Machine Learning Roundup 10/13/2016
Machine learning (ML) and deep learning (DL) content from the past 24 hours.
Note to readers: Big Analytics will rebrand as ML/DL soon.
— Adrian Colyer summarizes a paper on deep symbolic reinforcement learning.
— Another excellent piece from Nicole Hemsoth, on Bitfusion, a startup that delivers software-defined supercomputing through virtualization and efficient use of accelerators.
— Davey Winder summarizes how advances in machine learning combined with new data from wearables help insurers predict risk and detect fraud.
— Jason Lim summarizes what leading ML and AI scientists say about the future.
White House Report on AI
— The White House publishes a report: Preparing for the Future of Artificial Intelligence. In Fortune, Barb Darrow summarizes. The report, which is 50 pages long, includes a paragraph on discrimination. Jordan Pearson thinks it’s all about racism.
Bias in Machine Learning
— Yvonne Baur asks: Is machine learning sexist? She recaps the Word2vec problem, reported in MIT Technology Review and an academic paper; a neural network trained on millions of Google News articles learned gender stereotypes. Baur’s proposed solution is unbiased business and unbiased data. She should have read the academic paper; the authors suggest a specific way to treat bias.
— ProPublica releases the third installment in a four-part investigative series on black box algorithms that “dominate your life.”
Health and Medicine
— A team of investigators at the Medical University of South Carolina discovers that machine learning models that include biomarkers markedly improve clinicians’ ability to predict treatment outcomes.
— InsideBIGDATA touts a white paper on Healthcare and Life Sciences by Daniel Gutierrez.
DeepMind Rides the Subway
NVIDIA Supercomputers in Action
— OpenAI mines Reddit with a stupidly powerful NVIDIA DGX-1.
— Consulting firm ABI predicts a booming market for machine learning among telcos.
— Daven Mathies describes Netgear’s progress in facial recognition for home security.
— Can a computer win at poker? The answer reveals a lot about the direction of AI.
— TuSimple, a Chinese AI startup, announces that it has broken ten records on the KITTI/Cityscapes public dataset for autonomous driving.
— Drive.ai seeks to develop tools to retrofit existing cars for autonomous operation.
— In-Q-Tel, the CIA’s venture capital arm, invests in Brainspace, a startup specializing in machine learning for unstructured data.