AI Weekly 1 September 2018

//AI Weekly 1 September 2018

AI Weekly 1 September 2018

Hi! New AI Weekly is here! Enjoy your weekend reading AI news and don’t forget to share it with your friends 😉

GENERAL

Scientists identify a new kind of human brain cell – one of the most intriguing questions about the human brain is also one of the most difficult for neuroscientists to answer: What sets our brains apart from those of other animals? In a new study published in the journal Nature Neuroscience, Ed Lein and his colleagues reveal one possible answer to that difficult question. The research team, co-led by Lein and Gábor Tamás, Ph.D., a neuroscientist at the University of Szeged in Szeged, Hungary, has uncovered a new type of human brain cell that has never been seen in mice and other well-studied laboratory animals. https://www.alleninstitute.org/what-we-do/brain-science/news-press/articles/scientists-identify-new-kind-human-brain-cell

Artificial Intelligence Is Now a Pentagon Priority. Will Silicon Valley Help? https://www.nytimes.com/2018/08/26/technology/pentagon-artificial-intelligence.html

OPENAI’S DOTA 2 DEFEAT IS STILL A WIN FOR ARTIFICIAL INTELLIGENCE  https://www.theverge.com/2018/8/28/17787610/openai-dota-2-bots-ai-lost-international-reinforcement-learning

AI Opportunities: Transforming Coverage of Live Events – The AI in Production team at BBC R&D is looking at some of the ways that Artificial Intelligence (AI) and machine learning could transform the business of producing media. https://www.bbc.co.uk/rd/blog/2018-08-artificial-intelligence-production

VIDEOS

Training Keras with GPUs & Serving Predictions with Cloud ML Engine https://www.youtube.com/watch?v=4pC97HRhK9E

PROGRAMMING

Machine Learning in Swift – Simple recommendation algorithm for Fitbit. http://theaigeek.com/machine-learning-in-swift-simple-recommendation-algorithm-for-fitbit/

Machine learning environment setup within 10min!!! https://blog.usejournal.com/machine-learning-environment-setup-within-10min-515c34ee33f3

PAPERS

Fisher Information and Natural Gradient Learning of Random Deep Networks  – many methods for approximating the natural gradient have been introduced. This paper uses statistical neurodynamical method to reveal the properties of the Fisher information matrix in a net of random connections under the mean field approximation. Authors prove that the Fisher information matrix is unit-wise block diagonal supplemented by small order terms of off-block-diagonal elements, which provides a justification for the quasi-diagonal natural gradient method by Y. Ollivier. https://arxiv.org/abs/1808.07172

By |2018-09-01T11:32:14+00:00September 1st, 2018|AI Weekly|0 Comments

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