can be created by the exchange of goods that resolve a twist in the fabric of values. If I have something that you value more, and you have something that I value more, if we make an exchange, we unwind a twist in value space and bring the system back to equilibrium where we each have what we value most.

Efficiency is possible by cutting out the middleman in this exchange process. I can now post the things that I have that I no longer value on the internet, without the need for a middleman to buy from me at a price above my value of it, but below the price another buyer is willing to pay.

In the age of information, I can make a copy of what I have and give it away for almost nothing. Things which already exist therefore have almost no "commercial value". "Commercial value" must be created by creating something new. Creativity is possible by developing a model of what is possible, and navigating that model to discover new possibilities of increasing "personal value".

The development of navigational models for the creation and discovery of personal value still has commercial value not as a "thing" but as a process. Search, Navigation, Modeling, and "thing generation" should be part of one interactive process. There is commercial value in making that process more efficient. Each created thing should have its own modeled configuration, which is open to further search for value and transformation.

Topics: Value | Business | Model

Kingsley Uyi Idehen

By simply injecting "Context" which is what a high fidelity linked data mesh facilitates i.e. a mesh of weighted links endowed with specifically typed links (as opposed to a single ambiguous type unspecific link), you end up with an even more insight into the power of a Linked Data Web.

Topics: data2.0 | RDF

By George Dyson

Ed was reminded of cybernetician W. Ross Ashby's "Law of Requisite Variety": that any effective control system has to be as complex as the system it controls. This was the paradox of artificial intelligence: any system simple enough to be understandable will not be complicated enough to behave intelligently; and any system complicated enough to behave intelligently will not be simple enough to understand.

Topics: MachineLearning | Cybernetics