Amazon recently announced the launch of its second-generation model for text embeddings, Amazon Titan Text Embeddings V2. Text embeddings are essential for various natural language processing (NLP) applications such as knowledge bases, language models, and recommendation systems. The Amazon Titan V2 model is optimized to support customer use cases such as Retrieval Augmented Generation (RAG),…
The article discusses the challenges faced by many customers in managing diverse data sources and presents a solution for developing a chatbot capable of answering queries using both documentation and databases. The chatbot leverages Amazon's fully-managed service, Amazon Bedrock, which uses high-performing Foundation Models (FMs) from leading AI companies, dealing with structured and unstructured data.
Amazon…
Amazon has introduced a generative AI call summarization feature to its Transcribe Call Analytics product. The new feature means customer service representatives no longer need to manually chronicle their interactions with customers, which can often account for up to a third of total call time.
The additional capability will reduce customer waiting times and improve efficiencies…
Conversational AI assistants are able to provide quick, accurate responses via intelligent routing of questions to the most suitable AI functions. One example of this is Amazon Bedrock, a fully managed service that offers a selection of high-performance base models from leading AI companies via a single API. This post examines two primary techniques for…
Generative artificial intelligence (AI) is advancing rapidly, and organizations are exploring its potential applications. To ensure long-term success of AI-powered systems, it is essential to align them with well-established architectural principles. In this sense, the Amazon Web Services (AWS) Well-Architected Framework offers valuable guidelines for designing and operating reliable, secure, efficient, and cost-effective systems in…