Artificial Intelligence
Expanding Amazon Lex conversational experiences with US Spanish and British English
Amazon Lex provides the power of automatic speech recognition (ASR) for converting speech to text, along with natural language understanding (NLU) for recognizing user intents. This combination allows you to develop sophisticated conversational interfaces using both voice and text for chatbots, IVR bots, and voicebots. This week, we’re announcing Amazon Lex support for British English […]
Gaining insights into winning football strategies using machine learning
University of Illinois, Urbana Champaign (UIUC) has partnered with the Amazon Machine Learning Solutions Lab to help UIUC football coaches prepare for games more efficiently and improve their odds of winning. Previously, coaches prepared for games by creating a game planning sheet that only featured types of plays for a certain down and distance, and […]
Detecting and redacting PII using Amazon Comprehend
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning (ML) to find insights and relationships like people, places, sentiments, and topics in unstructured text. You can now use Amazon Comprehend ML capabilities to detect and redact personally identifiable information (PII) in customer emails, support tickets, product reviews, social media, and more. […]
Build alerting and human review for images using Amazon Rekognition and Amazon A2I
The volume of user-generated content (UGC) and third-party content has been increasing substantially in sectors like social media, ecommerce, online advertising, and photo sharing. However, such content needs to be reviewed to ensure that end-users aren’t exposed to inappropriate or offensive material, such as nudity, violence, adult products, or disturbing images. Today, some companies simply […]
Activity detection on a live video stream with Amazon SageMaker
Live video streams are continuously generated across industries including media and entertainment, retail, and many more. Live events like sports, music, news, and other special events are broadcast for viewers on TV and other online streaming platforms. AWS customers increasingly rely on machine learning (ML) to generate actionable insights in real time and deliver an […]
Automating the analysis of multi-speaker audio files using Amazon Transcribe and Amazon Athena
In an effort to drive customer service improvements, many companies record the phone conversations between their customers and call center representatives. These call recordings are typically stored as audio files and processed to uncover insights such as customer sentiment, product or service issues, and agent effectiveness. To provide an accurate analysis of these audio files, […]
Learn from the winner of the AWS DeepComposer Chartbusters Spin the Model Challenge
Support for AWS DeepComposer will be ending soon. Please see Support for AWS DeepComposer ending soon for more details. AWS is excited to announce the winner of the second AWS DeepComposer Chartbusters challenge, Lena Taupier. AWS DeepComposer gives developers a creative way to get started with machine learning (ML). In June, we launched the Chartbusters […]
Amazon Personalize now available in EU (Frankfurt) Region
Amazon Personalize is a machine learning (ML) service that enables you to personalize your website, app, ads, emails, and more with private, custom ML models that you can create with no prior ML experience. We’re excited to announce the general availability of Amazon Personalize in the EU (Frankfurt) Region. You can use Amazon Personalize to […]
Reducing training time with Apache MXNet and Horovod on Amazon SageMaker
Amazon SageMaker is a fully managed service that provides every developer and data scientist with the ability to build, train, and deploy machine learning (ML) models quickly. Amazon SageMaker removes the heavy lifting from each step of the ML process to make it easier to develop high-quality models. As datasets continue to increase in size, […]
Using the Amazon SageMaker Studio Image Build CLI to build container images from your Studio JupyterLab notebooks
April 2025: This post was reviewed and updated for accuracy. The Amazon SageMaker Studio Image Build convenience package allows data scientists and developers to easily build custom container images from your Studio JupyterLab notebooks via CLI. The CLI eliminates the need to manually set up and connect to Docker build environments for building container images […]