Share Your Experience with Azure AI and Support a Charity
AI is transforming how leaders tackle problem-solving and creativity across different industries. From creating realistic images to generating human-like text, the potential of large and small language model-powered applications is vast. Our goal at Microsoft is to continuously enhance our offerings and provide the best safe, secure, and private AI services and machine learning platform for developers, IT professionals and decision-makers who are paving the way for AI transformations. Are you using Azure AI to build your generative AI apps? We’re excited to invite our valued Azure AI customers to share their experiences and insights on Gartner Peer Insights. Your firsthand review not only helps fellow developers and decision-makers navigate their choices but also influences the evolution of our AI products. Write a Review: Microsoft Gartner Peer Insights https://gtnr.io/JK8DWRoL0.
The Azure Multimodal AI & LLM Processing Solution Accelerator
The Azure Multimodal AI & LLM Processing Accelerator is your one-stop-shop for all backend AI+LLM processing use cases like content summarization, extraction, classification and enrichment. This single accelerator supports all types of input data (text, documents, audio, image, video etc) and combines the best of Azure AI Services and LLMs to achieve reliable, consistent and scalable automation of tasks.
Announcing conversational PII detection service’s general availability in Azure AI language
We are ecstatic to share the release of general availability (GA) support for our Conversational PII redaction service in English-language contexts. GA support ensures better Azure SLA support, production environment support, as well as enterprise-grade security...The Conversational PII redaction service expands upon the Text PII redaction service, supporting customers looking to identify, categorize, and redactsensitive information such as phone numbers and email addresses in unstructured text...These services can help to detect sensitive information and protect an individual’s identity and privacy in both generative and non-generative AI applications which are critical for highly regulated industries such as financial services, healthcare or government, enabling our customers to adhere to the highest standards of data privacy, security, and compliance.
Language in Azure AI prompt flow
Prompt flow in Azure AI Studio is a development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs). Last Ignite, we announced Azure AI Language prompt flow available on GitHub. Today, we are excited to announce that Azure AI Language tooling is now available in prompt flow natively. With that, you can explore, quickly start to use and fine-tune various natural language processing capabilities from Azure AI Language, reducing your time to valueand deploying solutions with reliable evaluation. The Azure AI Language sample flows in Azure AI prompt flow gallery are good starting point for you. You can simply start by cloning one of the two sample flows: Analyze Documents: This flow is designed to analyze and extract insights from textual document input, such as identifying named entities, redacting Personal Identifiable Information (PII), analyzing sentiments, summarizing main points and translating to other languages. Analyze Conversations: This flow is designed for conversational input and particularly useful for contact center analytics or meeting review, such as summarizing customer issues and resolution, analyzing customer sentiment trend during calls, redacting PII, chaptering long meeting into segments making it easy to navigate and find topics of interest. Then you will see a wizard that guides you to configure tools in your flow, and run, evaluate, and deploy your flow: Graph view of your flow Files in your flow Azure AI Language tools in the “More tools” dropdown menu, which you can add capabilities that you need for your flow. There are more tools that you can add from LLM, Prompt, and Python menu. Configure output Configure steps (or tools) in the flow Run, evaluate, and deploy your flow What’s Next We will continue enhancing the underlying capabilities by leveraging state-of-the-art SLMs and LLMs, and enriching prompt flow offerings to further ease your effort in utilizing the best service Azure AI offers. Learn more about Azure AI Language in the following resources: Azure AI Language homepage: https://aka.ms/azure-language Azure AI Language product documentation: https://aka.ms/language-docs Azure AI Language product demo videos: https://aka.ms/language-videos Explore Azure AI Language in Azure AI Studio: https://aka.ms/AzureAiLanguage Prompt flow in Azure AI Studio: https://learn.microsoft.com/en-us/azure/ai-studio/how-to/prompt-flow PyPl package (includes general documentation): promptflow-azure-ai-language · PyPI Azure AI Language prompt flow github examples (includes READMEs): promptflow/examples/flows/integrations/azure-ai-language at main · microsoft/promptflow · GitHub
What’s new in Azure AI Language | BUILD 2024
Introduction AtAzure AI Language, we believe that language is at the core of human and artificial intelligence. As part of Azure AI that offers a comprehensive suite of AI services and tools for AI developers, Azure AI Language is a service that empowers developers to build intelligent natural language solutions that leverage a set of state-of-the-art language models, including Z-Code++, fine-tuned GPT and more. While LLMs in Azure OpenAI and model catalog are good for general purposes, Azure AI Language provides a set of prebuilt and customizable natural language capabilities that are fine-tuned and optimized for a wide range of scenarios, such as Personal Identifier Information (PII) detection, document and conversation summarization, text analytics for healthcare domain, conversational intent identification, etc., with leading quality and cost efficiency. These capabilities are available through a unified API that simplifies the integration and orchestration of natural language capabilities with no need of complex prompt engineering. Today, we're thrilled to announce more new features and capabilities designed to make your workflow more seamless and efficient than ever before at this year’s Microsoft Build with the following key highlights: 1) a unified experience for Azure AI Language in Azure AI Studio and improved integration with prompt flow, 2) improvements in existing prebuilt features such as Summarization, PII and NER, and 3) enhancements in custom features, especially in Conversational Language Understanding (CLU) to provide intent identification and entity extraction with higher quality in more regions. Azure AI Language now available in Azure AI Studio and prompt flow As part of Azure AI services, Azure AI Language now supports the new Azure AI service resource type for prebuilt capabilities like summarization, Personally Identifiable Information (PII) detection, and many others. It lets you access all Azure AI services, including Language, Speech and Vision, etc., with one single resource, which makes it easier to integrate the AI capabilities from across Azure AI. In the next few months, we will also support the customization capabilities in Azure AI Language in Azure AI Studio. We are excited to introduceAzure AI Language in Azure AI Studiowith two new playgrounds for you to try out: Summarization and Personally Identifiable Information detection. Both help infuse generative AI into your solutions. In Azure AI Studio, you have more options to try out and explore how to use them effectively for your needs. Prompt flow in Azure AI Studiois a development tool designed to streamline the entire development cycle of AI applications. We are happy to announce that Language's prompt flow tooling is now available in Azure AI prompt flow gallery. With that, you can explore and use various natural language processing features from Azure AI Language in prompt flow. You can quickly start to make use of Azure AI Language, reduce your time to value, and deploy solutions with reliable evaluation. What’s new in prebuilt features in Azure AI Language service Azure AI Language’s prebuilt capabilities enable customers to set up and running quickly without the need for model training. These prebuilt services are designed to accelerate time-to-value through pretrained models optimized for specific Language AI tasks, includingPersonally Identifiable Information (PII),Named Entity Recognition (NER),Summarization,Text Analytics for Health,Language Detection,Key Phrase ExtractionandSentiment Analysis and opinion mining, etc. As we learned a lot of customers want to use Language AI to derive insights from native documents like Word docs and PDFs, to minimize the time and eliminates the need for data preprocessing, we have recently released a public preview ofnative documents support for PII detection and Summarization service.More file formats and capabilities will be added into the feature towards its GA. Here is more information regarding what’s new in Azure AI Language’s prebuilt features: 2.1. Announcing GA general availability of Conversational PII Azure AI Language’s PII service can help to detect and protect an individual’s identity and privacy in both generative and non-generative AI applications which are critical for highly regulated industries such as financial services, healthcare or government. This PII service also supports Protected Health Information (PHI) and Payment Card Industry (PCI) data, and it’s available in 79 languages for around 30 general entity categories and more than 90 region-specific entity categories. By enabling users to identify, categorize, and redact sensitive information directly from complex text files, and native documents in .pdf, .docx and .txt file format, the PII service enables our customers to adhere to the highest standards of data privacy, security, and compliance with only 1 API call. Today, we are excited to announce thegeneral availability of conversational PII redactionin English-language contexts to further support customers looking to recognize and redact sensitive information in conversations, particularly now in speech transcriptions from meetings and calls for 6 recognized entity categories for conversations. Customers can now redact transcript, chat, and other text written in a conversational style (i.e. text with “um”s, “ah”s, multiple speakers, sensitive info in non-complete sentences, and the spelling out of words for more clarity) with better confidence in AI quality, Azure SLA support and production environment support, and enterprise-grade security in mind. Conversational PII will be available starting in late June. Please seeherefor the full list of supported languages for the PII service andherefor supported recognized for PII entities for conversation. 2.2. Enhanced address recognition for UK contexts with NER model updates We are excited to share an updatedNERmodel with improved AI quality and accuracy for both NER and PII detection. This model update will largely benefit location entities (e.g. addresses), finance entities (e.g. bank account numbers), and single letter spell outs where a speaker in a transcript may be spelling out a relevant entity (e.g. “M. I. CRO. S. O. F. and T”) where our new model shows improved F1 scores and decreased false positive recognitions. The updated model will be available starting in late June. 2.3. General availability of Recap summary for conversations in Summarization Azure AI Language’s Summarization service enables users to extract key points from the textual content and provide a comprehensive summary of documents or conversations. This service is powered by an ensemble of two sophisticated natural language models in which one is specifically trained for text extraction while the other fine-tuned GPT model is further optimized for text summarization without the need of any prompt engineering. In addition, Azure AI Language’s Summarization service comes with built-in hallucination detection capability. We appreciate customers' enthusiasm for Azure AI Language’s Summarization service since we announced its general availability last year. Document abstractive summarization and Conversation summarization capabilities are currently available in 6 regions and 11 languages whereas Custom Summarization is available in East US in English language. Please seeSummarization region supportarticle for the full list of supported regions, andSummarization language supportarticle for supported languages. Today, we are excited to announce the general availability of Recap summary for conversations in Azure AI Language service. This recap summary compresses a long conversation into one short paragraph and captures key information, which has been highly praised by preview customers, especially for many high-volume call center customers. Check out our product document to learn more aboutthe key features in conversation summarization. What’s new in custom features in Azure AI Language service Azure AI Language’s custom capabilities empower customers to customize their multilingual machine learning models based on a few labeled examples according to their specific use case. These custom service include but are not limited toCustom Text Classification,Custom Named Entity Recognition (NER), andConversational Language Understanding (CLU).Powered by the state-of-the-art transformer models, Azure AI Language’s custom multilingual models can be trained in one language and used for multiple other languages. In addition to custom features in Azure AI Language service, the advanced low-touch customization capability in Azure AI Language now also powersAzure AI Content Safety’s Custom Categoryfeature for custom content moderation. As part of custom services in Azure AI Language, Conversational Language Understanding (CLU) enables reliable conversational AI experience with intent identification and entity extraction. Today, we are excited to announce three new features in CLU as follows: Enhanced support for CLU applications to automate training data augmentation for diacritics Today, we are introducing a suite of improvements to increase the AI quality of your CLU apps. Many customers already enjoy our training configuration that allows customers to train in one language and use the app in 100+ languages. Since many customers around the world use English keyboards to type in Germanic and Slavic languages, it can be more difficult to classify the utterance into the correct intent without diacritic characters. Because of this, we’re excited to announce a new feature that allows you to automate the training data augmentation for diacritics. When this setting is enabled in your CLU project, CLU will automatically augment your training dataset to reduce the model’s sensitivity to diacritic characters. Derive more insights from additional granular entities in CLU applications Many of our customers enjoy the ease of leveraging prebuilt entity recognition, like location, in their custom models. However, it can be helpful to know even more information about an entity phrase. We are excited to introduce more granular entities in CLU. So, for an utterance such as “New York”, you can now recognize more than just location, but also additional details such as city or state. Check outCLU supported prebuilt entity componentsfor a full list of support prebuilt entities. Improved CLU training configuration to address CLU model scoring inconsistencies We have releaseda new CLU training configurationthat is designed to address scoring inconsistencies, especially related to managing confidence scores and ‘None’ intent classification for off-topic utterances. We are excited to see how this new training configuration (available in 2024-06-01-preview via REST API) improves your model’s performance. Availability of CLU authoring service in Azure US Government cloud As our government and defense customers expand their use of conversational AI, the need for Azure AI in government-compliant clouds has grown, so we are announcing that CLU authoring service is now available in the Azure US Government cloud. This means that you can build, manage, and deploy your custom CLU models for government use cases with the same ease and functionality as in the public cloud. We are looking forward to seeing how these new CLU capabilities will provide you with more flexibility and control, as you develop conversational AI solutions in your enterprise. Summary We look forward to seeing our customers use these capabilities to enhance productivity, summarize insights, protect data privacy and build intelligent chat experiences based on content in natural language. As always, Azure AI Language team remains committed to delivering innovative solutions that enable our customers to achieve their goals. We welcome your feedback as we strive to continuously improve and evolve our services with state-of-the-art AI models to offer the best managed and compliant natural language processing capabilities to our customers in Azure AI Language service. Learn more about Azure AI Language in the following resources: Azure AI Language homepage:https://aka.ms/azure-language Azure AI Language product documentation:https://aka.ms/language-docs Azure AI Language product demo videos:https://aka.ms/language-videos Explore Azure AI Language in Azure AI Studio:https://aka.ms/AzureAiLanguage Prompt flow in Azure AI Studio:https://learn.microsoft.com/en-us/azure/ai-studio/how-to/prompt-flow Native document support for PII and Summarization:https://aka.ms/language-native-docs-support Conversational PII detection:https://aka.ms/conversational-pii Summarization overview:https://aka.ms/summarization-docs Conversational Language Understanding overview:https://aka.ms/language-cluImagine, Integrate, Innovate: Join Microsoft's GenAI Hackathon - LIVE NOW!
Imagine, Integrate, Innovate: Build with Azure AI to revolutionize multimodal experiences in this virtual, GenAI hackathon. In the lead up to Microsoft Build, our flagship developer conference, we’re going big on multimodal building with our developer community by launching Microsoft's GenAI Hackathon on Devpost live now until May 6th! With Azure AI, you can blend the best of various AI technologies to create more dynamic, versatile, and responsible applications that make a big impact in the world.Whether you’re a pro or just starting out, there’s something for you.Azure AI Translator announces new features as container offering.
Seattle—April 17, 2024—Today,we are pleased to announce the release of document translation (preview) and transliteration features for Azure AI Translator containers. All Translator container customers will get these new features automatically as part of the update. Translator containers provide users with the capability to host the Azure AI Translator API on their own infrastructure and include all libraries, tools, and dependencies needed to run the service in any private, public, or personal computing environment. They are isolated, lightweight, portable, and are great for implementing specific security or data governance requirements. As of today’s release, the following operations are now supported when using Azure AI Translator containers: Text translation: Translate the text phrases between supported source and target language(s) in real-time. Text transliteration: Converts text in a language from one script to another script in real-time. E.g. converting Russian language text written in Cyrillic script to Latin script. Document translation (Preview): Translate a document between supported source and target language while preserving the original document’s content structure and format. When to consider using Azure AI Translator containers? You may want to consider Azure AI Translator containers in cases where: there are strict data residency requirements to ensure that sensitive information remains within the company’s security boundary. you reside in industries such as government, military, banking, and security enforcement where the ability to translate data without exposing it to external networks is a must. you require the ability to maintain continuous translation capabilities while operating in disconnected environments or with limited internet access. optimization, cost management, and flexibility to run on-premises with existing infrastructure is a priority. Getting started with Translator container. Translator containers are a gated offering. You need to request container access and get approved. Refer to the prerequisites for a more detailed breakdown. How do I get charged? The document translation and transliteration features would be charged at different rates similar to the cloud offering. Connected container: You're billed monthly at the pricing tier of the Azure AI Translator resource, based on the usage and consumption. Below is an example of document translation billing metadata transmitted by Translator connected container to Azure for billing. { "apiType": "texttranslation", "id": "f78748d7-b3a4-4aef-8f29-ddb394832219", "containerType": "texttranslation", "containerVersion": "1.0.0+2d844d094c930dc12326331b3e49515afa3635cb", "containerId": "4e2948413cff", "meter": { "name": "CognitiveServices.TextTranslation.Container.OneDocumentTranslatedCharacters", "quantity": 27.0 }, "requestTime": 638470710053653614, "customerId": "c2ab4101985142b284217b86848ff5db" } Disconnected container: As shown in the below usage records example, the aggregated value of‘Billed Unit’corresponding to the meters ‘One Document Translated Characters’ and ‘Translated Characters’ is counted towards the characters you licensed for your disconnected container usage. { "type": "CommerceUsageResponse", "meters": [ { "name": "CognitiveServices.TextTranslation.Container.OneDocumentTranslatedCharacters", "quantity": 1250000, "billedUnit": 1875000 }, { "name": "CognitiveServices.TextTranslation.Container.TranslatedCharacters", "quantity": 1250000, "billedUnit": 1250000 } ], "apiType": "texttranslation", "serviceName": "texttranslation" } References User documentation Pricing Send your feedback to mtfb@microsoft.comAzure AI Cloud Skills Challenge is LIVE!
The clock is ticking! Join our Azure AI Cloud Skills Challenges to earn a free exam voucher TL;DR: Time is running out to complete one of our four AI Cloud Skills Challenges! Finish one before April 19 th to receive 100% off the cost of a related certification exam from Microsoft.
