Category: *Post Types

In this post, we demonstrate how to use large vision models (LVMs) for semantic video search using natural language and image queries. We introduce some use case-specific methods, such as temporal frame smoothing and clustering, to enhance the video search performance. Furthermore, we demonstrate the end-to-end functionality of this approach by using both asynchronous and real-time hosting options on Amazon SageMaker AI to perform video, image, and text processing using publicly available LVMs on the Hugging Face Model Hub. Finally, we use Amazon OpenSearch Serverless with its vector engine for low-latency semantic video search.

In this post, we discuss how an enterprise with multiple accounts can access a shared Amazon SageMaker HyperPod cluster for running their heterogenous workloads. We use SageMaker HyperPod task governance to enable this feature.

This post evaluates the key options for querying data using generative AI, discusses their strengths and limitations, and demonstrates why Text-to-SQL is the best choice for deterministic, schema-specific tasks. We show how to effectively use Text-to-SQL using Amazon Nova, a foundation model (FM) available in Amazon Bedrock, to derive precise and reliable answers from your data.

Radial is the largest 3PL fulfillment provider, also offering integrated payment, fraud detection, and omnichannel solutions to mid-market and enterprise brands. In this post, we share how Radial optimized the cost and performance of their fraud detection machine learning (ML) applications by modernizing their ML workflow using Amazon SageMaker.

In this post, we share how Impel enhances the automotive dealership customer experience with fine-tuned LLMs on SageMaker.

In this post, we show how climate tech startups are developing foundation models (FMs) that use extensive environmental datasets to tackle issues such as carbon capture, carbon-negative fuels, new materials design for microplastics destruction, and ecosystem preservation. These specialized models require advanced computational capabilities to process and analyze vast amounts of data effectively.

In this post, we’ll explore how to combine Amazon Bedrock prompt caching with Claude Code—a coding agent released by Anthropic that is now generally available. This powerful combination transforms your development workflow by delivering lightning-fast responses from reducing inference response latency, as well as lowering input token costs.

We’ve witnessed remarkable advances in model capabilities as generative AI companies have invested in developing their offerings. Language models such as Anthropic’s Claude Opus 4 & Sonnet 4 and Amazon Nova on Amazon Bedrock can reason, write, and generate responses with increasing sophistication. But even as these models grow more powerful, they can only work […]

The Danish humanitarian organization Bevar Ukraine has developed a comprehensive virtual generative AI-powered assistant called Victor, aimed at addressing the pressing needs of Ukrainian refugees integrating into Danish society. This post details our technical implementation using AWS services to create a scalable, multilingual AI assistant system that provides automated assistance while maintaining data security and GDPR compliance.

In this post, we explore how Noodoe uses AI and Amazon Bedrock to optimize EV charging operations. By integrating LLMs, Noodoe enhances station diagnostics, enables dynamic pricing, and delivers multilingual support. These innovations reduce downtime, maximize efficiency, and improve sustainability. Read on to discover how AI is transforming EV charging management.