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You may be thinking of this: https://www.technologyreview.com/s/544376/this-ai-algorithm-learns-simple-tasks-as-fast-as-we-do/ https://www.technologyreview.com/

• nl 11y ago
  The paper is here: http://cims.nyu.edu/~brenden/LakeEtAl2015Science.pdf http://cims.nyu.edu/~brenden/LakeEtAl2015Science.pdf This isn't deep learning (or a neural network at all). However, it is an extremely interesting approach. Most of the previous "low data" deep learning approaches I've seen are broadly based around the approaches seen in "Zero-Shot Learning Through Cross-Modal Transfer"[1] That's not really low data in the sense that it needs lots of data for initial training, but then is able to learn new things with very few examples. [1] http://papers.nips.cc/paper/5027-zero-shot-learning-through-cross-modal-transfer http://papers.nips.cc/paper/5027-zero-shot-learning-through-...
  • sgt101 11y ago
    You might also be interested in things like the Anglican language from Oxford. http://www.robots.ox.ac.uk/~fwood/anglican/ http://www.robots.ox.ac.uk/~fwood/anglican/
    • nl 11y ago
      Yes indeed. Church[1] too. The thing is - I've never seen anything quite as compelling as the Science paper from the probabilistic programming community. [1] https://probmods.org/ https://probmods.org/
    • stan_rogers 11y ago
      We do not presume to come to this Thine output trusting in our own correctness, but in Thy manifold and great Processors. Print, we beseech Thee, the content of Thy variable X, according to Thy promises made unto mankind through Thy servant Alan, in whose name we ask. Amen.