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The Google Brain Team – Looking Back on 2017

research.googleblog.com

1–7 of 7 posts

Re: The Google Brain Team – Looking Back on 2017

#2
The most promising area here to me seem like automl. The promise of the new machine learning was that we get to move away from tedious feature engineering and everything will work and be simple. It may have become simpler but training/debugging new DL models is still painful causing the focus to move to extensive hyperparameter search. automl may become the next step in abstraction, where we design single models/algorithms that are able to build viable networks for many tasks/purposes.

Re: The Google Brain Team – Looking Back on 2017

#6
post #2

The most promising area here to me seem like automl. The promise of the new machine learning was that we get to move away from tedious feature engineering and everything will work and be simple. It may have become simpler but training/debugging new DL models is still painful causing the focus to move to extensive hyperparameter search. automl may become the next step in abstraction, where we design single models/algo…

I'm really excited by AutoML as well, it seems like one of the few next level advancements. One of the authors of AutoML is presenting in SF in Feb at the decentralized ai summit can't wait.