AWS AI Blog

NIPS 2017 Challenge Pushes Deep Learning to Improve Surgical Outcomes

by Lukasz Kidzinski and Sunil Mallya | on | Permalink | Comments |  Share

AWS, NVIDIA, Stanford, EPFL, and UC Berkeley have joined forces to tackle clinical problems in biomechanics. The NIPS 2017 Learning to Run challenge brings together over 300 researchers, engineers, and enthusiasts from around the world to apply deep learning to medical research. The challenge will culminate at the international AI conference Neural Information Processing Systems […]

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Combining Deep Learning Networks (GAN and Siamese) to Generate High-Quality, Life-Like Images

by Guy Ernest | on | Permalink | Comments |  Share

Because deep learning relies on the amount and quality of the data that is used to train it, companies spend a lot to get good image data. Typically, they use either expensive human annotation or other labor-intensive tasks, such as taking more photos of products or people. This approach is costly, and it doesn’t scale. […]

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Export your Amazon Lex bot schema to the Alexa Skills Kit

You can now export your Amazon Lex chatbot schema into the Alexa Skills Kit to simplify the process of creating an Alexa skill. Amazon Lex now provides the ability to export your Amazon Lex chatbot definition as a JSON file that can be added to the Alexa Skills Kit (ASK). Once you add the bot schema file […]

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Bring Machine Learning to iOS apps using Apache MXNet and Apple Core ML

With the release of Core ML by Apple at WWDC 2017, iOS, macOS, watchOS and tvOS developers can now easily integrate a machine learning model into their app. This enables developers to bring intelligent new features to users with just a few lines of code. Core ML makes machine learning more accessible to mobile developers. […]

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Apple Core ML and Keras Support Now Available for Apache MXNet

We’re excited about the availability of Apache MXNet version 0.11. With this release, MXNet hit major milestones, both in terms of community development and as an incubating Apache project. Contributors—including developers from Apple, Samsung and Microsoft—committed code to this release. There are over 400 contributors on the project so far. The project has now fully […]

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Use Synonyms and Slot Value Validation in your Amazon Lex Chatbots

You can now provide synonyms for slot values in Amazon Lex. With the synonym functionality, you can specify multiple synonyms for a slot value in your chatbot. The synonyms specified are resolved to the corresponding slot values. For example, if the slot value is “comedy”, with “funny” and “humorous” specified as synonyms, then user input […]

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How Amazon Polly Breathed Life into Dan Brown’s Digital Assistant

This is a guest post by Damian Dutton, CEO and Founder of Beeliked. Beeliked is, in their own words, “a digital marketing platform offering a wide range of campaigns to help brands engage with their existing audiences and reach new customers through the viral and social nature of the contests and games.” To support the […]

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Benchmarking Training Time for CNN-based Detectors with Apache MXNet

by Iris Fu and Cambron Carter | on | Permalink | Comments |  Share

This is a guest post by Cambron Carter, Director of Engineering, and Iris Fu, Computer Vision Scientist at GumGum. In their own words, “GumGum is an artificial intelligence company with deep expertise in computer vision, which helps their customers unlock the value of images and videos produced daily across the web, social media, and broadcast […]

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AWS CloudTrail Integration is Now Available in Amazon Lex

Amazon Lex is now integrated with AWS CloudTrail, a service that enables you to log, continuously monitor, and retain events related to API calls across your AWS infrastructure, to provide a history of API calls for your account. Amazon Lex API calls are captured from the Amazon Lex console or from your API operations using […]

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A/B Testing at Scale – Amazon Machine Learning Research

by Guy Ernest | on | Permalink | Comments |  Share

This week, Amazon presented an academic paper at KDD 2017, the prestigious machine learning and big data conference. The paper shows Amazon’s research into tools that help us measure customers’ satisfaction and better learn how we can implement ideas that delight them. Specifically, we show an efficient bandit algorithm for multivariate testing, where one seeks […]

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