Microsoft AI platform: Powerful tools and services which is Making Azure Artificial Intelligence (AI) Real for Developers. Updates on the Microsoft Build 2019/2020 Preview: for AI, IoT and Edge Computing.
Making Azure Artificial Intelligence (AI) real for every developer and every organization has become a priority to scientist for boosting technology, Progressive Web Apps and Internet of things (IoT). AI as it is popularly called is currently stimulating the next wave of transformative innovations that will bring a huge change the world at large. However, with Microsoft Azure Artificial Intelligence (AI), it has an objective to enable organizations to apply AI across the peak of their businesses. This is simply to engage user customers, empower organizational employees, improve operations and transform products for better results.
Azure AI Guiding investment principles
However, to make this a reality, Azure AI has three guiding investment principles such as;
- Azure AI helps to boost the productivity of app developers and data scientists and also empower them to build Artificial Intelligence solutions faster.
- They support these AI solutions to be deployed at scale together with already existing systems and developments.
- They make sure that companies can build their products with full confidence knowing that they are the intellectual owner. Giving them assurance that they control their data on a platform that complies with some of the industry’s strictest privacy standards and has the full adherence portfolio of any hybrid cloud provider.
The listed guiding principles above allows Microsoft Azure to fulfill their mission of empowering both professional and/or upcoming developer and every organization to connect with the potential of Artificial Intelligence. They currently have research centers that scattered around the world; including Shanghai to Redmond. The company continues to achieve industry success in areas such as advanced machine learning techniques, language, vision, speech, and specialized AI hardware. As can be seen, these improvements are now main components of several of products such as Xbox, Dynamics 365, Office 365, and Bing. Furthermore, Azure AI is significant because customers can take advantage from the newest innovations that have been thoroughly battle-tested in Microsoft products.
Azure AI Adoption
There have been tremendous adoption of Azure AI by customers and Microsoft says that they are honored and humbled by this outcome. Research shows that both small and medium scales companies business in different sectors are using the Azure AI to transform their business by the following:
- Azure AI uses machine learning to create predictive models, improving business processes.
- With Azure AI, developers can utilize advanced vision, speech, language, and decision-enabling abilities to create AI powered apps. Agents can also deliver personalized and engaging experiences to users.
- Users can use Azure AI for applying knowledge mining to discover hidden insights from immense sources of data.
In the meantime, there are different types of innovations across all of these areas. Hybrid Cloud Tech team will do some explanation for a better understanding.
Azure Machine Learning
First of all, the Azure Machine Learning service was designed to accelerate the end-to-end machine learning lifecycle of developers. By making use of Azure Machine Learning, web & app developers and organizations can easily and speedily create, coach, and deploy models anywhere. Developers can do this from the intelligent cloud to the intelligent edge, together with managing their models with integrated (CI/CD) tooling.
The Azure machine learning strives to enable developers, data scientists, and DevOps professionals across all skill levels to grow in output, operations and innovate quicker. Their recent announcements includes:
1. New competences to improve productivity now in preview:
- They have built an automated machine learning user interface that enables business domain experts to train machine learning models with just a few clicks.
- Users new to machine learning does not need to learn coding, because the visual interface that enables them to create, teach, and deploy models easily using pick and drop abilities.
- There is also the Azure Machine Learning notebooks that offers developers and data scientists a code-first machine learning experience.
2. New abilities to support operationalization of models at scale:
- Firstly, the MLOps or DevOps for machine learning capabilities, including Azure DevOps integration that enables Azure DevOps to be used to manage the entire machine learning life cycle including model reproducibility, validation, deployment, and retraining.
- Secondly, there is a general availability of hardware accelerated models that run on FPGA’s in Azure for extremely low latency and low-cost inferencing. Available in preview for Databox Edge.
- Lastly, the Model interpretability capabilities that allow customers to understand how a model works and why it makes certain predictions, removing the ‘black box’ aspect of ML models.
3. Microsoft commitment to an open platform:
- Firstly, they have given contribution to the open source MLflow project, with native support for MLflow in Azure Machine Learning service.
- Secondly, they is currently great support for ONNX Runtime for NVIDIA TensorRT and Intel nGraph for high speed inferencing on NVIDIA and Intel chipsets.
- Thirdly, they offers preview of a new service, Azure Open Datasets, that helps customers improve machine learning model accuracy using rich, curated open data and reduce time normally spent on both data discovery and preparation.
Additionally, study shows that customers such as Schneider Electric BP and Walgreens Boots are deploying machine learning solutions at scale using the Microsoft Azure Machine Learning.
Furthermore, Diana Kennedy, Vice President, Strategy, Architecture, and Planning, BP say that they Azure Machine Learning service. In her speech, she said that they peace of mind with automated machine learning, knowing that they are exhausting all the possible scenarios and using the best model for their inputs.”
Read more about Machine Learning to discover more.
Artificial Intelligence (AI) apps and agents
Generally speaking, the combination of Azure Cognitive Services and Azure Bot Service helps developers to simply infuse powerful AI capabilities into their mobile apps and agents.
As a matter of fact, Azure Cognitive Services has been described as the most comprehensive portfolio in the market for developers who want to have the ability to see, hear, respond, translate, reason and more into their apps. Currently, Microsoft Azure has made it even easier for developers to input AI into their applications:
Azure Latest Decision Category.
Azure AI Services
First and foremost, the services offered in this category provide users recommendations to ensure informed and efficient decision-making for organisations. These services includes the recently announced Anomaly Detector, Content Moderator and a new service called Personalizer, available in preview, are part of this latest category. The Personalizer is created on reinforcement-learning and prioritizes relevant content and experiences for each user. This will to help improve app usability and engagement. Xbox owned by Microsoft drove a 40% lift in user engagement on its home screen as a result of using the Personalizer category.
Azure AI Vision
In this category, Microsoft announced two new services that are currently available in preview. The first one called Ink Recognizer empowers developers to combine the advantage of physical pen and paper with the best of the digital by embedding digital ink recognition capabilities into apps. With the Ink Recognizer, developers can now build on top of it to make notes searchable and convert hand-written drafts into presentation-ready content in a few minutes. Likewise, the Computer Vision read capability, which extracts text from common file types including multi-page documents and PDF, TIFF formats, is now largely obtainable.
Azure AI Speech
Next is the Speech category, where Microsoft announced preview of new advanced speech-to-text capability called conversation transcription. The speech catalyzes meeting efficiency by transcribing conversations in real-time so participants can fully engage in the discussion. They can now know who said what when, and quickly follow up on next steps. In addition, neural text-to-speech capability and Speech Service Device SDK are also now available to users.
Azure AI Language
The last category is the Language. Azure AI Language understanding has a new analytics dashboard to assess the value of language models. Also, QnA Maker now supports multiturn dialogs. Check now, you will see that the Text Analytics named entity extraction capability is now accessible to its customers.
In the meantime, they have also expanded the portfolio of Cognitive Services that can run locally through a Docker container. The preview is available to container support for Anomaly Detector, Text-to-Speech and Speech-to-Text.
Only Azure provides developers with the flexibility to embed these powerful AI services where needed. Visit Azure Cognitive Services to find out more.
Azure Bot Service, built on Microsoft Bot Framework, makes it easier to develop bots and intelligent agents. New enhancements include:
- Adaptive dialogs enable developers to create more sophisticated, dynamic conversations.
- Language generation package streamlines the creation of smart and dynamic bot responses.
- Emulator now has improved fidelity for debugging channels.
Azure AI for Sports
The popular LaLiga shown in sports channels which the premier men’s soccer league of Spain, creates solutions using Cognitive Services, Bot Service, and other Azure services. After all, their intelligent bot gives LaLiga League innovative ways to stay connected with their fans on their preferred social platforms. In like manner, they are delivering a world-class voice assistant which is key to scoring brand love with fans:
In the same way, Howden, Chevron, UiPath, British Petroleum, Icertis and others has taken advantage of Azure Search and Form Recognizer to extract insights from their content and automate processes.
The Microsoft Azure AI uses the Form Recognizer as a major document extraction capability on our Robotic Process Automation (RPA) platform and our open AI ecosystem. Again, UiPath’s and Microsoft’s investments in AI are streamlining the process of unlocking key business data. They are making possible a new era of AI-driven business insights and knowledge management say Mark Benyovszky, Director Artificial Intelligence, UiPath.
Searches related to Azure AI (Artificial Intelligence) Real for Developers
- azure ai tutorial
- microsoft ai
- azure ai certification
- microsoft azure ai laptop
- azure ai gaming
- microsoft azure ai gamin
- azure ai training
- azure machine learning
Continuing to innovate
Microsoft says that they will continue to invest to make Azure the best place for AI and we are most excited to see how users are applying AI in their organisations. Finally, it is noted that the opportunities are limitless, and you can try creating with Azure AI.