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Exciting live demos will be the focal point of this track. Slides will be degraded to second class citizens. Our presenters will walk you through new services, new paradigms, and new ways to think about cloud-powered applications. Some of them will use the web console, others our developer SDKs, and some might even use the CLI. But no matter what their tool of choice is, rest assured, they will do it live, on-stage, no tricks, un-cut, down to the point, in 30 mins. Don't miss it!

Dive deep and increase your expertise at the technical demos. 9 live demos will provide 100% content and nearly 0% slides. This is how cloud works! From "MXNet on the Edge, How to Build Deep Learning Models that Work on Edge Devices" over "From Clouds to Fogs to Devices with AWS Greengrass" to "Build an Alexa Skill in 30 Min using AWS Lambda" - we have them all - live on stage!

Cyrus M Vahid, Principal Solution Architect, AWS

MXNet is an open-source deep learning framework that allows you to define, train, and deploy deep neural networks on a wide array of devices, from cloud infrastructure to mobile devices. It is highly scalable, allowing for fast model training, and supports a flexible programming model and multiple languages.

This talk highlights high level features of MXNet and walks through building a simple feed forward network and its transformation to a convolutional for hand-witten digit recognition.

Aran Khanna, Software Development Engineer, AWS Deep Learning

Miro Enev, Solutions Architect, NVIDIA, AWS

As customers keep adopting deep learning, there is growing demand to deploy and manage these sophisticated models at the “edge”, in mobile or IoT deployments, driven by the need for real time and reliable ML running on data generated at the edge. This session will focus on using an edge optimized version of the open-source deep learning engine, MXNet, along with the newly released AWS GreenGrass service to deploy, monitor and manage a state of the art object recognition model running on a $35 Raspberry Pi. We will focus on how MXNet and GreenGrass allow customers to leverage edge deep learning to reduce cloud compute and bandwidth costs, while increasing reliability of edge based deep learning systems.

Daniel Geske, Solutions Architect, AWS

Device Farm is an app testing service that enables you to test and interact with your Android, iOS, and Web apps on real, physical phones and tablets that are hosted by Amazon Web Services. This session provides an introduction to the service and gives you a jumpstart on how to integrate AWS Device Farm into your continuous integration and delivery pipeline. Learn how you can test and interact with your Android, iOS, and web apps on many devices at once, or reproduce issues on a device in real time. Leave with new ideas to pinpoint and fix issues before shipping your app.

Christian Petters, Solutions Architect, AWS

Amazon Rekognition enables you detect objects, scenes, and faces in images. You can also search and compare faces. Rekognition’s API enables you to quickly add sophisticated deep learning-based visual search and image classification to your applications without the need to deploy any infrastructure or having to understand the deep since behind it. This session provides you with an introduction to the capabilities available using a number of use cases as examples.

Robert Hoppe, mSales

Alexa and its custom skills open the way to a new field that can be called VoiceOps. Why not finishing our daily DevOp tasks on AWS just with our voice? The Alexa Skills Kit and AWS Lambda help us to build completely serverless, voice-enabled architectures within minutes without managing any servers. The presentation shows the use-case of msales that was solved using Alexa and AWS Lambda. All will be topped off with a live demo showing how to execute tasks with Alexa on AWS.

Memo Doring, Solutions Architect, Amazon Alexa

As we add thousands of skills to the skills store our developers have uncovered some basic and more complex tips for building better skills. Whether you are new to Alexa Skill development or if you have created skills that are live today, this session will help you understand and learn best practices. During this session, you’ll build an Alexa skill using more advanced VUI concepts and we’ll cover how to use AWS services like dynamoDB and S3 to implement the best practices we cover.

Amir Golan, Senior Product Manager, Amazon Web Services

A suite of Chef and AWS native automation tools that help automate your configuration and deployment processes, test for compliance and security, and get visibility into your instances and their status.

You will be able to use these tools to manage operational tasks such as software and operating system configurations, package installations, database setups, and more.

Marc Trimuschat, Everett Dolgner, AWS Storage Services

In this session, we’ll provide an overview and demonstration of two use cases for AWS Snowball, a petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data into and out of the AWS cloud. We’ll first review how Snowball integrates with Enterprise Backup solutions and then we’ll demo Snowball Edge’s on-board compute data collection and transformation capabilities.

Jan Metzner, Solutions Architect, AWS

You have a perfect microservices architecture in the cloud which also means you can test, deploy and architect the solution seamlessly - but what about the software on your devices?

AWS Greengrass moves serverless computing to devices which brings you local compute, messaging and data caching, as well as direct communication between devices.

In this session we will show you how to architect microservices solutions on devices that use the same programming languages and model like your cloud architecture. You will be able to test in the cloud and deploy to the devices as many times as needed.

Meet your technical experts and get answers to all your questions. The Ask an Architect bar at the AWS Summit Berlin is a place where you can get a 1:1 session with a member of the AWS Solutions Architect Team. No appointment is necessary. The AWS tech experts are here to help with the AWS foundational questions and the highly technical ones tied to your specific use case. So, bring your questions about AWS architecture, cost optimization, services and features, and anything else AWS-related.