Category: Artificial Intelligence (AI)

Azure and Llama 2: A Powerful Combination

Azure and Llama 2: A Powerful Combination

Are you looking for a cloud platform that offers high performance, scalability, security, and flexibility? If so, you should consider Azure and Llama 2, the latest version of the popular open-source framework for building cloud-native applications. In this blog post, we will explore the features and benefits of Azure and Llama 2 and show you how to get started with them.

What is Azure?

Azure is Microsoft’s cloud computing platform that provides a range of services and solutions for various scenarios, such as web hosting, data analytics, artificial intelligence, Internet of Things, and more. Azure has over 200 products and services that you can use to build, deploy, and manage your applications on the cloud. Some of the advantages of Azure are:

  • Supports multiple languages, frameworks, and tools, such as .NET, Java, Python, Node.js, Visual Studio, GitHub, etc.
  • Offers global coverage with more than 60 regions and 170+ data centers worldwide.
  • The pay-as-you-go pricing model lets you only pay for what you use, with no upfront costs or termination fees.
  • Built-in security features and compliance standards protect your data and applications from threats and breaches.
  • A rich ecosystem of partners and third-party integrations that enhance its capabilities and functionality.

What is Llama 2?

Llama 2 is the second major release of Llama, an open-source framework for building cloud-native applications using microservices architecture. Llama 2 aims to simplify the development, deployment, and management of microservices on the cloud. Some of the features of Llama 2 are:

  • Supports multiple programming languages, such as Java, Kotlin, Scala, Groovy, etc.
  • Provides a set of libraries and tools that help you create, test, and run your microservices, such as Llama Boot, Llama Cloud, Llama CLI, etc.
  • Enables you to use various cloud services and platforms, such as Azure, AWS, Google Cloud Platform, Kubernetes, Docker, etc.
  • Offers a reactive and non-blocking approach that improves the performance and scalability of your applications.

How do you use Azure and Llama 2 together?

Using Azure and Llama 2 together can help you leverage the best of both worlds: the power and flexibility of Azure’s cloud services and the simplicity and productivity of Llama’s microservices framework. Here are some steps to get started with Azure and Llama 2:

  1. Create an Azure account if you don’t have one already. You can get a free trial with $200 credit for 12 months.
  2. Install Llama CLI on your local machine. You can download it from the official website or use a package manager such as Homebrew or Chocolatey.
  3. Create a new Llama project using the command `llama init`. You can choose from various templates and options to suit your needs.
  4. Add Azure dependencies to your project using the command `llama add azure`. This will enable you to use Azure’s services such as App Service, Cosmos DB, Service Bus, etc.
  5. Deploy your project to Azure using the command `llama deploy azure`. This will create or update the necessary resources on Azure and upload your application code.
  6. Enjoy your cloud-native application running on Azure!

Conclusion

Azure and Llama 2 are a powerful combination for cloud computing that can help you build modern, scalable, secure, and flexible applications on the cloud. You can use them together to create microservices-based applications that take advantage of Azure’s rich features and services.

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September 21, 2023 Artificial Intelligence (AI), Microsoft Azure No comments yet
ChatGPT Enterprise: The Future of Communication

ChatGPT Enterprise: The Future of Communication

Overview

In the fast-paced realm of AI-driven communication, businesses crave innovative solutions that meet their conversational needs and prioritize security and privacy. Enter ChatGPT Enterprise, a dynamic platform that enhances interactions and fortifies data. In this blog post, we’ll delve into what ChatGPT Enterprise brings to the table and how you can harness its potential.

Security and Privacy Reinvented

In the digital age, safeguarding sensitive data is paramount. ChatGPT Enterprise actively takes security to new heights. It employs advanced security measures, such as robust data encryption and stringent access controls, to safeguard your information from prying eyes. This guarantees that your business can communicate securely, knowing your data is protected.

OpenAI’s unwavering commitment to privacy is evident in ChatGPT Enterprise. This AI respects user confidentiality, strictly adhering to data usage policies. Knowing that your conversations are not subject to data mining for personal information, you can have peace of mind, creating a safer and more ethical conversational experience.

Advantages of ChatGPT Enterprise

It delivers a wealth of benefits:

Customization: Tailor the AI to suit your business’s unique requirements, fine-tuning it to comprehend industry-specific terminology and nuances, making it a versatile asset across various domains.

Scalability: Seamlessly adapts to your business’s growth, whether you’re a budding startup or an international conglomerate.

Enhanced Precision: The AI’s precision in providing responses and context-aware suggestions elevates the caliber of your interactions.

24/7 Availability: It is at your service around the clock, offering constant support to your customers.

Cost-Efficiency: Automate routine tasks and streamline your support teams’ workload, resulting in substantial cost savings.

Statistics Speak Volumes

  • The impact of OpenAI’s ChatGPT Enterprise is undeniable. In a recent survey by OpenAI, businesses using it reported a remarkable 30% reduction in response time and an impressive 20% increase in customer satisfaction.
  • According to a recent study by Gartner, chatbots can reduce customer service costs by up to 30%, increase customer satisfaction by up to 40%, and generate up to 20% more revenue.

How to Dive into ChatGPT Enterprise

Embarking on your Chat GPT Enterprise journey is straightforward. Here’s a step-by-step guide:

  1. Request Access: Start by visiting the [OpenAI website](https://www.openai.com/chatgpt) to initiate your access request.
  2. Customize Your Model: Collaborate closely with OpenAI’s experts to tailor the AI to your specific requirements.
  3. Seamless Integration: Integrate ChatGPT seamlessly into your existing communication platforms or websites.
  4. Training: Familiarize your team with the AI and its capabilities to ensure optimal utilization.
  5. Launch: Deploy ChatGPT Enterprise and begin reaping the benefits of enhanced customer interactions.

In conclusion, ChatGPT Enterprise stands as a game-changer in the realm of AI-driven communication. With robust security, enhanced privacy, and a plethora of advantages, it empowers businesses to communicate more effectively and efficiently. Don’t miss the opportunity to elevate your customer interactions – request access to it today. Your business deserves nothing but the best in AI-powered communication.

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September 11, 2023 Artificial Intelligence (AI) No comments yet
Azure AI Services: Innovate with Cognitive Power

Azure AI Services: Innovate with Cognitive Power

Introduction

In today’s fast-paced digital world, the power of artificial intelligence (AI) is indispensable for creating user-centric applications. Microsoft Azure offers a suite of AI-driven services under Azure Cognitive Services; each designed to enhance user experiences and streamline operations. Let’s delve into these nine Azure Cognitive Services to understand how they can revolutionize your applications.

Azure AI Services Related Blog Posts

  • Enhance User Engagement with Azure Personalizer: Azure Personalizer enables real-time content recommendations and personalization, elevating user experiences. Analyzing user behavior tailors content and recommendations to keep users engaged and satisfied.
  • Spatial Analysis with Azure Cognitive Services: Azure Cognitive Services can turn physical spaces into intelligent environments. Through spatial analysis, you can gather data to make informed decisions and create smarter, data-driven spaces.
  • Azure Translator: Bridging Language Gaps: Azure Translator breaks language barriers by offering automatic translation services. Your content can now reach a global audience, ensuring inclusivity and expanding your application’s reach.
  • Azure Face API: Recognizing Faces with Precision: Azure Face API provides facial recognition and identification capabilities, enhancing application security and personalization. It can also be employed for user authentication and access control.
  • Azure Speech Services: Immersive Voice Experiences: Azure Speech Services brings voice recognition and synthesis to your applications, delivering immersive experiences. Users can interact naturally with your apps through voice commands and responses.
  • Azure Computer Vision: Insights from Images: Azure Computer Vision extracts valuable insights from images, enabling data-driven decision-making. It identifies objects, text, and even emotions, making it invaluable for various industries.
  • Azure Text Analytics: Understand Customer Sentiment: Azure Text Analytics performs sentiment analysis on customer feedback, helping you understand customer satisfaction and pain points. This data can drive improvements and boost customer relations.
  • Azure Form Recognizer: Streamline Document Workflows: Azure Form Recognizer automates document processing, reducing manual data entry and streamlining workflows. From invoices to forms, it extracts valuable information accurately.
  • Language Understanding with LUIS: Language Understanding with LUIS (Language Understanding Intelligent Service) empowers applications to comprehend user intent and context, making them smarter and more user-friendly.

Conclusion

By harnessing the capabilities of Azure Cognitive Services, you can unlock the potential of AI to create more personalized, efficient, and user-centric applications. From real-time personalization to spatial analysis and language translation, Azure Cognitive Services offers a comprehensive toolkit for developers to elevate their applications in today’s AI-driven world.

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September 7, 2023 Artificial Intelligence (AI), Microsoft Azure No comments yet
Azure Knowledge Mining: A Powerful AI Solution

Azure Knowledge Mining: A Powerful AI Solution

Overview

Are you looking for a way to extract valuable insights from your data, regardless of its format, location, or complexity? Do you want to leverage the power of artificial intelligence (AI) to search, analyze, and explore your content at scale? If so, you might be interested in Azure Knowledge Mining, an emerging discipline in AI that uses a combination of intelligent services to quickly learn from vast amounts of information.

What is Azure Knowledge Mining?

According to Microsoft, knowledge mining is “an emerging discipline in artificial intelligence (AI) that uses a combination of intelligent services to quickly learn from vast amounts of information. It allows organizations to deeply understand and easily explore information, uncover hidden insights, and find relationships and patterns at scale.”

Azure Knowledge Mining is the Microsoft solution for knowledge mining, based on Azure Cognitive Search, the only cloud search service with built-in AI capabilities. Azure Cognitive Search enables you to ingest content from various sources, enrich it with AI skills such as natural language processing, computer vision, and machine learning, and explore it through search, bots, applications, and data visualizations.

What are the benefits?

Azure Knowledge Mining can help you gain faster insights from diverse content types, customize your solution for your industry needs, and enable knowledge extraction wherever your data lives. Some of the benefits of Azure Knowledge Mining are you can:

  • Ingest content from Azure sources like Azure Blob storage, Azure Table storage, Azure SQL Database, Azure Cosmos DB, and hundreds of third-party sources via dedicated connectors.
  • Extract text-based content from file formats such as PDF, Microsoft Word, PowerPoint, and CSV. See the full list of supported formats.
  • Enrich the content with AI skills to extract information, find patterns, and deepen understanding. For example, you can extract entities, key phrases, sentiments, locations, languages, images, audio, and more from your content.
  • Apply machine learning models as custom skills for specific requirements like industry-specific regulations or custom entity extraction.
  • Explore the newly indexed data via search, bots, existing business applications, and data visualizations. You can also use semantic search to understand user intent and contextually rank the most relevant search results for users.

How to use Azure Knowledge Mining?

To use Azure Knowledge Mining, you must follow three steps: ingest, enrich, and explore.

  1. Ingest: You need to create an Azure Cognitive Search service in the Azure portal and connect it to your data sources using indexers or push APIs. You can also use the Import data wizard in the portal to quickly create an index from your data source.
  2. Enrich: You must define a skillset specifying the AI skills you want to apply to your content. You can use predefined cognitive skills or custom skills that you create using Azure Machine Learning or other tools. You can also use the Knowledge Store feature to project enriched documents into tables or objects for further analysis.
  3. Explore: You need to create a search index that stores the enriched documents and enables fast and flexible querying. You can use the Search explorer in the portal to test your queries and see the results. You can also use the Azure Cognitive Search SDKs or REST APIs to integrate search functionality into your applications or services.

Conclusion

Azure Knowledge Mining is a powerful AI solution that can help you uncover latent insights from all your content. You can use Azure Cognitive Search and other Azure AI services to ingest, enrich, and explore your data at scale and deliver enhanced experiences to your users and customers.

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September 6, 2023 Artificial Intelligence (AI), Microsoft Azure No comments yet
Azure Confidential Computing: Key Benefits

Azure Confidential Computing: Key Benefits

Overview

Azure confidential computing comprises technologies that safeguard your data and models at every stage of the AI lifecycle, even when in use. This allows you to execute AI workloads with sensitive data without risking unauthorized access or tampering. In this blog post, we’ll explore what Azure confidential computing offers, its advantages, and how you can employ it to develop secure AI solutions.

What is Azure Confidential Computing?

Azure confidential computing is grounded in the concept of trusted execution environments (TEEs). TEEs are hardware-protected memory areas that isolate code and data from the rest of the system. They thwart access or modification by anyone, including cloud operators, malicious admins, or privileged software like the hypervisor. TEEs also offer cryptographic attestation, validating the integrity and identity of the code within.

It supports two TEE types: software-based and hardware-based. Software-based TEEs use techniques like encryption and sandboxing, creating isolated environments. Hardware-based TEEs utilize dedicated hardware features like secure enclaves or protected memory, ensuring more robust isolation. Azure provides both TEE types through various services and VM sizes.

Advantages Confidential Computing

It provides several advantages for AI developers and users:

  • Protecting data and models in use: Run AI workloads with sensitive data (e.g., personal, financial, or health information) without exposing them to unauthorized access or tampering. Safeguard model architecture and weights from theft or reverse-engineering.
  • Enabling new scenarios and collaborations: Unlock new possibilities for AI applications demanding high security and privacy. Enable multi-party training and federated learning without sharing data or models centrally.
  • Increasing trust and compliance: Boost trust and transparency in your AI solutions by offering verifiable proof of data and model protection. Comply with regulations such as GDPR or HIPAA mandating data privacy and protection.

How to Utilize Azure Confidential Computing for AI?

The Confidential Computing offers multiple services and tools for building AI solutions with TEEs. Here are some examples:

  • Azure Machine Learning: Train and deploy AI models using hardware-based TEEs (e.g., Intel SGX or AMD SEV). Orchestrate federated learning across edge devices or cloud nodes.
  • Azure Cognitive Services: Access pre-built AI models for vision, speech, language, and decision-making using software-based TEEs (e.g., Open Enclave SDK or Intel SGX). Customize these models securely with your data.
  • NVIDIA GPU VMs: Run GPU-accelerated AI workloads using hardware-based TEEs (e.g., NVIDIA A100 Tensor Core GPUs with Ampere Protected Memory). Ensure data and model confidentiality and integrity while harnessing GPU performance.
  • Microsoft Research Confidential AI: Explore cutting-edge research projects and tools that delve into the confidential computing frontier for AI. Examples include CrypTFlow2 for secure multi-party computation on encrypted data and CryptoNets for encrypted model inference.

Conclusion

Azure confidential computing empowers you to safeguard your data and models throughout the AI lifecycle, even during use. With Azure confidential computing, you can create trustworthy AI solutions that deliver security, privacy, collaboration, and compliance benefits. To delve deeper into Azure confidential computing and get started, click here.

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September 6, 2023 Artificial Intelligence (AI), Microsoft Azure No comments yet

Microsoft Sales Copilot: Sales Team Empowerment

Overview

Do you want to streamline your sales process and improve your customer relationships? If you do, you should check out Microsoft Sales Copilot, the AI assistant designed for sellers.

Microsoft Sales Copilot is a smart CRM companion with Dynamics 365 Sales or Salesforce Sales Cloud. It helps you automate and simplify tasks, personalize customer interactions, and stay in the flow of work by integrating with Microsoft 365 apps, such as Outlook and Teams.

In this blog post, we will explore some of the features and advantages of Sales Copilot. We will also show you how to get started with this powerful tool.

What You Can Do with Microsoft Sales Copilot

The Sales Copilot offers a range of AI capabilities to help you drive efficiency and effectiveness in your sales process. With Sales Copilot, you can:

  • Draft emails and set up meetings in Outlook with data from your CRM and Microsoft 365 using AI.
  • Save AI-generated email and meeting summaries in Teams, Outlook, and Dynamics 365 Sales directly to your CRM.
  • Eliminate note-taking with AI-generated meeting transcriptions, competitor mentions, and action items in Teams and Dynamics 365 Sales.
  • Get AI assistance for suggested tips, related information, and answers to customers’ questions during Teams calls.
  • Build stronger customer relationships with real-time call insights, content recommendations, and post-call analysis to improve future interactions.
  • Sync updates in Teams and Outlook to your CRM automatically to maintain accurate customer records.
  • View a summary of your customer information in Microsoft 365 apps using data from your CRM.
  • Work together with disparate sales teams using Teams collaboration spaces that offer integrated access to Dynamics 365 Sales and Salesforce data.

How Sales Copilot Benefits You

The Sales Copilot can help you achieve several benefits for your sales performance and customer satisfaction. Using it, you can:

  • Save time and reduce errors by automating and simplifying tasks that would otherwise require manual data entry or context switching.
  • Increase productivity and focus by eliminating distractions and staying in the apps you use daily.
  • Enhance communication and collaboration by sharing relevant information and insights with your team members and managers.
  • Improve customer experience and loyalty by delivering personalized and timely responses, suggestions, and follow-ups.
  • Boost sales effectiveness and outcomes by leveraging AI insights and recommendations to optimize your sales strategy and tactics.

How to Get Started

If you are interested in trying out Sales Copilot, here are some steps you can take to get started:

  • Check if you have the required licenses for Microsoft Sales Copilot. You need a product license for Microsoft 365 for enterprise or Office 365 for enterprise and a subscription for Dynamics 365 Sales Enterprise or Premium or Salesforce Sales Cloud.
  • Install Microsoft Sales Copilot from this link.
  • Connect your CRM account (Dynamics 365 or Salesforce) to Microsoft Sales Copilot.
  • Start using Microsoft Sales Copilot in Outlook or Teams.

For more information on installing and using Sales Copilot, click support page.

Conclusion

Microsoft Sales Copilot is a powerful AI assistant that can help you streamline your sales process and improve customer relationships. It works with Dynamics 365 Sales or Salesforce Sales Cloud and integrates with Microsoft 365 apps, such as Outlook and Teams, to help you automate and simplify tasks, personalize customer interactions, and stay in the flow of work.

If you want to boost your sales productivity and effectiveness, try it. You can start by installing Microsoft Sales Copilot from this link and connecting your CRM account.

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September 5, 2023 Artificial Intelligence (AI), Azure - What's New, Microsoft 365, Microsoft Azure No comments yet
Microsoft Security Copilot: Fortifying Digital Defenses

Microsoft Security Copilot: Fortifying Digital Defenses

Microsoft Security Copilot: Overview

Cybersecurity is crucial to any business, especially in the digital age. However, managing security risks and threats can be challenging and time-consuming. That’s why Microsoft has developed Security Copilot, an AI-powered tool that helps you protect your data and devices from cyberattacks.

Security Copilot is a cloud-based service that integrates with Microsoft 365 and Azure. It provides you with a comprehensive and personalized security dashboard where you can monitor your security posture, identify vulnerabilities, and take action to remediate them. Security Copilot also leverages AI to analyze your security data and provide insights and recommendations on improving your security.

Features and Benefits

Some of the features and benefits of Security Copilot are:

  • Gives you a single view of your security status across your Microsoft products, services, and third-party applications and devices.
  • Alerts you of any security incidents or anomalies and helps you investigate and respond quickly and effectively.
  • Uses AI to prioritize the most critical security issues and suggest the best actions.
  • Helps you comply with industry standards and regulations, such as GDPR, HIPAA, PCI DSS, etc.
  • Enables you to create and enforce security policies and controls across your organization.
  • Allows you to customize your security settings and preferences according to your needs and preferences.

Getting Started with Microsoft Security Copilot

To use Security Copilot, you need to follow these steps:

  • Sign up for a free trial or a paid subscription on the Microsoft Security Copilot website.
  • Connect your Microsoft 365 account to the service using the Azure Active Directory (AAD) authentication.
  • Configure your security settings and preferences on the Security Copilot dashboard.
  • Start monitoring and managing your data security with the service.

Microsoft Security Copilot is a powerful and easy-to-use service that can help you protect your data from cyber threats. It leverages the advanced capabilities of Microsoft 365 and Azure to provide a comprehensive and integrated data security solution. Try it today and see how it can enhance your data security. To learn more, click here.

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September 5, 2023 Artificial Intelligence (AI), Azure - What's New, Microsoft 365, Microsoft Azure No comments yet
Microsoft GitHub Copilot: AI-Driven Code Assistance

Microsoft GitHub Copilot: AI-Driven Code Assistance

Overview

Are you looking for a way to speed up your coding process and improve your productivity? If yes, then you should check out Microsoft GitHub Copilot, a new AI-powered tool that can help you write better code faster.

What is Microsoft GitHub Copilot?

Microsoft GitHub Copilot is a Visual Studio Code extension that uses artificial intelligence to suggest code snippets as you type. It can generate whole functions, tests, comments, and more based on your context and intent. It can also adapt to your coding style and preferences, learning from your feedback and edits.

What are the advantages?

The GitHub Copilot can help you save time and effort by automating some of the tedious and repetitive coding tasks. It can also help you discover new ways of solving problems, learn new APIs and frameworks, and avoid common errors and bugs. Moreover, it can enhance your creativity and innovation by suggesting alternative approaches and solutions you might not have considered.

How to use Microsoft GitHub Copilot?

To use GitHub Copilot, you must have a Visual Studio Code editor and a GitHub account. You can install the extension from the Visual Studio Code Marketplace or from the GitHub Copilot website. Once installed, you can start using it by typing some code in your editor and waiting for the suggestions to appear in a pop-up window. You can accept, reject, or modify the suggestions as you wish. You can also use keyboard shortcuts or voice commands to interact with the tool.

Some points to consider while using Microsoft GitHub Copilot:

  • Microsoft GitHub Copilot is not a replacement for human programmers. It is a tool that can assist you, but not do everything for you. You must still write some code, review the suggestions carefully, and test the output thoroughly.
  • GitHub Copilot is not a source of truth. It does not guarantee the correctness, completeness, or quality of the code it generates. It may sometimes produce inaccurate, inappropriate, or insecure code. You are responsible for verifying the validity and legality of your code.
  • GitHub Copilot is not a plagiarism tool. It does not copy code from existing sources but synthesizes new code from a large corpus of public code and natural language data. However, some of the code it generates may be similar to existing code, so you should always cite the sources if you use any code snippets from Microsoft GitHub Copilot.

Conclusion

Microsoft GitHub Copilot is a groundbreaking tool that can revolutionize how developers code. It can help you write better code faster, with less hassle and more fun. However, it is not a magic wand that can solve all your coding problems. You still need to use your judgment, skills, and ethics when using it. To learn more about GitHub Copilot, visit its official website or read its documentation.

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September 5, 2023 Artificial Intelligence (AI), Azure - What's New, Microsoft 365, Microsoft Azure No comments yet

Amazon Machine Learning: August 2023 Updates

Amazon Machine Learning: Overview

Machine learning is a fast-growing field that enables computers to learn from data and make predictions. Amazon is a leader in machine learning, offering a range of services and tools for developers, researchers, and businesses. This blog post will highlight some of the new features and enhancements Amazon announced in August 2023 for its machine learning portfolio.

Amazon SageMaker Studio Lab: A Free and Interactive Environment for Machine Learning Education and Exploration

Amazon SageMaker Studio Lab is a new service that provides a free and interactive environment for anyone who wants to learn and experiment with machine learning. Users can access pre-configured Jupyter notebooks, tutorials, datasets, and frameworks and use its features such as data processing, model training, debugging, deployment, and monitoring. Also, collaborate with others and share their work through GitHub integration. Amazon SageMaker Studio Lab is ideal for students, educators, hobbyists, and anyone wanting to start with machine learning.

Amazon Comprehend Medical V2: A New Version of the Natural Language Processing Service for Healthcare and Life Sciences

Introducing Amazon Comprehend Medical V2, a fresh iteration of the natural language processing service designed to extract insights from unstructured medical text. Enhancements in this version include heightened accuracy, performance, and scalability. Additionally, it introduces novel features like entity linking, negation detection, temporal expression extraction, and medication dosage identification. Users have the flexibility to personalize the service using their medical ontologies and vocabularies. Amazon Comprehend Medical V2 helps healthcare and life sciences organizations analyze clinical notes, medical reports, and research papers.

Amazon Rekognition Video Enhancements: New Features for Video Analysis and Content Moderation

Experience the capabilities of Amazon Rekognition Video, a dynamic service that thoroughly analyzes videos to identify objects, faces, emotions, activities, scenes, and more. The latest enhancements unveiled in August 2023 introduce a multitude of valuable features:

  • Celebrity Recognition: Attain high-precision celebrity identification within videos, bolstered by enhanced confidence scores.
  • Text Extraction: Effortlessly detect and extract text elements from videos, encompassing signs, logos, captions, and subtitles.
  • Content Moderation Labels: Safeguard your content by effortlessly identifying and filtering out inappropriate or offensive video segments—encompassing nudity, violence, drugs, alcohol, and weapons.
  • Video Enhancement: Elevate the quality of videos afflicted by low resolution or noise through super-resolution and advanced denoising techniques.

Amazon Lex V3: A New Version of the Conversational AI Service for Building Chatbots

Amazon Lex V3 is a new version of the conversational AI service that allows users to build chatbots for various use cases, such as customer service, booking, ordering, and more. The new version offers improved performance, scalability, and flexibility, as well as new features such as, users can now:

  • Multi-language support: Build chatbots that support multiple languages and locales.
  • Multi-turn dialog management: Design complex conversational flows with branching logic and context management.
  • Custom slot types: Define their slot types with custom values and synonyms.
  • Speech synthesis markup language (SSML) support: Control the speech output of their chatbots with SSML tags.

Amazon Kendra Enhancements: New Features for the Intelligent Search Service

Amazon Kendra is an intelligent search service that uses natural language understanding and machine learning to deliver relevant and accurate answers from various sources of information. In August 2023, Amazon announced several new features and enhancements for the service, such as, users can now:

  • Document ranking: Customize the ranking of documents based on their relevance and importance.
  • Query auto-completion: Get suggestions for completing their queries as they type.
  • Expansion of Query: Generate more query results by expanding them with synonyms and related terms.
  • Faceted search: Filter their results by category and attribute.
  • Document highlighting: See the relevant portions of documents highlighted in the search results.

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September 1, 2023 Artificial Intelligence (AI), AWS - August 2023, AWS - What's New No comments yet
Azure Container Apps: What's New - August 2023

Azure Container Apps: What’s New – August 2023

Azure Container Apps: What’s New and Why You Should Care

Azure Container Apps is a service that enables you to deploy and run containerized applications and microservices without managing the underlying infrastructure. It is a serverless hosting service that supports any container and any programming model. You can scale your apps in response to HTTP request events or run them as always-on background jobs.

This blog post will explore some of the latest features and enhancements announced for Azure Container Apps on August 30, 2023.

Workload Profiles Environment

Workload profiles are designed to optimize spend and performance for microservices by selecting either serverless Consumption compute or customized Dedicated compute. These determine the amount of compute and memory resources available to your apps in an Azure Container Apps environment.

You can have multiple workload profiles of varying sizes within the same Container Apps environment and select the optimal compute size for each of your applications’ resource requirements. This is ideal for developers when deploying a microservice solution.

A Consumption workload profile is available by default and provides serverless scale all the way to zero, and bills only for resources your apps use.

Dedicated workload profiles provide dedicated compute resources for your apps and are ideal for running apps requiring more compute and/or memory resources. You can select from a range of compute sizes and types up to 32 vCPUs and 256 GiB of memory. Apps running in these dedicated workload profiles use the new Dedicated pricing plan which bills per compute instance and provides better cost predictability.

Azure Container Apps Dedicated Plan

Dedicated plan is a new option to run your apps on dedicated compute resources, select from a range of compute sizes, and types up to 32 vCPUs and 256 GiB of memory. You can choose from general-purpose or memory-optimized workload profiles depending on your apps’ needs.

The Dedicated plan offers several benefits, such as:

  • Better cost predictability as you are billed per compute instance rather than per app.
  • Higher performance and scalability as you can allocate more resources to your apps.
  • Greater flexibility as you can mix and match Consumption and Dedicated plans within the same Container Apps environment.

Additional Networking Features

Azure Container Apps also supports additional networking features that enable you to configure your apps’ connectivity and security. These include:

  • User defined routes (UDR) – Specify custom routes for outbound traffic from your apps.
  • Smaller subnet sizes – Use smaller subnets for your Container Apps environments, reducing IP address consumption.
  • Network address translation (NAT) gateway – Use a single public IP address for outbound traffic from your apps.

Azure Container Apps Jobs

Jobs are a new feature that allow you to run containerized jobs on demand, on a schedule, or in response to events. These are ideal for scenarios such as data processing, batch processing, or scheduled tasks.

There are certain characteristics that can be attributed to jobs:

  • Run until completion or until a specified timeout.
  • Configured with retries, concurrency limits, and dependencies.
  • Triggered by HTTP requests, events from Event Grid or Service Bus, or cron expressions.
  • Access secrets from Azure Key Vault or environment variables.
  • Use any container image from any registry.

Conclusion

Azure Container Apps is a powerful and flexible service that enables you to run your containerized applications and microservices without having to worry about the infrastructure. With the latest features and enhancements, you can optimize your costs, performance, and scalability and run jobs for various scenarios.

If you want to try out Azure Container Apps, you can get started with the following resources:

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August 31, 2023 Artificial Intelligence (AI), Azure - August 2023, Azure - What's New No comments yet
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