Developmental Approach to Machine Learning? - article by L.Smith and L.Slone - Agreed

Yes, agreed. A good read, suggesting developmental machine learning, spatio-temporally continuous input data etc.:

See the concept of “shape bias" from Developmental psychology. That's related to  discussions in the "AGI Digest" on recognition of "buildings, chairs, caricatures" ... and other articles from this research blog, regarding 3D-reconstruction at varying resolution/detail as one of the crucial operations in vision published in this blog and the general developmental direction which is driven from one of the very fist articles here about the "Educational test".

HYPOTHESIS AND THEORY ARTICLE

Front. Psychol., 05 December 2017 | https://doi.org/10.3389/fpsyg.2017.02124

A Developmental Approach to Machine Learning?

Linda B. Smith* and Lauren K. Slone

• Department of Psychological and Brain Sciences, Indiana University Bloomington, Bloomington, IN, United States

• 
  
• See also:

• Sunday, December 31, 2017

  CapsNet, capsules, vision as 3D-reconstruction and re-rendering and mainstream approval of ideas and insights of Boris Kazachenko and Todor Arnaudov

  An excerpt from an email from AGI list digest:
  
  

  Todor, 27.4.2012:
  
  "Invariants" in human fully functional vision are just those 3D-models (or their components, "voxels:) built in a normalized space, ...
  
  Every 3D-model has a normalized position per its basis, and also some characteristic division of major planes and position between the major planes, and there are "intuitive" ways to set the basis --> gravity/the ground plane foundations, which is generalized to "bottom", i.e.: ...
  
  

  As in other occasion - theoretically that seems pretty obvious to me , though.
  
  The way of constructing them robustly and "generally" are the problems to be solved.
  
  

  Wednesday, November 14, 2007

  Faults in Turing Test and Lovelace Test. Introduction of Educational Test