This Week in Machine Learning, 12 August 2016

David Joyner
Udacity Inc
Published in
2 min readAug 12, 2016

This week’s top Machine Learning stories, including detecting zero-day exploits, optimizing deep learning, detecting sarcasm, and more!

Machine Learning is one of the most exciting fields in the world. Every week we discover something new, something amazing, something revolutionary. It’s incredible, but it can also be overwhelming. That’s why we created This Week in Machine Learning! Each week we publish a curated list of Machine Learning stories as a resource to help you keep pace with all these exciting developments. New posts will be published here first, and previous posts are archived on the Udacity blog.

Whether you’re currently enrolled in our Machine Learning Nanodegree program, already working in the field, or just pursuing a burgeoning interest in the subject, there will always be something here to inspire you!

Engineering

Google uses its own DeepMind machine learning algorithms to optimize its data centers, resulting in a 40% drop in the amount of energy devoted to cooling.

Theory

A new branch of machine learning, transfer learning, promises to streamline deep learning by discovering features that transfer to new tasks.

Hardware

A paper presented at the Flash Memory Summit in Santa Clara, California reveals machine learning can be used to extend the life of flash memory.

Security

Scientists at Arizona State University develop a new machine learning algorithm for identifying zero-day security exploits as they spread around the hacker community.

Industry

Apple acquires Seattle-based Turi, a machine learning startup that aims to make machine learning and artificial intelligence more accessible to app developers.

Social

Researchers at the University of Lisbon and UT-Austin create a deep learning model that can identify sarcasm in tweets based on the tweet itself and its account’s history.

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David Joyner
Udacity Inc

Product lead at Udacity. Founder of LucyLabs. Instructor at Georgia Tech. Find me at DavidJoyner.net.