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What about machine translation, speech recognition and transcription, speech synthesis, image classification, segmentation and other computer vision tasks, faci

What about machine translation, speech recognition and transcription, speech synthesis, image classification, segmentation and other computer vision tasks, facial recognition, image and audio denoising, beating world champions at Go along with chess engines, language models for text generation, image editing (e.g. FaceApp)... You don’t have to fall for the hype and think deep learning will lead us to AGI in the next 5 years, but dismissing it as generative art and flashy papers isn’t any more accurate.

otabdeveloper4 5y ago
Did you read my post? None of that drives business decisions. As for Alexa, et al - these things fall into the "generative art" bucket. The search results they give aren't any better than the Eliza-tier expert systems of yore. They just feel much better and more human when you use them. (Which is also important, but doesn't drive business decisions, except as part of a marketing strategy.)
- joefourier 5y ago
  What do you mean by doesn’t drive business decisions? ~65 million Alexas were sold last year, and the product would be fairly useless without very high performance speech recognition powered by deep learning. I personally own a startup that uses deep neural networks as part of its core product functionality and our business decisions would be drastically different if it weren’t for modern machine learning. We could technically ship some similar products, but they would either be far inferior or take orders of magnitude longer to engineer by hand.
  - otabdeveloper4 5y ago
    Most business requires data analysis and planning. Under the hood regression models and/or some sort of component analysis is used. Deep learning is a cool feature to differentiate Alexa from competing home electronic gadgets. But if you want to forecast Alexa sales, or understand market segmentation, or the portrait of a typical Alexa buyer then you need something other than deep learning because neural nets utterly failed in this domain. The business metrics problem is vastly, vastly more important than the "making cool gadgets" problem, and huge resources were poured into making deep learning a thing in this space. The money was mostly wasted. (A negative result is still a result, but still the misallocation of resources is staggering.)
    - joefourier 5y ago
      I get that it didn’t work in your particular field and that obviously that’s what matters the most to you, but I would suggest reading up on its wider applications before dismissing the whole technology. Entire classes of products suddenly being possible is not just a “cool feature”. FYI, deep learning isn’t a differentiating feature for the Alexa, it powers essentially all modern voice applications.

otabdeveloper4 5y ago

Did you read my post? None of that drives business decisions. As for Alexa, et al - these things fall into the "generative art" bucket. The search results they give aren't any better than the Eliza-tier expert systems of yore. They just feel much better and more human when you use them. (Which is also important, but doesn't drive business decisions, except as part of a marketing strategy.)

joefourier 5y ago
What do you mean by doesn’t drive business decisions? ~65 million Alexas were sold last year, and the product would be fairly useless without very high performance speech recognition powered by deep learning. I personally own a startup that uses deep neural networks as part of its core product functionality and our business decisions would be drastically different if it weren’t for modern machine learning. We could technically ship some similar products, but they would either be far inferior or take orders of magnitude longer to engineer by hand.
- otabdeveloper4 5y ago
  Most business requires data analysis and planning. Under the hood regression models and/or some sort of component analysis is used. Deep learning is a cool feature to differentiate Alexa from competing home electronic gadgets. But if you want to forecast Alexa sales, or understand market segmentation, or the portrait of a typical Alexa buyer then you need something other than deep learning because neural nets utterly failed in this domain. The business metrics problem is vastly, vastly more important than the "making cool gadgets" problem, and huge resources were poured into making deep learning a thing in this space. The money was mostly wasted. (A negative result is still a result, but still the misallocation of resources is staggering.)
  - joefourier 5y ago
    I get that it didn’t work in your particular field and that obviously that’s what matters the most to you, but I would suggest reading up on its wider applications before dismissing the whole technology. Entire classes of products suddenly being possible is not just a “cool feature”. FYI, deep learning isn’t a differentiating feature for the Alexa, it powers essentially all modern voice applications.