Eye On AI

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Week Ending 07.21.19

RESEARCH WATCH: 07.21.19

Over the past week, 823 new papers were published in "Computer Science".

Over the past week, 49 new papers were published in "Computer Science - Artificial Intelligence".

  • The paper discussed most in the news over the past week was by a team at Massachusetts Institute of Technology: "Tackling Climate Change with Machine Learning" by David Rolnick et al (Jun 2019), which was referenced 22 times, including in the article How artificial intelligence can tackle climate change in National Geographic. The paper author, David Rolnick (Massachusetts Institute of Technology), was quoted saying "Climate change does not present one problem, it presents multiple problems. AI is only one of the tools that can have an impact in the fight to mitigate the effects of climate change". The paper also got the most social media traction with 1459 shares. The researchers describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. On Twitter, @ikdeepl said "Yikes “In 2006, at least two Scottish seafood firms flew hundreds of metric tons of shrimp from Scotland to China and Thailand for peeling, then back to Scotland for sale – because they could save on labor costs”".

  • Leading researcher Sergey Levine (University of California, Berkeley) came out with "Dynamical Distance Learning for Unsupervised and Semi-Supervised Skill Discovery".

Over the past week, 163 new papers were published in "Computer Science - Computer Vision and Pattern Recognition".

This week was active for "Computer Science - Computers and Society", with 31 new papers.

This week was active for "Computer Science - Human-Computer Interaction", with 33 new papers.

This week was very active for "Computer Science - Learning", with 283 new papers.

Over the past week, nine new papers were published in "Computer Science - Multiagent Systems".

  • The paper discussed most in the news over the past week was by a team at University of Tartu: "Perspective Taking in Deep Reinforcement Learning Agents" by Aqeel Labashet al (Jul 2019), which was referenced 2 times, including in the article Last Week in AI in Hacker Noon. The paper got social media traction with 23 shares. The researchers present their progress toward building artificial agents with such abilities. A Twitter user, @dawn_alderson, posted "yes, a meta-learning strategy to close the gap between level 0 and level 2 perspective taking=RL has much promise but, I rather suspect hybridity needs to evolve in terms of the LSTM stack. hh", while @jaaanaru observed "Our first step toward creating AI agents with theory of mind: deep reinforcement learning agents can learn to take the perspective of another agent. This work was inspired by experiments done with chimpanzees, so we have monkeys and bananas on figures!".

Over the past week, 28 new papers were published in "Computer Science - Neural and Evolutionary Computing".

This week was active for "Computer Science - Robotics", with 46 new papers.

  • The paper discussed most in the news over the past week was by a team at University of North Carolina: "Identifying Emotions from Walking using Affective and Deep Features" by Tanmay Randhavane et al (Jun 2019), which was referenced 7 times, including in the article Indian Researcher & His Team Build AI That Can Tell How We Feel Just By Seeing Us Walk in Indiatimes. The paper author, Aniket Bera (University of North Carolina), was quoted saying "Though we do not make any claims about the actual emotions a person is experiencing, our approach can provide an estimate of the perceived emotion of that walking style". The paper got social media traction with 191 shares. On Twitter, @joemmac said "Gait is also sufficiently individualized that it can be used to ID targets with far less resolution and perfect angles than facial detection. And yes I used "targets" on purpose... welcome to the dystopia!".

  • Leading researcher Sergey Levine (University of California, Berkeley)


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