Generative artificial intelligence (AI) foundation models (FMs) are gaining popularity with businesses due to their versatility and potential to address a variety of use cases. The true value of FMs is realized when they are adapted for domain specific data. Managing these models across the business and model lifecycle canContinue Reading
Harnessing the power of big data has become increasingly critical for businesses looking to gain a competitive edge. From deriving insights to powering generative artificial intelligence (AI)-driven applications, the ability to efficiently process and analyze large datasets is a vital capability. However, managing the complex infrastructure required for big dataContinue Reading
This post is co-written with Eliuth Triana, Abhishek Sawarkar, Jiahong Liu, Kshitiz Gupta, JR Morgan and Deepika Padmanabhan from NVIDIA. At the 2024 NVIDIA GTC conference, we announced support for NVIDIA NIM Inference Microservices in Amazon SageMaker Inference. This integration allows you to deploy industry-leading large language models (LLMs) on SageMakerContinue Reading
This post is co-written with Matt Marzillo from Snowflake. Today, we are excited to announce that the Snowflake Arctic Instruct model is available through Amazon SageMaker JumpStart to deploy and run inference. Snowflake Arctic is a family of enterprise-grade large language models (LLMs) built by Snowflake to cater to theContinue Reading
Building a deployment pipeline for generative artificial intelligence (AI) applications at scale is a formidable challenge because of the complexities and unique requirements of these systems. Generative AI models are constantly evolving, with new versions and updates released frequently. This makes managing and deploying these updates across a large-scale deploymentContinue Reading
Fine-tuning Meta Llama 3.1 models with Amazon SageMaker JumpStart enables developers to customize these publicly available foundation models (FMs). The Meta Llama 3.1 collection represents a significant advancement in the field of generative artificial intelligence (AI), offering a range of capabilities to create innovative applications. The Meta Llama 3.1 modelsContinue Reading
Amazon DataZone is a data management service that makes it quick and convenient to catalog, discover, share, and govern data stored in AWS, on-premises, and third-party sources. Amazon DataZone allows you to create and manage data zones, which are virtual data lakes that store and process your data, without theContinue Reading
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 writeContinue Reading
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 beContinue Reading
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 newContinue Reading
