The year in AI/ML advances: 2018 roundup

If I had to summarize the main highlights of machine learning advances in 2018 in a few headlines, these are the ones that I would probably come up:

• AI hype and fear mongering cools down
• More focus on concrete issues like fairness, interpretability, or causality
• Deep learning is here to stay and is useful in practice for more than image classification (particularly for NLP)
• The battle on the AI frameworks front is heating up, and if you want to be someone you better publish a few frameworks of your own

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