Amazon SageMaker is a cloud-based machine learning (ML) platform within the AWS ecosystem that offers developers a seamless and convenient way to build, train, and deploy ML models. Extensively used by data scientists and ML engineers across various industries, this robust tool provides high availability and uninterrupted access for itsContinue Reading
Today, we’re pleased to announce the general availability (GA) of Amazon Bedrock Custom Model Import. This feature empowers customers to seamlessly import and use their customized models alongside existing foundation models (FMs) through a single, unified API. Whether leveraging fine-tuned models like Meta Llama, Mistral Mixtral, and IBM Granite, orContinue Reading
Amazon SageMaker Studio is the latest web-based experience for running end-to-end machine learning (ML) workflows. SageMaker Studio offers a suite of integrated development environments (IDEs), which includes JupyterLab, Code Editor, as well as RStudio. Data scientists and ML engineers can spin up SageMaker Studio private and shared spaces, which areContinue Reading
Amazon Bedrock is a fully managed service that offers a choice of high-performing foundation models (FMs) from leading AI companies like AI21 Labs, Anthropic, Cohere, Meta, Mistral AI, Stability AI, and Amazon through a single API, along with a broad set of capabilities to build generative AI applications with security,Continue Reading
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,Continue Reading
With last month’s blog, I started a series of posts that highlight 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, butContinue Reading
Amazon SageMaker Studio provides a comprehensive suite of fully managed integrated development environments (IDEs) for machine learning (ML), including JupyterLab, Code Editor (based on Code-OSS), and RStudio. It supports all stages of ML development—from data preparation to deployment, and allows you to launch a preconfigured JupyterLab IDE for efficient codingContinue Reading
Traditionally, finding relevant information from documents has been a time-consuming and often frustrating process. Manually sifting through pages upon pages of text, searching for specific details, and synthesizing the information into coherent summaries can be a daunting task. This inefficiency not only hinders productivity but also increases the risk ofContinue Reading
Amazon Q is a new generative artificial intelligence (AI)-powered assistant designed for work that can be tailored to your business. Amazon Q can help you get fast, relevant answers to pressing questions, solve problems, generate content, and take actions using the data and expertise found in your company’s information repositoriesContinue Reading
Name entity recognition (NER) is the process of extracting information of interest, called entities, from structured or unstructured text. Manually identifying all mentions of specific types of information in documents is extremely time-consuming and labor-intensive. Some examples include extracting players and positions in an NFL game summary, products mentioned inContinue Reading
