Blog_dumb

Community Benchmarks on Kaggle lets the community build, share and run custom evaluations for AI models. ​ 

Over the past year, we’ve witnessed how creators globally have been using our AI models and tools to share their stories with the world. That’s why we launched the AI Fi… ​ 

The adoption and implementation of generative AI inference has increased with organizations building more operational workloads that use AI capabilities in production at scale. To help customers achieve the scale of their generative AI applications, Amazon Bedrock offers cross-Region inference (CRIS) profiles, a powerful feature organizations can use to seamlessly distribute inference processing across multiple …

Securing Amazon Bedrock cross-Region inference: Geographic and global Read More »

Today, we’re introducing an enhanced version of Veo 3.1 “Ingredients to Video.” ​ 

This post is co-written with Sunaina Kavi, AI/ML Product Manager at Omada Health. Omada Health, a longtime innovator in virtual healthcare delivery, launched a new nutrition experience in 2025, featuring OmadaSpark, an AI agent trained with robust clinical input that delivers real-time motivational interviewing and nutrition education. It was built on AWS. OmadaSpark was designed …

How Omada Health scaled patient care by fine-tuning Llama models on Amazon SageMaker AI Read More »

Amazon Nova Multimodal Embeddings processes text, documents, images, video, and audio through a single model architecture. Available through Amazon Bedrock, the model converts different input modalities into numerical embeddings within the same vector space, supporting direct similarity calculations regardless of content type. We developed this unified model to reduce the need for separate embedding models, …

Crossmodal search with Amazon Nova Multimodal Embeddings Read More »

Foundation models (FMs) and large language models (LLMs) have been rapidly scaling, often doubling in parameter count within months, leading to significant improvements in language understanding and generative capabilities. This rapid growth comes with steep costs: inference now requires enormous memory capacity, high-performance GPUs, and substantial energy consumption. This trend is evident in the open …

Accelerating LLM inference with post-training weight and activation using AWQ and GPTQ on Amazon SageMaker AI Read More »

This post is cowritten by Mike Koźmiński from Beekeeper. Large Language Models (LLMs) are evolving rapidly, making it difficult for organizations to select the best model for each specific use case, optimize prompts for quality and cost, adapt to changing model capabilities, and personalize responses for different users. Choosing the “right” LLM and prompt isn’t …

How Beekeeper optimized user personalization with Amazon Bedrock Read More »

This post is co-written by Instituto de Ciência e Tecnologia Itaú (ICTi) and AWS. Sentiment analysis has grown increasingly important in modern enterprises, providing insights into customer opinions, satisfaction levels, and potential frustrations. As interactions occur largely through text (such as social media, chat applications, and ecommerce reviews) or voice (such as call centers and …

Sentiment Analysis with Text and Audio Using AWS Generative AI Services: Approaches, Challenges, and Solutions Read More »

This post is co-written by TrueLook and AWS. TrueLook is a construction camera and jobsite intelligence company that provides real-time visibility into construction projects. Its platform combines high-resolution time-lapse cameras, live video streaming, and AI-powered insights to help teams monitor progress, improve accountability, and reduce risk across the entire project lifecycle. TrueLook used Amazon SageMaker …

Architecting TrueLook’s AI-powered construction safety system on Amazon SageMaker AI Read More »