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[D] Machine Learning & Robotics: My (biased) 2019 State of the Field

At the end of every year, I like to take a look back at the different trends or papers that inspired me the most. As a researcher in the field, I find it can be quite productive to take a deeper look at where I think the research community has made surprising progress or to identify areas where, perhaps unexpectedly, we did not advance. I’ve put together a post in which I give my perspective on the state of the field from this past year. The post is no doubt a biased sample of what I think is progress, but I hope it stimulates discussion about which subfields evolved or what priorities unexpectedly shifted in 2019.

Link to post:

A short summary/outline of my post for discussion:

  • From AlphaZero to MuZero MuZero picks up where AlphaZero left off a couple years ago and makes significant advances using a learned model to enable rollouts without planning in pixel space.
  • Representation Learning I’m particularly excited to see how recent progress in representation learning (like advances in “entity abstraction”) will help to blur the lines between black-box deep learning and old-school symbolic AI & classical planning.
  • Supervised Computer Vision Research Cools (slightly) Research in this space has slowed, but related techniques, like network pruning and network compilation, have taken off this past year.
  • Maturing Technologies
    • Graph Neural Networks
    • Explainable & Interpretable AI
    • Simulation Tools & Sim-to-Real
  • Bittersweet Lessons No discussion of 2019 would be complete without a conversation about Rich Sutton’s “The Bitter Lesson” post and rebuttals.

What do you think were the most interesting advancements or shifts this year?

submitted by /u/gregoryjstein
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.