Deep learning on mobile
Who is this presentation for?
- Software developers
Over the last few years, CNNs have risen in popularity, especially in the area of computer vision. Many mobile applications running on smartphones and wearable devices could benefit from the new opportunities enabled by deep learning techniques. However, CNNs are by nature computationally and memory intensive, making them challenging to deploy on a mobile device.
Anirudh Koul and Meher Kasam explain how to practically bring the power of convolutional neural networks and deep learning to memory- and power-constrained devices like smartphones. You’ll learn strategies to circumvent obstacles and build mobile-friendly shallow CNN architectures that significantly reduce the memory footprint and make them easier to store on a smartphone. They also dive into how to use a family of model-compression techniques to prune the network size for live-image processing, enabling you to build a CNN version optimized for inference on mobile devices. Along the way, you’ll learn practical strategies to preprocess your data in a manner that makes the models more efficient in the real world.
- A basic understanding of deep learning
What you'll learn
- Learn how to optimize a model for minimum latency and maximum speed
Anirudh Koul is a head of AI and research at Aira, noted by Time magazine as one of the best inventions of 2018. He’s a noted AI expert and O’Reilly author, including the upcoming Practical Deep Learning for Cloud and Mobile. Previously, he was a scientist at Microsoft AI, where he founded Seeing AI, the most-used technology among the blind community after the iPhone. With features shipped to a billion users, he brings over a decade of production-oriented applied research experience on petabyte-scale datasets. He’s been developing technologies using AI techniques for augmented reality, robotics, speech, productivity, and accessibility. Some of his recent work, which IEEE has called “life-changing,” has been honored by CES, FCC, Cannes Lions, American Council of the Blind, showcased at events by the UN, the White House, the House of Lords, the World Economic Forum, Netflix, National Geographic, and applauded by world leaders including Justin Trudeau and Theresa May.
Meher Kasam is an iOS software engineer at Square and is a seasoned software developer with apps used by tens of millions of users every day. He’s shipped features for a range of apps from Square’s point of sale to the Bing app. Previously, he worked at Microsoft, where he was the mobile development lead for the Seeing AI app, which has received widespread recognition and awards from Mobile World Congress, CES, FCC, and the American Council of the Blind, to name a few. A hacker at heart with a flair for fast prototyping, he’s won close to two dozen hackathons and converted them to features shipped in widely used products. He also serves as a judge of international competitions including the Global Mobile Awards and the Edison Awards.
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