AWS Machine Learning Blog

Category: Artificial Intelligence

Assisting People at Haptik Using Amazon Polly

Haptik is India’s first personal-assistant app. Users can use the app to plan travel, check in for flights, book taxis, and set reminders. And of all the different features, the most important and frequently used is the Reminders feature. People use Haptik to set wake-up calls, set up reminders to drink water, call people at different times, send greetings to others for different occasions, and much more. Through the reminders feature, users will receive notifications on the app along with a phone call at a requested time, relating the reminder message. In this post, we will cover how we use machine learning and text-to-speech (TTS) to set reminders for users – to call them at the given time to remind them of their tasks. We will cover how Amazon Polly helped us make personalized calls to our users and helped us scale our reminders feature to millions of users.

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AWS Contributes to Milestone 1.0 Release of Apache MXNet Including the Addition of a New Model Serving Capability

Today AWS announced contributions to the milestone 1.0 release of the Apache MXNet deep learning engine and the introduction of a new model serving capability for MXNet. These new capabilities (1) simplify training and deploying deep learning models, (2) enable implementation of cutting-edge performance enhancements, and (3) provide easy interoperability between deep learning frameworks. In […]

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Whooshkaa and Amazon Polly: Combining Eyes and Ears to Widen Publishing Horizons

Based in Australia, Whooshkaa is a creative audio-on-demand podcast platform that helps publishers and advertisers reach their audiences. We’re always trying new products and techniques, and combining them to pioneer new solutions for our customers. The Amazon Polly Text-To-Speech (TTS) feature is a great example of this. Already, we have top-tier publishers, sporting bodies, and Australia’s biggest telecommunications company using Amazon Polly to augment their established delivery methods.

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Customize and Display AWS DeepLens Project Output on Your Laptop

AWS DeepLens is a deep-learning-enabled developer toolkit with a video camera. It enables you to develop machine learning skills using hands-on computer vision tutorials, pre-built models and allows you to extend them. Examples of pre-built models include object detection to recognize and detect different objects in your room such as TV monitors, people and bottles, […]

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Extend AWS DeepLens to Send SMS Notifications with AWS Lambda

AWS DeepLens is a deep learning enabled developer toolkit with a video camera. It enables you to develop machine learning skills using hands-on computer vision tutorials, pre-built models and allows you to extend them. This blog post explains how to extend the local functionality of DeepLens with cloud functionality using the AWS IoT Rule Engine […]

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Distributed Inference Using Apache MXNet and Apache Spark on Amazon EMR

In this blog post we demonstrate how to run distributed offline inference on large datasets using Apache MXNet (incubating) and Apache Spark on Amazon EMR. We explain how offline inference is useful, why it is challenging, and how you can leverage MXNet and Spark on Amazon EMR to overcome these challenges. Distributed inference on large […]

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Receive Phone Call Alerts for AWS Account Security Events With Amazon Polly

Security of your AWS account is paramount. Staying up to date with any security-related events in your AWS account is important. There are various ways to get alerts- via email or SMS, however in this blog post I’m going to show you how to get a voice alert on your phone using Amazon AI services like Amazon Polly and any cloud-based communications platform like Twilio.

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Amazon Rekognition Announces Real-Time Face Recognition, Support for Recognition of Text in Image, and Improved Face Detection

Amazon Rekognition today announces three new features: detection and recognition of text in images, real-time face recognition across tens of millions of faces, and detection of up to 100 faces in challenging crowded photos. Customers who are already using Amazon Rekognition for face verification and identification will experience up to a 10% accuracy improvement in most cases.

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Run Deep Learning Frameworks with GPU Instance Types on Amazon EMR

Today, AWS is excited to announce support for Apache MXNet and new generation GPU instance types on Amazon EMR, which enables you to run distributed deep neural networks alongside your machine learning workflows and big data processing. Additionally, you can install and run custom deep learning libraries on your EMR clusters with GPU hardware. Through […]

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