Category Archives : Artificial Intelligence

10

May

Spark + AI Summit: Data scientists and engineers put their trust in Microsoft Azure Databricks

Microsoft will have a major presence at Spark + AI Summit, 2018, in San Francisco, the premier event for the Apache Spark community. Rohan Kumar, Corporate Vice President of Azure Data, will deliver a keynote on how Azure Databricks combines the best of Apache® Spark™ analytics platform and Microsoft Azure Data Services to help customers unleash the power of data and reimagine possibilities that will improve our world.

Azure Databricks, a fast, easy, and collaborative Apache Spark-based analytics platform optimized for Azure, was made generally available in March 2018. To learn more about the announcement, read Rohan Kumar’s blog about how Azure Databricks can help customers accelerate innovation and simplify the process of building Big Data & AI solutions. At Spark + AI Summit, we have a number of sessions showcasing the great work our customers and partners are doing and how Azure Databricks is helping them achieve productivity at scale.

Sign up for training on Spark!

On Monday, June 4, 2018 there are a number of full-day training courses on Apache Spark ranging from beginner to advanced that will enhance your skill set and even prepare you for certification on Spark.

Apache Spark essentials

This 1-day course is for

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10

May

Full-integrated experience simplifying Language Understanding in conversational AI systems

Creating an advanced conversational system is now a simple task with the powerful tools integrated into Microsoft’s Language Understanding Service (LUIS) and Bot Framework. LUIS brings together cutting-edge speech, machine translation, and text analytics on the most enterprise-ready platform for creation of conversational systems. In addition to these features, LUIS is currently GDPR, HIPPA, and ISO compliant enabling it to deliver exceptional service across global markets.

Talk or text?

Bots and conversational AI systems are quickly becoming a ubiquitous technology enabling natural interactions with users. Speech remains one of the most widely used input forms that come natural when thinking of conversational systems. This requires the integration of speech recognition within the Language Understanding in conversational systems. Individually, speech recognition and language understanding are amongst the most difficult problems in cognitive computing. Introducing the context of Language Understanding improves the quality of speech recognition. Through intent-based speech priming, the context of an utterances is interpreted using the language model to cross-fertilize the performance of both speech recognition and language understanding. Intent based speech recognition priming uses the utterances and entity tags in your LUIS models to improve accuracy and relevance while converting audio to text. Incorrectly recognized spoken phrases or

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07

May

Build 2018: What’s new in Azure video processing and video AI

Developers and media companies trust and rely on Azure Media Services to build the ability to encode, protect, analyze and deliver video at scale. This week, at the Build 2018 conference in Seattle, we are proud to announce a major new API version for Azure Media Services, along with new developer focused features, and updates to Video Indexer.

Media processing at scale: Public preview of the new Azure Media Services API (v3)

Starting at Build 2018, developers can begin working with the public preview of the new Azure Media Services API (v3). The new API provides a simplified development model, enables a better integration experience with key Azure services like Event Grid and Functions, includes two new media analysis capabilities, and provides a new set of SDKs for .NET, .NET Core, Java, Go, Python, and Node.js!

We have created a set of preliminary documentation to get developers started quickly learning more about the new Azure Media Services preview release announcements.

Get Started with v3 Public Preview: REST API, SDKs, Swagger Files. Code Samples used at the Build 2018 session. Learn more about.. How the new Transform template makes it easier to submit encoding and analysis Jobs. How to use the

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07

May

Azure AI Platform announcements: New innovations for developers

Artificial Intelligence (AI) has emerged as one of the most powerful forces in the digital transformation. At Microsoft, we believe developers, data scientists and enterprises should have easy access to the power of AI so they can build systems that augment human ingenuity in unique and differentiated ways. Today, at Microsoft Build 2018, as we engage in conversations about digital transformation with over a million developers, customers and partners, I am pleased to share some of our latest and most exciting innovations in the Azure AI Platform.

The Azure AI Platform consists of three major sets of capabilities:

1. AI Services (Figure 1): These span pre-built AI capabilities such as  Azure Cognitive Services and Cognitive Search (Azure Search + integrated Cognitive Services), Conversational AI with Azure Bot Service, and custom AI development with Azure Machine Learning (AML).

Figure1: AI Services in Azure

2. AI Tools & Frameworks: These span Visual Studio tools for AI, Azure Notebooks, Data Science VMs, Azure Machine Learning Studio and the AI Toolkit for Azure IoT Edge.

3. AI Infrastructure: These span Azure Data Services, compute services including Azure Kubernetes Services (AKS) and AI Silicon support including GPUs and FPGAs.

Cognitive Services are cloud hosted

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07

May

Accelerating AI on the intelligent edge: Microsoft and Qualcomm create vision AI developer kit

Today at the Microsoft Build developer conference, we are announcing a partnership with Qualcomm, one of the largest mobile and IoT chipset manufacturers in the world, to jointly create a vision AI developer kit. This will empower Qualcomm’s latest AI hardware accelerators to deliver real-time AI on devices without the need for constant connectivity to the cloud or expensive machines.

This vision AI developer kit brings all the key hardware and software required to develop camera-based IoT solutions using Azure IoT Edge and Azure Machine Learning (ML) – helping innovators deliver the next generation of AI-enabled robotics, industrial safety, retail, home and enterprise security cameras, smart home devices and more. This is a crucial step toward enabling developers to easily create, manage and monitor AI on the edge.

This partnership allows developers to start building AI offerings with prebuilt solutions — including customizable models — or create new AI models and deploy directly to the cloud or to the new hardware accelerated devices. They can do so using the same powerful IoT Edge platform they have been using to manage other IoT devices and edge deployments — use a single pane of glass to manage all their AI assets across

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07

May

New Azure innovations are helping developers write code today for tomorrow’s technology challenges

This morning, at the Microsoft Build conference in Seattle, I talked about the key areas of new Azure innovation that enable the intelligent cloud and intelligent edge – spanning developer tools, DevOps, containers, serverless, Internet of Things (IoT) and artificial intelligence (AI).

Innovation starts with developers writing code. The effectiveness of your dev tools are at the heart of your ideas becoming reality. With this in mind, we continue to deliver new innovation and experiences with Visual Studio tools. Whether it is Visual Studio, VS Code or Visual Studio Team Services for DevOps, we are committed to providing the most productive developer experience end-to-end. Today, we announced a preview of Visual Studio IntelliCode, that brings AI to everyday development by providing intelligent suggestions that improve code quality and productivity. We also announced the preview of Live Share, which lets developers collaborate on their code and problem solve across Visual Studio and VS Code. Finally, building on our shared commitment to developers and open source, we also announced a fantastic partnership with GitHub where Visual Studio App Center will be natively available in GitHub via their marketplace. This means any GitHub developer building mobile apps for iOS, Android, Windows and macOS

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07

May

Microsoft Conversational AI tools enable developers to build, connect and manage intelligent bots

Conversational AI is the next user interface (UI) wave in computing. We’ve evolved from a world of having to learn and adapt to computers to one where they’re learning how to understand and interact with us. Natural interactions with computers start with language, speech, and semantic understanding, and continues through supporting rich multi model interactions.

Today at the Build conference, we are announcing major updates related to our Conversational AI tools including updates to Aure Bot Service, Microsoft Cognitive Services Language Understanding, and QnAMaker, as well as the release of new experimental projects from the Cognitive Services Labs including Conversation Learner and Personality Chat. This blog post provides a brief recap of all Conversational AI announcements from Build and takes a quick dive into some of our newly updated services.

With Microsoft’s Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack, and more. It’s quick, free, and easy to get started with the Microsoft Bot Builder software development kit (SDK) and its related tools, for a complete bot building experience. Building intelligent bot requires stitching together several components. Developers can

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02

May

Microsoft extends AI support to PyTorch 1.0 deep learning framework

Today Microsoft is announcing the support for PyTorch 1.0 in Azure Machine Learning Services and Data Science Virtual Machine.

PyTorch 1.0 takes the modular, production-oriented capabilities from Caffe2 and ONNX and combines them with PyTorch’s existing flexible, research-focused design to provide a fast, seamless path from research prototyping to production deployment for a broad range of AI projects. With PyTorch 1.0, AI developers can both experiment rapidly and optimize performance through a hybrid front end that seamlessly transitions between imperative and declarative execution modes. Data Scientists can develop models in PyTorch 1.0, which are saved in ONNX as the native format and directly use them in applications built on Windows ML and other platforms that support ONNX.

At Microsoft we believe bringing AI advances to all developers, on any platform, using any language, in an open and interoperable AI ecosystem, will help ensure AI is more accessible and valuable to all. Microsoft’s support for ONNX is an example of this – ONNX allows developers to choose the right framework for their task, framework authors can focus on innovative enhancements, and hardware vendors can streamline optimizations.

Azure Machine Learning Services provides support for a variety of frameworks including TensorFlow, Microsoft Cognitive

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25

Apr

Bing Custom Search: Build a customized search experience in minutes

It’s a little over five months since we launched the Bing Custom Search for general availability, and we’re happy to see a considerable number of websites around the world that are now powered by Bing Custom Search. You can use the Bing Custom Search offering for either powering your site search or building the vertical search experience through multiple relevant domains.

Bing Custom Search is an easy-to-use, ad-free search solution that enables users to build a search experience and query content on their specific site, or across a hand-picked set of websites or domains. To help users surface the results they want, Bing Custom Search provides a simple web interface where users can control ranking specifics and pin or block responses to suit their needs.

The Bing API Team’s goal is to empower both developers and non-developers to harness the power of the web by allowing them to build a customized search engine experience. Setting up a custom search instance is easy and quick. For customers who don’t have resources to invest in development efforts, we offer an easy to use Hosted UI solution at no additional cost.

If you believe in delighting your users and want to integrate customized

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12

Apr

Rubikloud leverages Azure SQL Data Warehouse to disrupt retail market with accessible AI

In the modern retail environment, consumers are well-informed and expect intuitive, engaging, and informative experiences when they shop. To keep up, retailers need solutions that can help them delight their customers with personalized experiences, empower their workforce to provide differentiated customer experiences, optimize their supply chain with intelligent operations and transform their products and services.

With global scale and intelligence built in to key services, Azure is the perfect platform to build powerful apps to delight retail customers, the possibilities are endless. With a single photo, retailers can create new access points for the customer on a device of their choice. Take a look at this example of what’s possible using Microsoft’s big data and advanced analytics products

AI can be complex, this is where Rubikloud comes in. Rubikloud is focused on accessible AI products for retailers and delivering on the promise of “intelligent decision automation”. They offer a set of SaaS products, Promotion Manager and Customer Lifecycle Manager, that help retailers automate and optimize mass promotional planning and loyalty marketing. These products help retailers reduce the complexities of promotion planning and store allocations and better predict their customers intention and behavior throughout their retail life cycle.

As Rubikloud

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