AI

Unlock the power of structured data for enterprises using natural language with Amazon Q Business

One of the most common applications of generative artificial intelligence (AI) and large language models (LLMs) in an enterprise environment is answering questions based on the enterprise’s knowledge corpus. Pre-trained foundation models (FMs) excel at natural language understanding (NLU) tasks, including summarization, text generation, and question answering across a wide range of topics. However, they […]

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Cohere Rerank 3 Nimble now generally available on Amazon SageMaker JumpStart

The Cohere Rerank 3 Nimble foundation model (FM) is now generally available in Amazon SageMaker JumpStart. This model is the newest FM in Cohere’s Rerank model series, built to enhance enterprise search and Retrieval Augmented Generation (RAG) systems. In this post, we discuss the benefits and capabilities of this new model with some examples. Overview

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3 Questions: How to prove humanity online

As artificial intelligence agents become more advanced, it could become increasingly difficult to distinguish between AI-powered users and real humans on the internet. In a new white paper, researchers from MIT, OpenAI, Microsoft, and other tech companies and academic institutions propose the use of personhood credentials, a verification technique that enables someone to prove they

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Perform generative AI-powered data prep and no-code ML over any size of data using Amazon SageMaker Canvas

Amazon SageMaker Canvas now empowers enterprises to harness the full potential of their data by enabling support of petabyte-scale datasets. Starting today, you can interactively prepare large datasets, create end-to-end data flows, and invoke automated machine learning (AutoML) experiments on petabytes of data—a substantial leap from the previous 5 GB limit. With over 50 connectors,

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Delight your customers with great conversational experiences via QnABot, a generative AI chatbot

QnABot on AWS (an AWS Solution) now provides access to Amazon Bedrock foundational models (FMs) and Knowledge Bases for Amazon Bedrock, a fully managed end-to-end Retrieval Augmented Generation (RAG) workflow. You can now provide contextual information from your private data sources that can be used to create rich, contextual, conversational experiences. The advent of generative

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