AWS Machine Learning Blog

Category: Expert (400)

Improved ML model deployment using Amazon SageMaker Inference Recommender

Each machine learning (ML) system has a unique service level agreement (SLA) requirement with respect to latency, throughput, and cost metrics. With advancements in hardware design, a wide range of CPU- and GPU-based infrastructures are available to help you speed up inference performance. Also, you can build these ML systems with a combination of ML […]

Deploy large models at high performance using FasterTransformer on Amazon SageMaker

Sparked by the release of large AI models like AlexaTM, GPT, OpenChatKit, BLOOM, GPT-J, GPT-NeoX, FLAN-T5, OPT, Stable Diffusion, and ControlNet, the popularity of generative AI has seen a recent boom. Businesses are beginning to evaluate new cutting-edge applications of the technology in text, image, audio, and video generation that have the potential to revolutionize […]

Generate a counterfactual analysis of corn response to nitrogen with Amazon SageMaker JumpStart solutions

In his book The Book of Why, Judea Pearl advocates for teaching cause and effect principles to machines in order to enhance their intelligence. The accomplishments of deep learning are essentially just a type of curve fitting, whereas causality could be used to uncover interactions between the systems of the world under various constraints without […]

Zero-shot prompting for the Flan-T5 foundation model in Amazon SageMaker JumpStart

The size and complexity of large language models (LLMs) have exploded in the last few years. LLMs have demonstrated remarkable capabilities in learning the semantics of natural language and producing human-like responses. Many recent LLMs are fine-tuned with a powerful technique called instruction tuning, which helps the model perform new tasks or generate responses to […]

Enable fully homomorphic encryption with Amazon SageMaker endpoints for secure, real-time inferencing

This is joint post co-written by Leidos and AWS. Leidos is a FORTUNE 500 science and technology solutions leader working to address some of the world’s toughest challenges in the defense, intelligence, homeland security, civil, and healthcare markets. Leidos has partnered with AWS to develop an approach to privacy-preserving, confidential machine learning (ML) modeling where […]

Accelerate hyperparameter grid search for sentiment analysis with BERT models using Weights & Biases, Amazon EKS, and TorchElastic

Financial market participants are faced with an overload of information that influences their decisions, and sentiment analysis stands out as a useful tool to help separate out the relevant and meaningful facts and figures. However, the same piece of news can have a positive or negative impact on stock prices, which presents a challenge for […]

Achieve high performance at scale for model serving using Amazon SageMaker multi-model endpoints with GPU

Amazon SageMaker multi-model endpoints (MMEs) provide a scalable and cost-effective way to deploy a large number of machine learning (ML) models. It gives you the ability to deploy multiple ML models in a single serving container behind a single endpoint. From there, SageMaker manages loading and unloading the models and scaling resources on your behalf […]

Connecting Amazon Redshift and RStudio on Amazon SageMaker

Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) […]

New performance improvements in Amazon SageMaker model parallel library

Foundation models are large deep learning models trained on a vast quantity of data at scale. They can be further fine-tuned to perform a variety of downstream tasks and form the core backbone of enabling several AI applications. The most prominent category is large-language models (LLM), including auto-regressive models such as GPT variants trained to complete […]

Identify key insights from text documents through fine-tuning and HPO with Amazon SageMaker JumpStart

Organizations across industries such as retail, banking, finance, healthcare, manufacturing, and lending often have to deal with vast amounts of unstructured text documents coming from various sources, such as news, blogs, product reviews, customer support channels, and social media. These documents contain critical information that’s key to making important business decisions. As an organization grows, […]