Dreams, Drugs and ConvNets

Dreams, Drugs and ConvNets

Artefacts of human and artificial cognition.
at Studenckie Koło Naukowe Neurobiologii, the University of Warsaw


Piotr Migdał

March 02, 2017


  1. 1.

    Dreams, Drugs & ConvNets Piotr Migdał, PhD deepsense.io / freelancer

    http://p.migdal.pl/ 2 Mar 2017, Studenckie Koło Naukowe Neurobiologii UW
  2. 2.
  3. 3.
  4. 4.

    Deep Learning progress • image recognition, neural style, word analogies,

    per-char translations, playing ATARI games, Go, [no idea what’s next] • fast-paced (more than my quantum physics PhD):
 6 month ago a breakthrough, now a baseline • (no questions about Singularity please!)
  5. 5.

    Artificial neural networks • Multidimensional arrays • Simple matrix operations

    (add, multiply) • Floats (not spikes) • Simple activation functions (sigmoid, ReLU) • Cost function and back-propagation • A lot of weights (e.g. 100M)
  6. 9.

    Big questions • creating general AI or sentient beings •

    transferring our minds (mind uploading) “I mean, if we're able to save even just a small piece of ourselves, why wouldn't we do that?” - SOMA https://www.youtube.com/watch?v=BZTfi1jv-EE
  7. 10.

    Flesh vs machines:
 practical questions • Cross-inspiration: • Machine Learning

    to Human Cognition • Human Cognition to Machine Learning • Common abstractions • Learning in general • Hierarchical signal processing
  8. 13.

    The biggest lie of every
 parent, pet owner
 and neural

    network trainer: “I’ve never shown it that, it must have learned it by itself!”
  9. 18.

    • What should I use:

    good GPU! http://alexgrey.com/shop/st-al.html
  10. 30.

    Learning what is important • Object consistency • Toddler needs

    to learn, so do ConvNets http://blogs.scientificamerican.com/illusion-chasers/what-little-babies-see-that-you-no-longer-can/
  11. 36.

    Questions? • If you want to learn: • http://lumiverse.io/series/neural-networks-demystified •

    https://gist.github.com/stared/7de2908b9bcba01c39ee3c591875a23c • http://www.deeplearningbook.org/ • Keras (on top of TensorFlow) in Jupyter Notebook • https://medium.com/@mateuszsieniawski/keras-with-gpu-on-amazon-ec2-a-step-by- step-instruction-4f90364e49ac#.4i1norivh • https://www.erowid.org/ http://p.migdal.pl/ + I do like emails: pmigdal@gmail.com