This post is co-authored by Chun Ming Chin, Technical Program Manager, and Max Kaznady, Senior Data Scientist, of Microsoft, with Luyi Huang, Nicholas Kao and James Tayali, students at University of California at Berkeley.
This blog post is about the UC Berkeley Virtual Tutor project and the speech recognition technologies that were tested as part of that effort. We share best practices for machine learning and artificial intelligence techniques in selecting models and engineering training data for speech and image recognition. These speech recognition models, which are integrated with immersive games, are currently being tested at middle schools in California.
The University of California, Berkeley has a new program founded by alum and philanthropist Coleman Fung called the Fung Fellowship. In this program, students develop technology solutions to address education challenges such as enabling underserved children to help themselves in their learning. The solution involves building a Virtual Tutor that listens to what children say and interacts with them when playing educational games. The games were developed by a technology company founded by Coleman named Blue Goji. This work is being done in collaboration with the Partnership for a Healthier America, a nonprofit organization chaired by Michelle Obama.
Now in preview
Jenkins Azure ACR Build plugin now in public preview – Azure Container Registry (ACR) Build is a suite of features within ACR. It provides cloud-based container image building for Linux, Windows, and ARM, and can automate OS and framework patching for your Docker containers. Now you can use Azure ACR Plugin in Jenkins to build your Docker image in Azure Container Registry based on git commits or from a local directory. One of the best things about ACR build is you only pay for the compute you use to build your images.
Also in preview Update Management: Pre/post tasks, dynamic groups, and update inclusion The Azure Podcast
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The Azure Podcast | Episode 247 – Partner Spotlight – Snowflake – Cynthia, Evan and Cale talk to Leo Giakoumakis, head of Snowflake’s Seattle Development Center, about their Data warehouse platform built for the cloud (and now available on Azure).
Now generally available
Immutable storage for Azure Storage Blobs now generally available – Many industries are required to retain business-related communications in a Write-Once-Read-Many (WORM) or immutable state that ensures they are non-erasable and non-modifiable for a specific retention interval. Immutable
Earlier this week, MIT, in collaboration with Boston Consulting Group, released their second global study looking at AI adoption in industry.
A top finding is that the leading companies in AI adoption are now convinced of the value of AI and are facing the challenge of moving beyond individual point solutions toward broad, systematic use of AI across the company and at-scale.
In the report, Joseph Sirosh, CTO of AI at Microsoft, discusses how Microsoft is building a complete AI platform that empowers enterprises to implement these AI-first business models and do so at scale. Scaling AI across an entire business requires companies to look far beyond just building that initial model.
As Joseph says, companies need an “AI Oriented Architecture capable of constantly running AI experiments reliably, with continuous integration and development, and then learning from those experiments and continuing to improve its operations.”
For those of you who are attending Microsoft Ignite at Orlando next week, you can hear Joseph talk about AI Oriented Architectures first hand, and get guidance on how enterprises can build successful AI solutions at scale.
Adopting Microsoft AI is super easy – you can get started here.
AI / ML Blog Team
Azure Artifacts manages the dependencies used in your codebase and provides easy tools to ensure the immutability and performance of those components. Released as one of the new services available for developers in Azure DevOps, the current features in Artifacts will help you and your users produce and consume artifacts. For teams that use or produces binary packages, Azure Artifacts provides a secure, highly performant store and easy feed.
Getting started with Artifacts: Package feeds
Azure Artifacts groups packages in to feeds, which are containers for packages that help you consume and publish.
We’ve optimized default settings to be most useful to feed users, such as making your feed account visible to easily share a single source of packages across your entire team. However, if you’d like to customize your settings, simply access the settings tab to refresh your preferences.
New feature: Universal Packages
Azure Artifacts is a universal store for all the artifacts you use as part of development and deployment. In addition to NuGet, npm, and Maven packages, feeds now support Universal Packages, which can store any file or set of files. You create and consume Universal Packages via the Visual Studio Team Services (VSTS) CLI. Consider
https://blogs.microsoft.com/iot/2018/09/20/why-iot-is-for-every-business-not-just-enterprise/Source: https://blogs.microsoft.com/iot/2018/09/20/why-iot-is-for-every-business-not-just-enterprise/ Harvard Business Review, McKinsey, and Gartner all agree: The Internet of Things (IoT) will transform business. Companies will connect the things they use and sell, creating rich, real-time data streams for their internal teams and partners. READ MORE
To help you stay up to date on online training opportunities, were releasing a monthly list of the latest free Data and Artificial Intelligence (AI) sessions in one convenient post.
With SQL Server virtual machines, you can use full versions of SQL Server in the cloud without having to manage any on-premises hardware. SQL Server virtual machines also simplify licensing costs when you pay as you go. They run many different geographic regions worldwide and offer a variety of machine sizes.
As data continues its exponential growth, its increasingly important to trim costs and manage risks while ensuring that your users have uninterrupted access. Register for this upcoming session to learn how to get started with SQL Server on Azure virtual machines, migrate your on-premises database to the cloud and use built-in features such as automated backup and patching.
Infuse your apps, websites, and bots with intelligent algorithms to see, hear, speak, understand, and interpret your user needs through natural methods of communication. The Microsoft AI platform offers a comprehensive set of flexible AI services for any scenario and enterprise-grade AI infrastructure that runs AI
With the abundance of data coming from IoT devices and the global nature of business today, it’s essential to be able to understand correlations and track historical trends across your assets.
Imagine managing a fleet of trucks carrying items that need to be maintained at a specific temperature. Occasionally you see a low temperature alert triggered for some of your trucks during their daily scheduled delivery. As an operator, you will need to conduct a root cause analysis to understand why this is happening, if there are recurring patterns, and how to prevent it from happening in the future.
To help you with this, we’re excited to announce that we have now integrated Azure Time Series Insights into the Azure IoT Remote Monitoring solution accelerator. With Time Series Insights, you can gain deeper insights into your time-series sensor data by spotting trends, anomalies, and correlations across real-time and historical data in all your locations. New Remote Monitoring deployments (both Basic and Standard) will include Time Series Insights out-of-the-box* at no extra cost. All messages data from your IoT devices will be stored in Time Series Insights, but your alarms, rules, and configuration settings will remain in Cosmos DB.
Artificial Intelligence (AI) and machine learning (ML) technologies extend the capabilities of software applications that are now found throughout our daily life: digital assistants, facial recognition, photo captioning, banking services, and product recommendations. The difficult part about integrating AI or ML into an application is not the technology, or the math, or the science or the algorithms. The challenge is getting the model deployed into a production environment and keeping it operational and supportable. Software development teams know how to deliver business applications and cloud services. AI/ML teams know how to develop models that can transform a business. But when it comes to putting the two together to implement an application pipeline specific to AI/ML — to automate it and wrap it around good deployment practices — the process needs some effort to be successful.
The need for aligned development approaches
DevOps has become the de-facto development standard for cloud services. It places an emphasis on process, automation, and fosters a culture that encourages new ways of working together across teams. DevOps is an application-centric paradigm that focuses on the platform, instrumentation, and process to support applications: what is the infrastructure needed to support the application? What tools can
Gaining insights rapidly from data is critical to being competitive in today’s business world. With a modern data warehouse, customers can bring together all their data at any scale into a single source of truth for use cases such as business intelligence and advanced analytics.
A key component of successful data warehousing is replicating data from diverse data sources into the canonical data warehousing database. Ensuring that data arrives in your data warehouse consistently and reliably is crucial for success. Data integration tools ensure that users can successfully connect to their critical data sources while moving data between source systems and their data warehouse in a timely yet reliable fashion.
We’re excited to announce that Fivetran has certified their zero maintenance, zero configuration, data pipelines product for Azure SQL Data Warehouse. Fivetran is a simple to use system that enables customers to load data from applications, files stores, databases, and more into Azure SQL Data Warehouse.
– George Fraser, CEO and Co-Founder at Fivetran
We’re also pleased
https://blogs.msdn.microsoft.com/sql_server_team/developers-choice-hinting-query-execution-model/Source: https://blogs.msdn.microsoft.com/sql_server_team/developers-choice-hinting-query-execution-model/ Over the years you have read a number of blogs advocating for or against trace flags that influence SQL Server’s query execution model. You can see a number of query execution related trace flags are documented at READ MORE