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Computer use is a breakthrough capability from Anthropic that allows foundation models (FMs) to visually perceive and interpret digital interfaces. This capability enables Anthropic’s Claude models to identify what’s on a screen, understand the context of UI elements, and recognize actions that should be performed such as clicking buttons, typing text, scrolling, and navigating between …

Getting started with computer use in Amazon Bedrock Agents Read More »

Organizations building and deploying AI applications, particularly those using large language models (LLMs) with Retrieval Augmented Generation (RAG) systems, face a significant challenge: how to evaluate AI outputs effectively throughout the application lifecycle. As these AI technologies become more sophisticated and widely adopted, maintaining consistent quality and performance becomes increasingly complex. Traditional AI evaluation approaches …

Evaluating RAG applications with Amazon Bedrock knowledge base evaluation Read More »

Google shares policy recommendations in response to OSTP’s request for information for the U.S. AI Action Plan.

This post was co-written with Vishal Singh, Data Engineering Leader at Data & Analytics team of GoDaddy Generative AI solutions have the potential to transform businesses by boosting productivity and improving customer experiences, and using large language models (LLMs) in these solutions has become increasingly popular. However, inference of LLMs as single model invocations or …

How GoDaddy built a category generation system at scale with batch inference for Amazon Bedrock Read More »

Open foundation models (FMs) allow organizations to build customized AI applications by fine-tuning for their specific domains or tasks, while retaining control over costs and deployments. However, deployment can be a significant portion of the effort, often requiring 30% of project time because engineers must carefully optimize instance types and configure serving parameters through careful …

Benchmarking customized models on Amazon Bedrock using LLMPerf and LiteLLM Read More »

The integration of generative AI agents into business processes is poised to accelerate as organizations recognize the untapped potential of these technologies. Advancements in multimodal artificial intelligence (AI), where agents can understand and generate not just text but also images, audio, and video, will further broaden their applications. This post will discuss agentic AI driven …

Creating asynchronous AI agents with Amazon Bedrock Read More »

The Qwen 2.5 multilingual large language models (LLMs) are a collection of pre-trained and instruction tuned generative models in 0.5B, 1.5B, 3B, 7B, 14B, 32B, and 72B (text in/text out and code out). The Qwen 2.5 fine tuned text-only models are optimized for multilingual dialogue use cases and outperform both previous generations of Qwen models, and …

How to run Qwen 2.5 on AWS AI chips using Hugging Face libraries Read More »

This post is cowritten with Harrison Hunter is the CTO and co-founder of MaestroQA. MaestroQA augments call center operations by empowering the quality assurance (QA) process and customer feedback analysis to increase customer satisfaction and drive operational efficiencies. They assist with operations such as QA reporting, coaching, workflow automations, and root cause analysis. In this …

Revolutionizing customer service: MaestroQA’s integration with Amazon Bedrock for actionable insight Read More »

DeepSeek-R1, developed by AI startup DeepSeek AI, is an advanced large language model (LLM) distinguished by its innovative, multi-stage training process. Instead of relying solely on traditional pre-training and fine-tuning, DeepSeek-R1 integrates reinforcement learning to achieve more refined outputs. The model employs a chain-of-thought (CoT) approach that systematically breaks down complex queries into clear, logical …

Optimize hosting DeepSeek-R1 distilled models with Hugging Face TGI on Amazon SageMaker AI Read More »

Compelling AI-generated images start with well-crafted prompts. In this follow-up to our Amazon Nova Canvas Prompt Engineering Guide, we showcase a curated gallery of visuals generated by Nova Canvas—categorized by real-world use cases—from marketing and product visualization to concept art and design exploration. Each image is paired with the prompt and parameters that generated it, …

Exploring creative possibilities: A visual guide to Amazon Nova Canvas Read More »