Re-posted from the Microsoft SQL Server blog.
Earlier today, at Build 2017, we made a string of announcements to further help developers and customers around the planet create breakthrough experiences through the power of artificial intelligence and big data. There were 3 major themes to these announcements:
1. AI at the Heart of the Microsoft Data Platform
Microsoft is simplifying the deployment of AI-powered apps by bringing intelligence into existing data platforms. The extensibility of our database architecture helped us introduce R support to SQL Server 2016, and we’re now adding Python support in our upcoming SQL Server 2017 release. Developers can tap into GPU-accelerated computing through the Python/R interfaces in SQL Server, implementing sophisticated AI directly in the database and gaining massively higher throughput on even their most intensive deep learning jobs, including on images and other unstructured data.
We are delivering key SQL Server 2017 enhancements to Azure SQL Database, giving you a consistent programming surface across on-premises and cloud. Today, we announced that support for Graph is coming to Azure SQL Database. Additionally, Azure SQL Database uses AI within the service itself, learning from your unique patterns, making performance and tuning recommendations, and even taking automatic actions on your behalf. We also announced the general availability of Threat Detection, which uses ML to learn, profile and detect anomalous activity over your database, so you can be automatically alerted about such events.
We also introduced a preview of the Azure Database Migration Service, dramatically simplifying the migration of your on-premises third-party or SQL Server databases into Azure SQL Database.
2. Deliver AI to Wherever Your Users Are
Delivering transformative AI-powered apps often requires more than a relational database or a simple NoSQL database. You need a flexible database that can ingest massive volumes of data and data types and deliver millisecond performance to users anywhere on the planet. Microsoft today announced the Azure Cosmos DB, the industry’s first globally-distributed, multi-model database service. Built from the grounds up with global distribution and horizontal scale at its core, Cosmos DB offers turnkey global distribution across any number of Azure regions, transparently scaling and distributing your data wherever your users are, worldwide.
Cosmos DB is based on the work of Microsoft’s Turing Award -winning researcher, Dr. Leslie Lamport – you can see a video of Dr. Lamport’s comments on Cosmos DB here.
3. Choice of Database Platforms & Tools
We are also giving developers more choice, announcing two new relational database services today – Azure Database for MySQL and Azure Database for PostgreSQL. These new services are built on our proven database platform, with the high availability, scale and data protection capabilities you expect from Microsoft, backed by an enterprise-grade, highly available and fault-tolerant cloud services platform.
We are also further enhancing the capabilities of Azure Data Lake (ADL) today. ADL lets you store data of any size, shape, and speed, and do all types of processing and analytics across platforms and languages. ADL includes a set of built-in cognitive capabilities that make it seamless to execute AI over petabytes of data. Today, we announced the General Availability of Azure Data Lake Tools for Visual Studio Code (VSCode), giving developers a powerful code editor for big data analytics. ADL Tools for VSCode supports U-SQL authoring, scripting, and extensibility with C#.
At Microsoft, we continue to evolve our intelligent data platform, and today’s announcements show our focus on empowering developers and organizations around the planet to build the next generation of AI-powered apps, with a choice of world-class platforms and tools. Learn more about these announcements at the original blog post here.
CIML Blog Team
from Cortana Intelligence and Machine Learning Blog https://blogs.technet.microsoft.com/machinelearning/2017/05/10/now-serving-more-ai-with-your-big-data/