Category: Thought Leadership

With my blog post from June, I started a series that highlights the key factors that are driving customers to choose Amazon Bedrock. I explored how Bedrock enables customers to build a secure, compliant foundation for generative AI applications. Now I’d like to turn to a slightly more technical, but equally important differentiator for Bedrock—the multiple techniques that you can use to customize models and meet your specific business needs.

Generative artificial intelligence (AI) models have opened up new possibilities for automating and enhancing software development workflows. Specifically, the emergent capability for generative models to produce code based on natural language prompts has opened many doors to how developers and DevOps professionals approach their work and improve their efficiency. In this post, we provide an […]

GraphStorm is a low-code enterprise graph machine learning (GML) framework to build, train, and deploy graph ML solutions on complex enterprise-scale graphs in days instead of months. With GraphStorm, you can build solutions that directly take into account the structure of relationships or interactions between billions of entities, which are inherently embedded in most real-world […]

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Company earnings calls are crucial events that provide transparency into a company’s financial health and prospects. Earnings reports detail a firm’s financials over a specific period, including revenue, net income, earnings per share, balance sheet, and cash flow […]

Amazon Q Business is a fully managed, generative artificial intelligence (AI)-powered assistant that helps enterprises unlock the value of their data and knowledge. With Amazon Q, you can quickly find answers to questions, generate summaries and content, and complete tasks by using the information and expertise stored across your company’s various data sources and enterprise […]

As conversational artificial intelligence (AI) agents gain traction across industries, providing reliability and consistency is crucial for delivering seamless and trustworthy user experiences. However, the dynamic and conversational nature of these interactions makes traditional testing and evaluation methods challenging. Conversational AI agents also encompass multiple layers, from Retrieval Augmented Generation (RAG) to function-calling mechanisms that […]

Large language models (LLMs) have achieved remarkable success in various natural language processing (NLP) tasks, but they may not always generalize well to specific domains or tasks. You may need to customize an LLM to adapt to your unique use case, improving its performance on your specific dataset or task. You can customize the model […]

See how AWS is democratizing generative AI with innovations like Amazon Q Apps to make AI apps from prompts, Amazon Bedrock upgrades to leverage more data sources, new techniques to curtail hallucinations, and AI skills training.

Responsible AI is a longstanding commitment at Amazon. From the outset, we have prioritized responsible AI innovation by embedding safety, fairness, robustness, security, and privacy into our development processes and educating our employees. We strive to make our customers’ lives better while also establishing and implementing the necessary safeguards to help protect them. Our practical […]

Generative AI has revolutionized industries by creating content, from text and images to audio and code. Although it can unlock numerous possibilities, integrating generative AI into applications demands meticulous planning. Amazon Bedrock is a fully managed service that provides access to large language models (LLMs) and other foundation models (FMs) from leading AI companies through a […]