"In a world of fiercely complex, emergent, and hard-to-master systems - from our climate to the diseases we strive to conquer - we believe that intelligent programs will help unearth new scientific knowledge that we can use for social benefit. To achieve this, we believe we’ll need general-purpose learning systems that are capable of developing their own understanding of a problem from scratch, and of using this to identify patterns and breakthroughs that we might otherwise miss. This is the focus of our long-term research mission at DeepMind.DeepMind’s work in 2016: a round-up | DeepMind
While we remain a long way from anything that approximates what you or we would term intelligence, 2016 was a big year in which we made exciting progress on a number of the core underlying challenges, and saw the first glimpses of the potential for positive real-world impact."
Wednesday, January 04, 2017
DeepMind’s work in 2016: a round-up | DeepMind
Check the full post for a review of DeepMind's 2016 results; also see What DeepMind brings to Alphabet (The Economist)
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