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In 2010, we embarked on a journey to build a cloud platform that would empower organizations globally. In February, we celebrated 15 years of bringing Azure innovation to the world, and today, we celebrate Microsoft again being recognized as a leader in Forrester’s recently published report, The Forrester Wave™: Public Cloud Platforms, Q4 2024. We …

Microsoft named a leader in The Forrester Wave: Public Cloud Platforms, 2024 Read More »

This post is co-authored with Sundeep Sardana, Malolan Raman, Joseph Lam, Maitri Shah and Vaibhav Singh from Verisk. Verisk (Nasdaq: VRSK) is a leading strategic data analytics and technology partner to the global insurance industry, empowering clients to strengthen operating efficiency, improve underwriting and claims outcomes, combat fraud, and make informed decisions about global risks. …

Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion Read More »

Today, Amazon Web Services (AWS) announced the general availability of Amazon Bedrock Knowledge Bases GraphRAG (GraphRAG), a capability in Amazon Bedrock Knowledge Bases that enhances Retrieval-Augmented Generation (RAG) with graph data in Amazon Neptune Analytics. This capability enhances responses from generative AI applications by automatically creating embeddings for semantic search and generating a graph of …

Announcing general availability of Amazon Bedrock Knowledge Bases GraphRAG with Amazon Neptune Analytics Read More »

Learn more about the first-ever Google for Startups Accelerator: AI for Energy.

Agents are revolutionizing the landscape of generative AI, serving as the bridge between large language models (LLMs) and real-world applications. These intelligent, autonomous systems are poised to become the cornerstone of AI adoption across industries, heralding a new era of human-AI collaboration and problem-solving. By using the power of LLMs and combining them with specialized …

Build a Multi-Agent System with LangGraph and Mistral on AWS Read More »

In the rapidly evolving landscape of artificial intelligence, Retrieval Augmented Generation (RAG) has emerged as a game-changer, revolutionizing how Foundation Models (FMs) interact with organization-specific data. As businesses increasingly rely on AI-powered solutions, the need for accurate, context-aware, and tailored responses has never been more critical. Enter the powerful trio of Amazon Bedrock, LlamaIndex, and …

Evaluate RAG responses with Amazon Bedrock, LlamaIndex and RAGAS Read More »

High service quality is crucial to the reliability of the Azure platform and its hundreds of services. Continuously monitoring the platform service health enables our teams to promptly detect and mitigate incidents that may impact our customers. In addition to automated triggers in our system that react when thresholds are breached and customer-report incidents, we …

Optimizing incident management with AIOps using the Triangle System Read More »

This post was co-authored with Johann Wildgruber, Dr. Jens Kohl, Thilo Bindel, and Luisa-Sophie Gloger from BMW Group. The BMW Group—headquartered in Munich, Germany—is a vehicle manufacturer with more than 154,000 employees, and 30 production and assembly facilities worldwide as well as research and development locations across 17 countries. Today, the BMW Group (BMW) is the …

Innovating at speed: BMW’s generative AI solution for cloud incident analysis Read More »

Time series forecasting is critical for decision-making across industries. From predicting traffic flow to sales forecasting, accurate predictions enable organizations to make informed decisions, mitigate risks, and allocate resources efficiently. However, traditional machine learning approaches often require extensive data-specific tuning and model customization, resulting in lengthy and resource-heavy development. Enter Chronos, a cutting-edge family of …

Time series forecasting with LLM-based foundation models and scalable AIOps on AWS Read More »

Generative AI question-answering applications are pushing the boundaries of enterprise productivity. These assistants can be powered by various backend architectures including Retrieval Augmented Generation (RAG), agentic workflows, fine-tuned large language models (LLMs), or a combination of these techniques. However, building and deploying trustworthy AI assistants requires a robust ground truth and evaluation framework. Ground truth …

Ground truth generation and review best practices for evaluating generative AI question-answering with FMEval Read More »