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RE•WORK are offering a 20% discount on passes for the Deep Learning Summit & AI Assistant Summit with the code AIWEEKLY.
Experts will share their advancements in AI and confirmed speakers include Fabrizio Silvestri, Facebook; Ankur Handa, OpenAI; Andreas Damianou, Amazon; Marta Gernelo, DeepMind & more.
In the News
Apple scales back its ambitions for a self-driving car
Apple has been shifting its focus to a car OS rather than a full-blown self-driving car. Here's an interesting description of the discussions and the shake-up that took place during the shift.
Inside Facebook’s AI workshop
A few years ago the company’s machine learning group numbered just a few and needed days to run an experiment. Now several hundred employees run thousands of experiments a day. AI is woven so intricately into the platform that it would be impossible to separate the products — your feed, your chat, your kid’s finsta — from the algorithms.
How businesses succeed with AI
A survey of 3,000 executives is compiled here to reveal how AI is perceived by the C-suite. (TL;DR "the next digital frontier")
Why everyone is hating on IBM Watson
Watson has been a great technical and marketing success for IBM. But things seem to have run amok. Here's why.
The robot fashion guru
Amazon's AI uses machine-learning to find what suits you
Learning
Background removal with deep learning
Testing different approaches to remove backgrounds in photos
This is how Netflix's top-secret recommendation system works
Netflix splits viewers up into more than two thousands taste groups. Which one you’re in dictates the recommendations you get
Support Vector Machines Tutorial
SVM, though introduced 50 years ago, are still widely used. Here is an introduction to SVMs along with useful libraries and resources.
Software tools & code
Deep Learning for Siri’s voice
Paper by Apple researchers on their work to make Siri's voice more natural and smooth. They use a hybrid approach, mixing unit selection (concatenation of pre-recorded phonemes) and parametric synthesis.
Fashion replacement for MNIST
Drop-in replacement for the well-known MNIST digit dataset.
Hardware
Google TPU performance analysis
About
This newsletter is a collection of AI news and resources curated by @dlissmyr. If you find it worthwhile, please forward to your friends and colleagues, or share on your favorite network!
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