GenAI News

Enterprises are increasingly shifting from relying solely on large, general-purpose language models to developing specialized large language models (LLMs) fine-tuned on their own proprietary...

My first attempt at building a travel planning agent looked exactly like most early prototypes: one big model, a few tools, and a long...

Today, we’re announcing structured outputs on Amazon Bedrock—a capability that fundamentally transforms how you can obtain validated JSON responses from foundation models through constrained...

Training and deploying large AI models requires advanced distributed computing capabilities, but managing these distributed systems shouldn’t be complex for data scientists and machine...

In the post Evaluating generative AI models with Amazon Nova LLM-as-a-Judge on Amazon SageMaker AI, we introduced the Amazon Nova LLM-as-a-judge capability, which is...

Embedding models power many modern applications—from semantic search and Retrieval-Augmented Generation (RAG) to recommendation systems and content understanding. However, selecting an embedding model requires...

This is a guest post co-written with David Meredith and Josh Zacharias from Associa. Associa, North America’s largest community management company, oversees approximately 7.5 million...

Marketing teams face major challenges creating campaigns in today’s digital environment. They must navigate through complex data analytics and rapidly changing consumer preferences to...

This post is cowritten with James Luo from BGL. Data analysis is emerging as a high-impact use case for AI agents. According to Anthropic’s 2026...

Building production-ready AI agents requires careful planning and execution across the entire development lifecycle. The difference between a prototype that impresses in a demo...