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The new NC H100 v5 Virtual Machine (VM) Series, in preview, is built on the latest NVL variant of the NVIDIA Hopper 100 (H100), which will offer greater memory per GPU. The new VM series will provide customers with greater performance, reliability and efficiency for mid-range AI training and generative AI inferencing. By maintaining more memory per GPU in the VM, customers increase data processing efficiency and enhance overall workload performance. Microsoft Copilot Studio: AI transformation begins by tapping into an organization’s unique data and workflows. Microsoft Copilot Studio is a low-code tool designed to customize Microsoft Copilot for Microsoft 365 by integrating business-critical data and build custom copilots for internal or external use. Copilot Studio works with connectors, plugins and GPTs, allowing IT teams to steer Copilot to the best data sources for specific queries. Several new updates have been made throughout Azure offerings, giving users the ability to better integrate their applications, data and processes. OD18: Microsoft makes endpoint management and protection easy – when it's consolidated across platfo... Blog: Microsoft Azure AI, data, and application innovations help turn your AI ambitions into reality
Meanwhile, the Arm-based Azure Cobalt 100 CPU is designed for general-purpose computing workloads on the Microsoft Cloud. It is a 64-bit processor with 128 computing cores and is 40% more power efficient than existing Arm-based chips deployed in Azure. Both deliver a throughput of 12.5 gigabytes per second and will be available early in 2024. Chaos Studio offers customers the opportunity to intentionally disrupt their applications to uncover reliability issues and strategize for issue prevention before they impact users. For example, Chaos Studio enables users to assess how applications respond to real-world disruptions like network delays, unexpected storage failures, expired secrets or even complete datacenter outages. Templates in Chaos Studio allow customers, in a matter of minutes, to test the resilience of their Azure resources by providing a set of pre-filled experiments based on common outage scenarios. Dynamic targets functionality allows users to select experiment targets by using Keyword Query Language (KQL) queries, rather than static list selection, allowing more sophisticated fault injection scenarios to be created. Azure Container Apps is adding new features to make it easier to deploy code to the cloud and run AI workloads. Vector database add-ins: Three of the most popular open-source vector database variants, Qdrant, Milvus and Weaviate, are now available in preview as add-ins for developers to get started in a fast and affordable way.GPT-4 updates: Azure OpenAI Service has also rolled out updates to GPT-4, including the ability for fine-tuning. Fine-tuning will allow organizations to customize the AI model to better suit their specific needs. It’s akin to tailoring a suit to fit perfectly, but in the world of AI. Updates to GPT-4 are in preview. Copilot Studio : This is Microsoft, enabling anyone with low code skills to create customized AI assistants. Its 1,000+ pre-built connectors extend data integration plugins for various use cases. The Mv3 platform offers improved resilience against common failures in memory, storage and networking, resulting in minimal interruptions to mission-critical workloads. Mv3 delivers up to 30 percent faster SAP HANA ( High-performance ANalytic Appliance) data load times for SAP OLAP (Online Analytical Processing) workloads compared to the previous generation Mv2, and up to 15 percent higher performance per core for SAP OLTP (Online Transaction Processing) workloads over Mv2. A new task-optimization summarization capability in Azure AI Language, powered by large language models (GPT-3.5-Turbo, GPT-4, Z-Code++ and more).
Named entity recognition, document translation and summarization in containers will allow government agencies and industries, such as financial services and healthcare, with strict data residency requirements to run AI services on their own infrastructure. Introducing new task-optimized summarization capabilities powered by fine-tuned large-language model Skilling labs are deep technical skilling classroom environments supported by Microsoft experts with formal instructions and lab-like learning experiences. The in-person skilling labs will be available on a first-come, first-served basis.= Microsoft previously announced Microsoft Applied Skills, a new credential that allows individuals to prove they have specific skills needed to implement projects aligned to business scenarios. Continue your learning journey after Ignite with more skilling sessions! On October 24-27, join us for four days of Microsoft Technical Takeoff: Windows and Microsoft Intune.It’s an exciting time for Azure IoT and the digital transformation in physical operations! Join us at Ignite 2023 to learnwhat the teams have been up to lately (Hint: we think you’re gonna like it ). Don’t miss out, Ignite is the best place to get up to speed on the latest information and technologies from Azure IoT and Edge platforms and connect with product teams. This offering, now in preview, will feature a “One Microsoft” approach from cloud to edge to digitally transform physical operations. Microsoft is standardizing cloud-to-edge architecture for digital solutions in physical operations with industry standards and open-source approaches. What has been your approach to Bring Your Own PC and is it evolving based on learnings from the pandemic? Does Windows 365 change the equation? What is missing from the Microsoft suite of solutions to help you achieve your goals. Model catalog will empower users to discover, evaluate, fine-tune and deploy foundation models from renowned providers, such as Hugging Face, Meta and OpenAI, facilitating developers in selecting the optimal foundation models for their specific use cases. Within the model catalog, users can find a comprehensive comparison view for benchmarking metrics of multiple foundation models, allowing users to self-educate and make informed decisions about the suitability of models and datasets for their specific use cases. Model catalog has expanded to include new models like Code Llama, Stable Diffusion and OpenAI’s CLIP (Contrastive Language-Image Pretraining) models. Model catalog will be generally available soon and is available in preview in Azure AI Studio, broadening its availability and applicability. Microsoft is the Copilot company, and we believe in the future there will be a Copilot for everyone and for everything you do. Some of our Copilot-related announcements and updates include:
New file system performance and economics with Azure Native Qumulo Scalable File Service: Azure Native Qumulo (ANQ) V2 Scalable File Service transforms the cloud file service by combining the performance and elasticity of the cloud with enterprise features and universal compatibility of on-premises file systems.
Model-as-a-Service through inference APIs and hosted-fine-tuning, coming soon in preview, will enable developers and machine learning professionals to easily integrate foundation models such as Llama 2 from Meta, upcoming premium models from Mistral, and Jais from G42 as an API endpoint to their applications and fine-tune models without having to manage the underlying GPU infrastructure. Microsoft’s ecosystem approach includes longstanding partnerships with industry leaders to provide customers with choice in performance, efficiency and cost for AI inferencing, training and general compute. Are you optimistic about Microsoft’s AI undertakings? Please share with us on LinkedIn Opens a new window , X Opens a new window , or Facebook Opens a new window . We’d love to hear from you!
Florence foundation model: Trained with billions of text-image pairs and integrated as cost-effective, production-ready computer vision services in Azure AI Vision, this improved feature enables developers to create cutting-edge, market-ready, responsible computer vision applications across various industries. Florence foundation model is generally available. Essential Tools for 2024 Planning: Copilot in Viva Goals, Goals in Viva Engage and Planner Updates (CP) Extensibility support on Linux is now in preview. Previously available on Windows, it will allow Linux web apps to take advantage of third-party software services on Azure and connect to Azure Native ISV services more easily.Passing an interactive, lab-based assessment that takes candidates through a series of scenario-based tasks in products like Microsoft Azure or Power Platform. The lab assessment is accessible on-demand directly from Microsoft Learn. SCOM Managed Instance is now generally available. Since preview, SCOM Managed Instance has added multiple capabilities such as the integration of SCOM alerts with that of Azure Monitor, the ability to send integrated alerts to IT service management tools, the ability to view service health from the Azure portal and an enhanced onboarding experience.
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