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It's been an incredible week, with 3 major milestones

  • Microsoft won the image recognition Image-net challenge (see results) with an "extremely deep" network. The difficulty when dealing with such networks is to facilitate information flow and avoid so-called "vanishing gradients". Their approach based on residual learning is detailed in this paper.

  • Progress in"one-shot" machine learning where algorithms learn representations with very limited training sets. The approach here, called Bayesian Program Learning is detailed in this Science article

  • Google announced groundbreaking achievements in quantum computing, including a 100-million-fold speed-up over traditional approaches on a specific problem. In the long-term, this could shake up all the AI/ML field.

In the News



Also in the news this week...

  • The NIPS conference in Montreal took place this week. This year's hot topics and accepted papers can be viewed with this tool
  • Tensorflow gains traction outside of Google
  • $15M grant given to Cambridge to create a new interdisciplinary institution on AI and its implications for humanity

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