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On limits of deep learning and where to go next with AI.

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Posted May 4, 2016 by Filip Piekniewski

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Basic info

I’m proposing a new machine learning meta-architecture for learning forward models. The architecture is called Predictive Vision Model (PVM). In this blog I present my thoughts on how PVM relates to deep learning and the global AI landscape. Occasionally I’ll blog about my sysadmin projects and sci-fi.

See a short bio note here.

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Recent Posts

  • A brief story of Silicon Valley's affair with AI
  • Autonomous vehicle safety myths and facts, 2019 update
  • Fooled by data
  • Elon and the collective
  • AI winter - update
  • Deep learning - the "why" question.
  • Mathematical foundations of neuroscience
  • Some fun numbers about the human brain
  • 2017 PVM talk at UC Merced
  • Autopsy of a deep learning paper
  • Rebooting AI - postulates
  • AI winter - Addendum
  • AI winter is well on its way
  • Are black holes really so black?
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  • The paradox of reproducibility in statistical research
  • Problems with measuring performance in Machine Learning
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  • PVM on the GPU (dev update)
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  • Recurrent dreams and filling in
  • Learning physics is the way to go
  • More thoughts on the self driving car
  • Yann LeCun lecture at CMU, 11.2016, a few comments
  • Myths and facts about AI
  • AI and the ludic fallacy
  • Predictive Vision in a nutshell
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  • The Elephant in the Chinese room
  • The peculiar perception of the problem of perception
  • Adversarial red flag
  • Just how close are we to solving vision?
  • Intelligence is real
  • When you are 80% there means you are not there
  • PVM is out

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