[dexter89_kp3]

Not in favor of the headline. The deepmind blog clearly states "Our results suggest that ML can complement maths research to guide intuition about a problem by detecting the existence of hypothesised patterns with supervised learning and giving insight into these patterns with attribution techniques from machine learning"

[dang]

The submitted headline was "Podcast: Google's 'DeepMind' Does Mathematics" because the submitted URL was https://www.numberphile.com/videos/deep-mind-podcast.

Since the title of the article we changed it to is vague and baity, I replaced it with a representative sentence from the article body, i.e. where Williamson describes the purpose of the research.

[anonymousDan]

Can anyone elaborate on what these attribution techniques might be? My understanding is that explainability is a bit of a holy grail for DNN research - are reliable techniques starting to emerge?