AI

In December, we announced the preview availability for Amazon Bedrock Intelligent Prompt Routing, which provides a single serverless endpoint to efficiently route requests between different foundation models within the same model family. To do this, Amazon Bedrock Intelligent Prompt Routing dynamically predicts the response quality of each model for a request and routes the request to […]

This post is co-written with Saibal Samaddar, Tanushree Halder, and Lokesh Joshi from Infosys Consulting. Critical insights and expertise are concentrated among thought leaders and experts across the globe. Language barriers often hinder the distribution and comprehension of this knowledge during crucial encounters. Workshops, conferences, and training sessions serve as platforms for collaboration and knowledge

Yuewen Group is a global leader in online literature and IP operations. Through its overseas platform WebNovel, it has attracted about 260 million users in over 200 countries and regions, promoting Chinese web literature globally. The company also adapts quality web novels into films, animations for international markets, expanding the global influence of Chinese culture.

This post is co-written with Vikram Gundeti and Nate Folkert from Foursquare. Personalization is key to creating memorable experiences. Whether it’s recommending the perfect movie or suggesting a new restaurant, tailoring suggestions to individual preferences can make all the difference. But when it comes to food and activities, there’s more to consider than just personal

Large language models (LLMs) have become integral to numerous applications across industries, ranging from enhanced customer interactions to automated business processes. Deploying these models in real-world scenarios presents significant challenges, particularly in ensuring accuracy, fairness, relevance, and mitigating hallucinations. Thorough evaluation of the performance and outputs of these models is therefore critical to maintaining trust

Only four of the 21 robots in the race crossed the finish line, highlighting just how far humanoids are from keeping up with their real human counterparts.

When an AI model for code-editing company Cursor hallucinated a new rule, users revolted.

AI agents are revolutionizing how businesses enhance their operational capabilities and enterprise applications. By enabling natural language interactions, these agents provide customers with a streamlined, personalized experience. Amazon Bedrock Agents uses the capabilities of foundation models (FMs), combining them with APIs and data to process user requests, gather information, and execute specific tasks effectively. The

Retrieval Augmented Generation (RAG) enhances AI responses by combining the generative AI model’s capabilities with information from external data sources, rather than relying solely on the model’s built-in knowledge. In this post, we showcase the custom data connector capability in Amazon Bedrock Knowledge Bases that makes it straightforward to build RAG workflows with custom input