François Chollet on Twitter: "AutoML may soon find itself with the same issue as reinforcement learning: people associating the entire problem domain (very broad and very important) with an extremely specific class of (flawed) methods for approaching it."

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1. Gharib Gharibi‏ @gharib_gharibi 23 Jul 2018
  Replying to @fchollet
  
  It needs to start somewhere!
  
  2 likes
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1. Eoghan Flanagan‏ @KateandPie 23 Jul 2018
  Replying to @fchollet
  
  From the applied side of the industry I can tell you we are still in the "Let's put AutoML in every presentation title" phase
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1. elvis‏ @omarsar0 23 Jul 2018
  Replying to @fchollet
  
  Any potential solutions to solve this problem?
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1. Jiliac‏ @Jilyac 23 Jul 2018
  Replying to @fchollet
  
  Q-learning is flawed? But yeah, it's sad people close themselves possibilities by over-approximating a field.
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1. Reed‏ @ReedRoof 23 Jul 2018
  Replying to @fchollet
  
  I feel so fucking sad
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1. Erin LeDell‏ @ledell 23 Jul 2018
  Replying to @fchollet
  
  We can thank @Google marketing for that. http://www.fast.ai/2018/07/23/auto-ml-3/ …pic.twitter.com/dLwJWST4ig
  
  2 retweets 17 likes
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1. Andrei Khobnia‏ @AI_Kho_ 23 Jul 2018
  Replying to @fchollet
  
  Who really tried AutoML should understand that it is just a method to search NN architecture hyperparameters. There are other methods (this is mentioned in original AutoML paper, btw).
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