Recently, Microsoft held its annual global IT conference, Microsoft Ignite 2021, virtually. The event announced a number of AI-based features and updates across the cloud platform Azure and other business applications. 

Like every year, the session started with a keynote speech from CEO Satya Nadela. His talk focused on the critical role of the public cloud.

During the keynote speech, Nadella touched upon five key attributes that will drive the next generation of innovation in cloud: 

• Ubiquitous and decentralised computing
• Empowered creators & communities at every place
• Expanded economic opportunity for every member of the global workforce
• Sovereign data and ambient intelligence
• Trust by design

Let’s look at all the machine learning updates and features announced at the recent Ignite 2021 event. 

Alex Kipman, Mixed Reality Technical Fellow at Microsoft, unveiled Microsoft Mesh — a new mixed-reality platform powered by Azure. Microsoft Mesh enables presence and shared experiences from anywhere on any device through mixed reality applications. With the Microsoft Mesh SDK, you can build collaborative, cross-platform mixed reality applications faster using AI-powered tools for avatars, holoportation, spatial rendering, and more. Mesh contains tools to enable holographic rendering, immersive experiences, spatial maps, and multi-user sync. 

Microsoft has announced the public preview of Azure Percept. Percept is a platform of hardware and services that intends to simplify the ways in which customers can use Azure AI technologies on the edge, including taking advantage of Azure cloud offerings such as device management, AI model development and analytics. 

Azure Percept will assist customers in building and managing edge AI solutions. The platform intends to simplify the process of developing, training and deploying edge AI solutions. Roanne Sones, Corporate Vice President at Microsoft’s edge and platform group, said the goal of this new solution is to give customers a single, end-to-end system, from the hardware to the AI capabilities, that “just works” without a lot of technical know-how.

Azure Purview

To enable customers to discover and govern data, Microsoft introduced its unified governance service called Azure Purview. Users can now use Azure Purview to scan Azure Synapse workspaces across serverless and dedicated SQL pools.

Azure Arc is a set of technologies that extends Azure management and services to any infrastructure. The developers at Microsoft created Azure Arc to enable the flexibility and agility customers are seeking to innovate anywhere while providing governance and security. Azure Arc enables customers to run Azure services in any Kubernetes environment, whether it’s on-premises, multi-cloud or at the edge. At Ignite 2021, the team announced the expansion of  Azure Arc enabled services to include Azure Machine Learning. Now, users can enable the Azure Machine Learning agent to run on any OSS Kubernetes cluster that Azure Arc supports.

Azure Synapse Pathway

Azure Synapse Pathway helps customers simplify their migration experience to Azure Synapse. With this tool, users can now scan their source systems and automatically translate their existing scripts into TSQL. Azure Synapse Pathway will support customers migrating from Teradata, Snowflake, Netezza, AWS Redshift, SQL Server, and Google BigQuery. 

Semantic Search

Semantic Search on Azure Cognitive Search is said to offer the best combination of search relevance, developer experience, and cloud service capabilities available on the market. At the heart of Azure Cognitive Search is its full text, keyword-based search engine built on the BM25 algorithm. With Semantic Search, users can avail a ranking algorithm that will use deep neural networks to rank the articles based on how “meaningful” they are relative to the query. 

Form Recognizer is an Azure Cognitive Service and an AI-powered document extraction service that understands any document. The service applies advanced machine learning techniques to accurately extract the text, key or value pairs as well as tables from documents. The document extraction service has several features, such as simple extraction, customised results, flexible deployment, among others.

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OpenCV.org has announced that the popular and long-running package OpenCV-Python is now an official OpenCV project.

OpenCV is a computer vision library that includes modules for standard image processing tasks such as filtering, warping, and color space conversion.

OpenCV was started at Intel in 1999. Its algorithms cover computer vision and machine learning and the collection is expanding day by day. OpenCV supports a variety of programming languages including C++, Python, and Java, and is available on platforms including Windows, Linux, OS X, Android, and iOS. Interfaces for high-speed GPU operations based on CUDA and OpenCL are also under active development.

OpenCV-Python is the Python API for OpenCV, combining the best qualities of the OpenCV C++ API and the Python language. It is a Python wrapper for the original OpenCV C++ implementation. It contains pre-built OpenCV with dependencies and Python bindings, so there’s no need to install OpenCV separately. OpenCV-Python makes use of the Numpy numerical operations library, and all the OpenCV array structures are converted to and from Numpy arrays. This makes it easier to integrate with other libraries that use Numpy such as SciPy and Matplotlib.

PyPi packages are provided for Windows, Linux (x86_64 and aarch64) and MacOS (x86_64). The OpenCV team is working on bringing support to the new Apple M1-powered hardware too, but say that this support depends on CI services support and hardware availability.

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