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Vector embeddings have become essential for modern Retrieval Augmented Generation (RAG) applications, but organizations face significant cost challenges as they scale. As knowledge bases grow and require more granular embeddings, […]

Amazon Bedrock offers model customization capabilities for customers to tailor versions of foundation models (FMs) to their specific needs through features such as fine-tuning and distillation. Today, we’re announcing the

Organizations are adopting large language models (LLMs), such as DeepSeek R1, to transform business processes, enhance customer experiences, and drive innovation at unprecedented speed. However, standalone LLMs have key limitations

This post was written with Ilan Geller, Kamal Mannar, Debasmita Ghosh, and Nakul Aggarwal of Accenture. Video highlights offer a powerful way to boost audience engagement and extend content value

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

For Google AI Pro and AI Ultra subscribers, AI Mode in Search now features the ability to use Gemini 2.5 Pro and do deeper research for you. ​ 

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.

Doctors, developers and researchers gathered in Paris to prototype new medical solutions using Google’s AI models. ​ 

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

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