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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 under 20 mins. Don't miss it!

Dive deep and increase your expertise at the technical demos. 9 live demos will provide 100% content and 0% slides. This is how cloud works! From "BMXNet on the Edge, How to Build Deep Learning Model that Work on Edge Devices" over "Targeted Push Notifications & Mobile Engagement - Amazon Pinpoint Demo" to "Building a Smarter Home with Alexa" - we have them all - live on stage!

Aran Khanna, Software Development Engineer, 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.

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.

Markus Kaiser, Solutions Architect, AWS

Amazon Pinpoint, a new AWS service, makes it easy to run targeted campaigns to improve user engagement. Pinpoint helps you understand app user behavior, define who to target, what push notification to send, when to deliver the notifications, and track results.

Thomas Reske, 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.

Memo Doring, Solutions Architect, Amazon Alexa

Natural user interfaces, such as those based on speech, enable customers to interact intuitively with their home. This session will address the vision for the VUI (Voice User Interface) smart home and cover innovations that Amazon Alexa make possible. Session attendees will learn how developers, designers, and device makers build engaging voice experiences using the Alexa Skills Kit.

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.

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.

Jan Metzner, Solutions Architect, AWS

With AWS Greengrass we introduced serverless computing with local compute, messaging and data caching to devices. In this session we will show you how to manage real-time requirements for embedded devices out of the cloud. You will see how to optimize control logic in the cloud, bring this to devices with AWS IoT and AWS Greengrass in order to react in real-time. Weather this is a robot, an industrial machine or any other device you can have local control combined with intelligence in the cloud. 

Dr. Steffen Hausmann, Solutions Architect, AWS

The increasing number of available data sources in today's application stacks created a demand to continuously capture, store, and process data from various sources to quickly turn high volume streams of raw data into actionable insights.
Apache Flink addresses may of the challenges faced in this domain as it's streaming dataflow engine is specifically tailored to distributed computations over data streams. While Flink provides all the necessary capabilities to process streaming data, provisioning and maintaining a Flink cluster still requires considerable effort and expertise. In this talk we will discuss how cloud services can remove most of the burden of running the clusters underlying your Flink jobs.
We will explain how to build a real-time processing pipeline on top of AWS by integrating Flink with Amazon Kinesis Streams, Amazon EMR, and Amazon Elasticsearch Service. We will furthermore illustrate how to leverage the reliable, scalable, and elastic nature of the AWS cloud to effectively create and operate your real-time processing pipeline with little operational overhead.

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.