AWS Machine Learning Blog

Stability AI builds foundation models on Amazon SageMaker

We’re thrilled to announce that Stability AI has selected AWS as its preferred cloud provider to power its state-of-the-art AI models for image, language, audio, video, and 3D content generation. Stability AI is a community-driven, open-source artificial intelligence (AI) company developing breakthrough technologies. With Amazon SageMaker, Stability AI will build AI models on compute clusters […]

Launch Amazon SageMaker Autopilot experiments directly from within Amazon SageMaker Pipelines to easily automate MLOps workflows

Amazon SageMaker Autopilot, a low-code machine learning (ML) service that automatically builds, trains, and tunes the best ML models based on tabular data, is now integrated with Amazon SageMaker Pipelines, the first purpose-built continuous integration and continuous delivery (CI/CD) service for ML. This enables the automation of an end-to-end flow of building ML models using […]

AI21 Jurassic-1 foundation model is now available on Amazon SageMaker

Today we are excited to announce that AI21 Jurassic-1 (J1) foundation models are available for customers using Amazon SageMaker. Jurassic-1 models are highly versatile, capable of both human-like text generation, as well as solving complex tasks such as question answering, text classification, and many others. You can easily try out this model and use it […]

Introducing AWS AI Service Cards: A new resource to enhance transparency and advance responsible AI

Artificial intelligence (AI) and machine learning (ML) are some of the most transformative technologies we will encounter in our generation—to tackle business and societal problems, improve customer experiences, and spur innovation. Along with the widespread use and growing scale of AI comes the recognition that we must all build responsibly. At AWS, we think responsible […]

AWS Unveils New AI Service Features and Enhancements at re:Invent 2022

Over the last 5 years, artificial intelligence (AI) and machine learning (ML) have evolved from a niche activity to a rapidly growing mainstream endeavor. Today, more than 100,000 customers across numerous industries rely on AWS for ML and AI initiatives that infuse AI into a broad range of business use cases to automate repetitive and […]

Deploy an MLOps solution that hosts your model endpoints in AWS Lambda

In 2019, Amazon co-founded the climate pledge. The pledge’s goal is to achieve net zero carbon by 2040. This is 10 years earlier than the Paris agreement outlines. Companies who sign up are committed to regular reporting, carbon elimination, and credible offsets. At the time of this writing, 377 companies have signed the climate pledge, […]

Introducing Amazon Kendra tabular search for HTML Documents

Amazon Kendra is an intelligent search service powered by machine learning (ML). Kendra reimagines enterprise search for your websites and applications so your employees and customers can easily find the content they’re looking for, even when it’s scattered across multiple locations and content repositories within your organization. Amazon Kendra users can now quickly find the […]

Enterprise administrative controls, simple sign-up, and expanded programming language support for Amazon CodeWhisperer

Amazon CodeWhisperer is a machine learning (ML)-powered service that helps improve developer productivity by generating code recommendations based on developers’ prior code and comments. Today, we are excited to announce that AWS administrators can now enable CodeWhisperer for their organization with single sign-in (SSO) authentication. Administrators can easily integrate CodeWhisperer with their existing workforce identity […]

Optimize hyperparameters with Amazon SageMaker Automatic Model Tuning

Machine learning (ML) models are taking the world by storm. Their performance relies on using the right training data and choosing the right model and algorithm. But it doesn’t end here. Typically, algorithms defer some design decisions to the ML practitioner to adopt for their specific data and task. These deferred design decisions manifest themselves […]

How JPMorgan Chase & Co. uses AWS DeepRacer events to drive global cloud adoption

This is a guest post by Stephen Carrad, Vice President at JP Morgan Chase & Co. JPMorgan & Chase Co. started its cloud journey four years ago, building the integrations required to deploy cloud-native applications into the cloud in a resilient and secure manner. In the first year, three applications tentatively dipped their toes into […]