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"considering that 2016 is generally regarded as the date of the deep learning revolution" -- I thought it was 2012, when AlexNet took the imagenet crown?

sillysaurusx 4y ago
That's probably fair. But you'd be hard-pressed to find a DL stack to try out your ideas with prior to 2016, since that's when Tensorflow launched. :) (Gosh, it's been less than a decade. Time sometimes doesn't fly, considering how much it's changed the world since then...)
- abrichr 4y ago
  Theano was first released in 2007.
  - sillysaurusx 4y ago
    That’s actually fascinating. Were there many experiments done in it back in the 00’s? I’m just trying to imagine the things you could do with it back then. 2007 had relatively fast gpus for the time, but certainly nothing compared to today. Yet it’d certainly be enough for MNIST training, which makes me wonder what else could be done.
    - ladberg 4y ago
      FWIW in 2016 I was at an ML team at Apple that had been shipping production neural networks on-device for a while already. At the everyone used an assortment of random tools (Theano, Torch, Caffe). I worked on an internal tool that originally started as a Theano fork but was closer to a modern-day Tensorflow XLA (and has since been axed in favor of Tensorflow for most teams).
    - abrichr 4y ago
      You can look at Yoshua Bengio's Google Scholar profile [1] and scroll down to see what they were working on around that time. Here are some papers with many citations: - An empirical evaluation of deep architectures on problems with many factors of variation [2] - Extracting and composing robust features with denoising autoencoders [3] - Scaling learning algorithms towards AI [4] [1] https://scholar.google.com/citations?hl=en&user=kukA0LcAAAAJ&view_op=list_works&sortby=pubdate https://scholar.google.com/citations?hl=en&user=kukA0LcAAAAJ... [2] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:5nxA0vEk-isC https://scholar.google.com/citations?view_op=view_citation&h... [3] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:3fE2CSJIrl8C https://scholar.google.com/citations?view_op=view_citation&h... [4] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:roLk4NBRz8UC https://scholar.google.com/citations?view_op=view_citation&h...
  - jebarker 4y ago
    Yep, I worked on a production DL system based on Theano in ~2014

sillysaurusx 4y ago

That's probably fair. But you'd be hard-pressed to find a DL stack to try out your ideas with prior to 2016, since that's when Tensorflow launched. :) (Gosh, it's been less than a decade. Time sometimes doesn't fly, considering how much it's changed the world since then...)

abrichr 4y ago
Theano was first released in 2007.
- sillysaurusx 4y ago
  That’s actually fascinating. Were there many experiments done in it back in the 00’s? I’m just trying to imagine the things you could do with it back then. 2007 had relatively fast gpus for the time, but certainly nothing compared to today. Yet it’d certainly be enough for MNIST training, which makes me wonder what else could be done.
  - ladberg 4y ago
    FWIW in 2016 I was at an ML team at Apple that had been shipping production neural networks on-device for a while already. At the everyone used an assortment of random tools (Theano, Torch, Caffe). I worked on an internal tool that originally started as a Theano fork but was closer to a modern-day Tensorflow XLA (and has since been axed in favor of Tensorflow for most teams).
  - abrichr 4y ago
    You can look at Yoshua Bengio's Google Scholar profile [1] and scroll down to see what they were working on around that time. Here are some papers with many citations: - An empirical evaluation of deep architectures on problems with many factors of variation [2] - Extracting and composing robust features with denoising autoencoders [3] - Scaling learning algorithms towards AI [4] [1] https://scholar.google.com/citations?hl=en&user=kukA0LcAAAAJ&view_op=list_works&sortby=pubdate https://scholar.google.com/citations?hl=en&user=kukA0LcAAAAJ... [2] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:5nxA0vEk-isC https://scholar.google.com/citations?view_op=view_citation&h... [3] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:3fE2CSJIrl8C https://scholar.google.com/citations?view_op=view_citation&h... [4] https://scholar.google.com/citations?view_op=view_citation&hl=en&user=kukA0LcAAAAJ&cstart=800&pagesize=100&sortby=pubdate&citation_for_view=kukA0LcAAAAJ:roLk4NBRz8UC https://scholar.google.com/citations?view_op=view_citation&h...
- jebarker 4y ago
  Yep, I worked on a production DL system based on Theano in ~2014