Lessons from Optics, The Other Deep Learning – arg min blog


33 bookmarks. First posted by Vaguery january 2018.


Trying to frame our discussions of deep learning science, when we are still pre-newtonian in a lot of it...
deep  machine  learning  abstraction  mental  model  design  science  epistemology 
7 weeks ago by asteroza
How deep learning could to be more like optics
physics  deep-learning  science 
february 2018 by pmigdal
Favorite tweet: deliprao

I love this analogy of #DeepLearning to optics by @alirahimi0. There is a lot we don't understand. That's okay and not okay. Differentiable programming enabled by hardware advances is here to stay. Let's continue to make sense of it! https://t.co/kRmH0Ntc7f pic.twitter.com/ZJxZ3IPsrO

— Delip Rao (@deliprao) February 12, 2018

http://twitter.com/deliprao/status/963155300927750144
IFTTT  twitter  favorite 
february 2018 by tswaterman
An excellent post describing how I have been feeling about DL methods:
ATM it's hard to mov…
from twitter_favs
february 2018 by kartik
Lessons from Optics, The Other Deep Learning
from twitter_favs
february 2018 by danbri
Imagine you’re an engineer, you’re given this net, and you’re asked to make it work better on a dataset. You might presume each of these layers is there for a reason. But as a field, we don’t yet have a common language to express these reasons. The way we teach deep learning is very different from the way we teach other technical disciplines.

A few years ago, I got into optics. In optics, you also build stacks of components that process inputs. Here’s a camera lens.
machine-learning  philosophy-of-engineering  system-of-professions  pedagogy  knowing-what-you-know  epistemology  engineering-criticism 
january 2018 by Vaguery