Blog_dumb

This post is co-written with Kristina Olesova, Zdenko Esetok, and Selimcan akar from Accenture. In today’s data-driven world, organizations often face the challenge of extracting structured information from unstructured PDF documents. These PDFs can contain a myriad of elements, such as images, tables, headers, and text formatted in various styles, making it difficult to parse …

Accelerate performance using a custom chunking mechanism with Amazon Bedrock Read More »

Amazon SageMaker Data Wrangler provides a visual interface to streamline and accelerate data preparation for machine learning (ML), which is often the most time-consuming and tedious task in ML projects. Amazon SageMaker Canvas is a low-code no-code visual interface to build and deploy ML models without the need to write code. Based on customers’ feedback, …

Migrate Amazon SageMaker Data Wrangler flows to Amazon SageMaker Canvas for faster data preparation Read More »

Amazon SageMaker Ground Truth significantly reduces the cost and time required for labeling data by integrating human annotators with machine learning to automate the labeling process. You can use SageMaker Ground Truth to create labeling jobs, which are workflows where data objects (such as images, videos, or documents) need to be annotated by human workers. These …

Use IP-restricted presigned URLs to enhance security in Amazon SageMaker Ground Truth Read More »

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 …

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

Here’s how our bioacoustic foundation model, Health Acoustic Representations (HeAR), may help improve health outcomes for people across India.

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 …

Cohere Rerank 3 Nimble now generally available on Amazon SageMaker JumpStart Read More »

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, …

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

Whether you’re a new student, a thriving startup, or the largest enterprise, you have financial constraints, and you need to know what you’re spending, where it’s being spent, and how to plan for the future. Nobody wants a surprise when it comes to the bill, and this is where Microsoft Cost Management comes in. We’re always looking …

Microsoft Cost Management updates—July 2024 Read More »

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 …

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