The main goal of artificial intelligence (AI) is to translate human knowledge into equations.
The problem that arise and still holds is that it can't be solved on a human time scale with current technology.
The problem must be reduced to a problem that can be solved under time constraints pratical for mortals.
Machine learning produce projections of human knowledge over a smaller number of dimensions to make the computation pratical and sometime infer knowledge about how the results was done.
Instead of trying to put order in the mix, my idea is to increase the entropy of knowledge graph using grounded topologies.
Building such structure can be done though personnal note taking applications, croudsource applications and puzzle games.
Not only we leverage Human knowledge and computation skills but append to the already mastered ways of the intelligencewith improved logical and fuzzy reasoning but also push further the use of pattern matching cognition skills that the brain already has.
The opportunities to create cogni-games are manyfolds. People with disabilities can be offered new ways to interact with the world in a meaningful and enjoyable way.
cogni-art and cogni-game are really what should.be+is all about anthroposcene.
Anthropo[morphically_s]c[r]e[e]ne[d] Anthropoc[Sh]e[e]ne[d] AnthroP[r]o[bos]c[is]ene -- AnthropO[bs]cene --
Anthropo[S]ceney||AnthropO[bs]cene by Mez Breeze