This Week in Machine Learning, 3 February 2017

David Joyner
Udacity Inc
Published in
2 min readFeb 6, 2017

This week’s top Machine Learning stories, including quantum physics, song-writing, computer vision, 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!

Technology

Bjørn Karmann from the Copenhagen Institute for Interaction Design creates the Objectifier, which uses machine learning to automate household interactions.

Arts

Grammy-nominated artist Alex Da Kid uses IBM Watson to analyze the Billboard’s hit songs for lyrical themes and to generate the musical underpinnings of the song “Not Easy”.

Commerce

Hewlett Packard Enterprise acquires Sunnyvale, California-based machine learning security startup Niara to improve its suite of tools for cybersecurity.

Society

Accenture publishes a new report predicting that machine learning and artificial intelligence will change, rather than replace, the existing human workforce.

Science

Scientists use machine learning to address some of the biggest unsolved problems in physics, like understanding and predicting the waveform function in quantum systems.

Industry

Facebook provides new details about its deep learning platform Lumos, allowing individuals without computer vision training to teach an agent to recognize images.

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David Joyner
Udacity Inc

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