Machine Learning & AI Main Developments in 2018 and Key Trends for 2019

KDNuggets' survey of experts to on their thoughts. My favorite predictions came from Andriy Burkov who leads the ML team @ Gartner:

1. I expect everybody getting excited about AutoML promise even more than this year. I also expect it to fail (with the exception of some very specific and well-defined use cases, like image recognition, machine translation, and text classification, where handcrafted features aren't needed or are standard, raw data is close to what the machine expects as the input, and the data is in abundance).
2. Marketing automation: with mature generative adversarial networks and variational autoencoders it is becoming possible to generate thousands of pictures of the same person or paysage with small differences in facial expressions or mood between those images. Based on how consumers react to those pictures, we can generate optimal advertisement campaigns.

The thought of auto-generated images feeding into Facebook campaigns that are automatically A/B tested for reactions with millions of cheap impressions is simultaneously wonderful and horrifying.


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