Global trade patterns are being redefined. As tariffs reshape international commerce, enterprises face a once-in-a-generation inflection point. To successfully navigate the rapidly evolving supply chains, dynamic pricing structures, and ever-shifting regulations, they will need to reevaluate their longstanding business practices in real-time or risk falling behind. This post explores how enterprises can harness Palantir to address …
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. …
Read more “Accelerating insurance policy reviews with generative AI: Verisk’s Mozart companion”
AI Hypercomputer is a fully integrated supercomputing architecture for AI workloads – and it’s easier to use than you think. In this blog, we break down four common use cases, including reference architectures and tutorials, representing just a few of the many ways you can use AI Hypercomputer today. Short on time? Here’s a quick …
Read more “Guide: Our top four AI Hypercomputer use cases, reference architectures and tutorials”
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 …
Read more “Build a Multi-Agent System with LangGraph and Mistral on AWS”
Today, we’re announcing built-in performance monitoring and alerts for Gemini and other managed foundation models – right from Vertex AI’s homepage. Monitoring the performance of generative AI models is crucial when building lightning-fast, reliable, and scalable applications. But understanding the performance of these models has historically had a steep learning curve: in the past, you …
Read more “Introducing built-in performance monitoring for Vertex AI Model Garden”
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 …
Read more “Innovating at speed: BMW’s generative AI solution for cloud incident analysis”
As AI use increases, security remains a top concern, and we often hear that organizations are worried about risks that can come with rapid adoption. Google Cloud is committed to helping our customers confidently build and deploy AI in a secure, compliant, and private manner. Today, we’re introducing a new solution that can help you …
Read more “Announcing AI Protection: Security for the AI era”
Part 3: System Strategies and Architecture By: Varun Khaitan With special thanks to my stunning colleagues: Mallika Rao, Esmir Mesic, Hugo Marques This blog post is a continuation of Part 2, where we cleared the ambiguity around title launch observability at Netflix. In this installment, we will explore the strategies, tools, and methodologies that were employed to …
Building cloud infrastructure based on proven best practices promotes security, reliability and cost efficiency. To achieve these goals, the AWS Well-Architected Framework provides comprehensive guidance for building and improving cloud architectures. As systems scale, conducting thorough AWS Well-Architected Framework Reviews (WAFRs) becomes even more crucial, offering deeper insights and strategic value to help organizations optimize …
Read more “Accelerate AWS Well-Architected reviews with Generative AI”
Increasingly, organizations across industries are turning to generative AI foundation models (FMs) to enhance their applications. To achieve optimal performance for specific use cases, customers are adopting and adapting these FMs to their unique domain requirements. This need for customization has become even more pronounced with the emergence of new models, such as those released …
Read more “Customize DeepSeek-R1 distilled models using Amazon SageMaker HyperPod recipes – Part 1”