(Part A)
In early machine learning days, researchers coded programs with specific rules to respond to as many scenarios as the researchers themselves could imagine.
However, when unforeseen scenarios came along, their programs quickly broke/failed.
(Part B)
Modern machine learning now learns rules automatically, and fail far less, achieving human level performance on narrow cognitive tasks. However, there are still problems with modern machine learning, and separately, researchers are still manually designing the basis nodes/connections (artificial neurons/synapses) involved in these modern automatic rule learning models.
(Part C)
So, I then investigate whether it is feasible to automate even more, by utilizing stem cell data to "grow" those basis nodes/connections, instead of manually designing them.
(Part D)
What follows is a rough exploration of stem cell proliferation, determination & differentiation as an approach to‘grow’ some degree of software artificial general intelligence.
See my paper here: stem-cell-agi-exploration_research-gate
Or here:stem-cell-agi-exploration_academia
Criticism regarding the topic is welcome. Help me to scrutinize this idea fully. (and or build on the idea if possible)
via International Skeptics Forum http://ift.tt/2oXJEcG
Aucun commentaire:
Enregistrer un commentaire