AWS re:Invent 2017

With the "freemium" model as the new norm for mobile apps, developers are supplementing their revenue with ad-based monetization. To maximize ad revenue, developers are using multiple ad networks as a best practice. This has created the need to track performance across ad networks and optimize for maximum revenue and fill rate. In this session, we create an app with ads from multiple ad networks. We illustrate how ad revenue can be maximized across these networks by tracking key metrics. Finally, we provide examples of segmenting users based on ad interactions and attributes, to further optimize ad monetization.

In this session, we will build a highly scalable mobile app, website, and serverless mobile backend architecture that demonstrates on-demand video streaming, adaptive multi-bitrate transcoding, and video content ingestion. We use AWS Lambda and Amazon Elastic Transcoder to automatically convert high resolution videos upon upload, Amazon CloudFront to stream video content to devices using network-aware adaptive multi-bitrate protocols (such as HLS), Amazon Cognito to authenticate users, and AWS Mobile Hub and AWS CloudFormation to automate setting up the required resources.

Mobile app development toolchains leveraging JavaScript, such as Ionic and React Native, are growing in popularity more each day. The pace of business makes it difficult to hire multiple engineers for different platforms and duplicate efforts. In this session you'll see hands on how you can build beautiful user applications using Ionic and React Native without spending months learning how your backend architecture should be designed. Using the newly released AWS Mobile CLI and build tooling you'll understand how your mobile developers can with a set of simple commands interface with Serverless AWS infrastructure and add in features such as User Sign-In and Sign-Up with Amazon Cognito, Serverless infrastructures using Amazon API Gateway, AWS Lambda and Amazon DynamoDB, and comprehensive analytics through Amazon Pinpoint.

JavaScript based applications across mobile and web can be challenging to integrate with AWS services for teams that aren't familiar with infrastructure operations. AWS Mobile has just launched a comprehensive open-source library, AWS Amplify, and tooling to help frontend and mobile developer quickly add features to their applications using a declarative programming style organized by categories of Authentication, Storage, APIs and Analytics. You'll see how Serverless infrastructure for mobile and web applications can not only be launched in a couple of commands, but you can use the new tooling to iteratively add features and code to applications that under the covers interface with Amazon Cognito, Amazon S3, Amazon API Gateway, AWS Lambda, Amazon DynamoDB and Amazon Pinpoint. You'll also see some framework specific techniques such as leveraging Higher Order Components (HOCs) in a React or React Native application as well as other best practices and utilities that AWS Mobile has released.

Given the increasing popularity of natural language interfaces such as Voice as User technology or conversational artificial intelligence (AI), Ally® Bank was looking to interact with customers by enabling direct transactions through conversation or voice. They also needed to develop a capability that allows third parties to connect to the bank securely for information sharing and exchange, using oAuth, an authentication protocol seen as the future of secure banking technology. Cognizant's Architecture team partnered with Ally Bank's Enterprise Architecture group and identified the right product for oAuth integration with Amazon Alexa and third-party technologies. In this session, we discuss how building products with conversational AI helps Ally Bank offer an innovative customer experience; increase retention through improved data-driven personalization; increase the efficiency and convenience of customer service; and gain deep insights into customer needs through data analysis and predictive analytics to offer new products and services. Session sponsored by Cognizant

In this session, we dive into design paradigms and architectures that allow you to leverage the power of AWS AI services and Analytics to build intelligent AI systems. Going back to 2001, Washington County jail management system has archived hundred thousands of mugshots and by using Amazon Rekognition and other AWS services, they were able to build a powerful tool for identifying suspects.

Deep Learning continues to push the state of the art in domains such as computer vision, natural language understanding, and recommendation engines. In this session, we provide an overview of Deep Learning focusing on relevant application domains. We introduce popular Deep Learning frameworks such as TensorFlow and Apache MXNet, and we discuss how to select the right fit for your targeted use cases. We also walk you through other key considerations for optimizing Deep Learning training and inference, including setting up and scaling your infrastructure on AWS.

Amazon Polly is a service that turns text into lifelike speech, making it easy to develop applications that use high-quality speech to increase engagement and accessibility. Get a glimpse into successful applications that use Amazon Polly text-to-speech service to enable an app to talk to its users. Attendees will benefit from understanding real-world business use cases, and learn how to add feature-rich voice capabilities to their new or existing applications.

In this session, we cover an integration of Amazon Lex with a contact center solution. We demonstrate how an Amazon Lex chatbot can be inserted into an interactive voice response (IVR) workflow in a contact center, enabling users to interact with the chatbot using natural language. We walk through a ready-to-deploy integration that includes building the bot, setting up the IVR, and managing the call routing. We also describe the best practices for selective routing based on user intent, exchange of information between the chatbot/IVR, and handover to a human agent.

Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Neural machine translation uses deep learning to deliver more accurate and more natural sounding translation than older statistical and rule-based translation algorithms. Amazon Translate enables translation at scale so that you can easily translate large volumes of text efficiently to handle tasks like localizing content for international users and facilitating real-time cross-lingual communication. Join this session to learn more and find out how you get can started with Amazon Translate, today!