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Favorite This post was co-written with Mohammad Jama, Yun Kim, and Barry Eom from Datadog. The emergence of generative AI agents in recent years has transformed the AI landscape, driven by advances in large language models (LLMs) and natural language processing (NLP). The focus is shifting from simple AI assistants
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Shared by AWS Machine Learning July 16, 2025
Favorite Amazon Bedrock Knowledge Bases has extended its vector store options by enabling support for Amazon OpenSearch Service managed clusters, further strengthening its capabilities as a fully managed Retrieval Augmented Generation (RAG) solution. This enhancement builds on the core functionality of Amazon Bedrock Knowledge Bases , which is designed to
Read More Shared by AWS Machine Learning July 16, 2025
Favorite AI agents will change how we all work and live. Our AWS CEO, Matt Garman, shared a vision of a technological shift as transformative as the advent of the internet. I’m energized by this vision because I’ve witnessed firsthand how these intelligent agent systems are already beginning to solve
Read More Shared by AWS Machine Learning July 16, 2025
Favorite This post is co-written with Mark Berkeland, Oscar Rodriguez and Marina Gerzon from Vonage. Voice-based technologies are transforming the way businesses engage with customers across customer support, virtual assistants, and intelligent agents. However, creating real-time, expressive, and highly responsive voice interfaces still requires navigating a complex stack of communication
Read More Shared by AWS Machine Learning July 16, 2025
Favorite When we launched the AWS Generative AI Innovation Center in 2023, we had one clear goal: help customers turn AI potential into real business value. We’ve already guided thousands of customers across industries from financial services to healthcare—including Formula 1, FOX, GovTech Singapore, Itaú Unibanco, Nasdaq, NFL, RyanAir, and
Read More Shared by AWS Machine Learning July 15, 2025
Favorite This post is co-written with Kshitiz Gupta, Wenhan Tan, Arun Raman, Jiahong Liu, and Eiluth Triana Isaza from NVIDIA. As large language models (LLMs) and generative AI applications become increasingly prevalent, the demand for efficient, scalable, and low-latency inference solutions has grown. Traditional inference systems often struggle to meet
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Favorite This post is co-written with Andrew Liu, Chelsea Isaac, Zoey Zhang, and Charlie Huang from NVIDIA. DGX Cloud on Amazon Web Services (AWS) represents a significant leap forward in democratizing access to high-performance AI infrastructure. By combining NVIDIA GPU expertise with AWS scalable cloud services, organizations can accelerate their
Read More Shared by AWS Machine Learning July 15, 2025
Favorite Data is your generative AI differentiator, and successful generative AI implementation depends on a robust data strategy incorporating a comprehensive data governance approach. Traditional data architectures often struggle to meet the unique demands of generative such as applications. An effective generative AI data strategy requires several key components like
Read More Shared by AWS Machine Learning July 14, 2025
Favorite This post is cowritten with Jimmy Cancilla from Rapid7. Organizations are managing increasingly distributed systems, which span on-premises infrastructure, cloud services, and edge devices. As systems become interconnected and exchange data, the potential pathways for exploitation multiply, and vulnerability management becomes critical to managing risk. Vulnerability management (VM) is
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Favorite Vehicle data is critical for original equipment manufacturers (OEMs) to drive continuous product innovation and performance improvements and to support new value-added services. Similarly, the increasing digitalization of vehicle architectures and adoption of software-configurable functions allow OEMs to add new features and capabilities efficiently. Sonatus’s Collector AI and Automator
Read More Shared by AWS Machine Learning July 14, 2025