AWS Machine Learning Blog

This blog post was last reviewed or updated April, 2022 with database schema updates. We’re excited to announce dynamic filters in Amazon Personalize, which allow you to apply business rules to your recommendations on the fly, without any extra cost. Dynamic filters create better user experiences by allowing you to tailor your business rules for […]

At AWS, our mission is to enable developers and businesses with no prior machine learning (ML) expertise to easily build sophisticated, scalable, ML-powered applications with our AI services. Today, we’re excited to announce that Amazon Lex and Amazon Polly are expanding language support. You can build ML-powered applications that fit the language preferences of your […]

December 2020 Update – The Wildcard and warmup races are complete and the Round 1 Knockouts are officially underway, streaming live on Twitch. In this round, competitors participate in a brand-new live racing format on the AWS DeepRacer console. Racers submit their best models from anywhere in the world and attempt to navigate the track, […]

September 2021: This blog has been updated to include three recently launched accuracy metrics in Amazon Forecast and the ability to select an accuracy metric to optimize AutoML. We’re excited to announce that you can now measure the accuracy of your forecasting model to optimize the trade-offs between under-forecasting and over-forecasting costs, giving you flexibility in […]

Processing incoming documents such as contracts and agreements is often an arduous task. The typical workflow for reviewing signed contracts involves loading, reading, and extracting contractual terms from agreements, which requires hours of manual effort and intensive labor. At AWS Finance and Global Business Services (AWS FGBS), this process typically takes more than 150 employee […]

Amazon Polly is launching a new Australian English voice, Olivia. Amazon Polly turns text into lifelike speech, allowing you to build speech-enabled products. Building upon the existing Australian English Standard voices, Nicole and Russell, Olivia is the first Australian English voice in Amazon Polly powered by the Neural Text-to-Speech (NTTS) technology. The NTTS voices in […]

October 2022: This post was reviewed and updated to include updates from Amazon SageMaker’s recently released SourceIdentity feature and renaming of AWS SSO to IAM Identity Center. Amazon SageMaker is a fully managed service that provides every machine learning (ML) developer and data scientist with the ability to build, train, and deploy ML models quickly. […]

Amazon Polly turns text into lifelike speech, allowing you to create applications that talk and build entirely new categories of speech-enabled products. We’re thrilled to announce the launch of a brand-new, British Newscaster speaking style voice: Amy. The speaking style mimics a formal and authoritative British newsreader. This Newscaster voice is the result of our […]

AWS is excited to announce the winner of the AWS DeepComposer Chartbusters The Sounds of Science Challenge, Sungin Lee. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). In June, we launched Chartbusters, a monthly global competition during which developers use AWS DeepComposer to create original compositions and compete to […]

Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). SageMaker Studio lets data scientists spin up Studio notebooks to explore data, build models, launch Amazon SageMaker training jobs, and deploy hosted endpoints. Studio notebooks come with a set of pre-built images, which consist of the Amazon SageMaker Python SDK […]