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Has anyone done something genuinely useful with ml/ai/whatever outside of advertising or stock trading? I am genuinely curious if it has really been applied to

Has anyone done something genuinely useful with ml/ai/whatever outside of advertising or stock trading? I am genuinely curious if it has really been applied to real commercial applications.

colordrops 8y ago
Improvements in search, translation, image recognition and categorization, voice recognition, and text to speech off the top of my head. I'm sure there are a lot more.
- paulie_a 8y ago
  Yeah but those are all pretty terrible to the actual end consumer. They might be cool technologies but at the end of the day, I am a user that hates dealing with them. IVRs are terrible a experience. Image recognition is iffy at best. Text to speak is terrible. In 10 years maybe they will have it hashed out... just like 10 years ago, or 20 years ago
  - vazamb 8y ago
    What are you talking about? Google assistant is entirely ML driven text to speech and sounds great, wavenet by deepmind is almost indistinguishable from human speech.
  - colordrops 8y ago
    I'd have to disagree. While IVR sucks (most current implementations don't use ML by the way), image recognition and categorization is at or better than human levels in most cases now. Cutting edge TTS is now nearly indistinguishable from a human. Just check out some samples [1]. And while translation still sucks, ML based translation is still far better than previous approaches. [1] https://www.theverge.com/2018/3/27/17167200/google-ai-speech-tts-cloud-deepmind-wavenet https://www.theverge.com/2018/3/27/17167200/google-ai-speech...
- tyrex2017 8y ago
  Have you spent real money on something because it used Deep Learning? Me not. Maybe indirectly, ads have become more targeted, but we cant be sure how much. It might be just a dtandard small optimization
mr_toad 8y ago
A lot of problems that involve risk or uncertainty, and that have measurable inputs. Thinks like market segmentation, customer retention and conversion, identifying potential bad debts and fraud, targeting products, identification of product features etc. Not as sexy as the headlines, and less likely to involve DNN, but still profitable.

Has anyone done something genuinely useful with ml/ai/whatever outside of advertising or stock trading? I am genuinely curious if it has really been applied to real commercial applications.

colordrops 8y ago

Improvements in search, translation, image recognition and categorization, voice recognition, and text to speech off the top of my head. I'm sure there are a lot more.

paulie_a 8y ago
Yeah but those are all pretty terrible to the actual end consumer. They might be cool technologies but at the end of the day, I am a user that hates dealing with them. IVRs are terrible a experience. Image recognition is iffy at best. Text to speak is terrible. In 10 years maybe they will have it hashed out... just like 10 years ago, or 20 years ago
- vazamb 8y ago
  What are you talking about? Google assistant is entirely ML driven text to speech and sounds great, wavenet by deepmind is almost indistinguishable from human speech.
- colordrops 8y ago
  I'd have to disagree. While IVR sucks (most current implementations don't use ML by the way), image recognition and categorization is at or better than human levels in most cases now. Cutting edge TTS is now nearly indistinguishable from a human. Just check out some samples [1]. And while translation still sucks, ML based translation is still far better than previous approaches. [1] https://www.theverge.com/2018/3/27/17167200/google-ai-speech-tts-cloud-deepmind-wavenet https://www.theverge.com/2018/3/27/17167200/google-ai-speech...
tyrex2017 8y ago
Have you spent real money on something because it used Deep Learning? Me not. Maybe indirectly, ads have become more targeted, but we cant be sure how much. It might be just a dtandard small optimization

mr_toad 8y ago

A lot of problems that involve risk or uncertainty, and that have measurable inputs. Thinks like market segmentation, customer retention and conversion, identifying potential bad debts and fraud, targeting products, identification of product features etc. Not as sexy as the headlines, and less likely to involve DNN, but still profitable.