de:code 2018 was Microsoft Japan's annual conference for developers held on May 22-23, 2018 in Tokyo. The conference covered topics like Azure, AI, mobile, IoT, and focused on themes of ubiquitous computing, cross-platform development, and machine learning. Keynotes demonstrated new Azure capabilities like Event Grid, IoT Edge, and customizing Cognitive Services for tasks like visual search and image classification. Sessions also covered tools like Visual Studio, Azure Kubernetes Service, and Azure Data Bricks for big data analytics on Spark. The latest trends in machine learning presented were addressing bias in data and models, and meta learning to learn how to learn more efficiently.

1. de:code 2018
report
Osamu Masutani
May, 23, 2018

2. Event summary
de:code 2018 Microsoft Japan
• Date : May 22-23 2018
• Venue : The Prince Park Tower Tokyo
• https://www.microsoft.com/ja-jp/events/decode/2018/
• Annual conference of Microsoft Japan for developers
• Scope : Azure, AI, Mobile, IoT
• Audience
• Application, Web developer/designer
• Infrastructure administrator
• Architect
• Event component
• Key note, Sessions, Special program
• EXPO, Hackathon
Woman in technology
Key note
CVP, Azure Marketing, Julia White氏
CVP, Developer Division, Julia Liuson氏
CVP, Mixed Reality Studios General
Manager, Lorraine Bardeen氏

3. Summary
• Theme : LOVE to CODE
• Core technologies
• Ubiquitous computing
• AI
• Multi-sense/multi-device experience
• Multi-device
• Cross platform application (timeline, messaging etc..)
• Cross platform development (Xamarin, UWP,
Functions etc…)
Your phone

4. Azure
• 4 sectors
• Container + Serverless
• IoT
• Data
• AI
• Key note demo
• Azure Event Grid + IoT Edge + Cosmos DB:Multi Master write
• NBA’s video analysis with Azure Search & Cognitive Services

5. Development suite
• Visual Studio > 7M users
• Visual Studio Code > 3.6M users
• New features
• Visual Studio Live Share
• Real time collaborative development
• Azure DevOps Projects
• App fabric + CI/CD + application insights
• DevOps project with AKS
• Azure Kubernetes Services

6. Mixed Reality
• Official “application” for Hololens
• Microsoft Remote Assist
• Remote connection into AR for assistive task
• Microsoft Layout
• AR based real size, real time design
• Current important usecases
• Remote assist
• Spatial analysis
• Training
• Cooperative work

7. Others
• IoT business collaboration lab. (ビジネス共創ラボ)
• 435 companies
• Robot, healthcare, VR, logistics etc…
• AI bot “Linna”
• Updated with sympathy engine
• Understand context
• AI for Accessibility
• Many program to assist
• Accessibility Developer Community

8. Cognitive Services
• Rebrand to “Azure Cognitive Services”
• Customizing features
• Custom vision
• Object detection with location
• Model export with TensorFlow,CoreML,ONNX
• Custom speech
• Change voice with customized person
• Custom translation
• Add dictionary
• Bing
• Visual search
• Search by image
• Custom search
• Custom image, suggest, statistics
Custom vision
Visual search

9. Azure data lake
• Azure DataLake store
• Hive-like data store for file, document, object,
table
• Can access as scale out data store
• Most of platform in Azure can access to
datalake
• Azure DataLake analytics
• SQL based big data analytic engine
• No need to understand Hadoop
• High customized data flow both query based
and process based pipeline
• U-SQL with various UDF (C#, Python, R)

10. Azure data bricks
• DataBricks on Azure
• Native full stack analytic environment on Spark
• Azure integration
• Azure AD, data store (incl. data ware house, data lake, cosmos db), Power BI
• Familiar interface
• Easy management of Spark cluster
• Jupyter notebook
• Data share
• As you go style
• Cluster can launch fast
• Auto destruction of cluster

11. Azure Geo AI Data Science Virtual Machine
• ESRI provide special VM on Azure
• ArcGIS Pro is preinstalled
• Quickly start geographic analytics
• Can coop with Data science VM features
• Image classification is demonstrated
• Import satellite image data to ArcGIS
• Analyze with plugin by python
• Display classified map in ArcGIS
Image classification
Image classification
ArcGSI Pro

12. Latest trend in Machine learning
• Senior scientist Olga Liakhovich from MS report NIPS2018
• Growing conference over 8000 people attend
• Bias
• Any data have bias
• We need consider the bias implicitly/explicitly
• Meta learning
• Learn how to learn
• Deep learning choose quick and efficient structure/hyper parameter of deep
learning