AWS Machine Learning Blog

Category: Artificial Intelligence

Managing multi-topic conversation flows with Amazon Lex Session API checkpoints

In daily conversations, you often jump back and forth between multiple topics. For example, when discussing a home improvement project related to new windows and curtains, you might have questions like, “How about closing out on curtain styles and then revisiting colors?” When AWS launched Amazon Lex Session API, you learned how to address such […]

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Verifying and adjusting your data labels to create higher quality training datasets with Amazon SageMaker Ground Truth

Building a highly accurate training dataset for your machine learning (ML) algorithm is an iterative process. It is common to review and continuously adjust your labels until you are satisfied that the labels accurately represent the ground truth, or what is directly observable in the real world. ML practitioners often built custom systems to review […]

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Amazon Textract is now HIPAA eligible

Today, Amazon Web Services (AWS) announced that Amazon Textract, a machine learning service that quickly and easily extracts text and data from forms and tables in scanned documents, is now eligible for healthcare and life science workloads that require HIPAA compliance. This launch builds upon the existing portfolio of AWS artificial intelligence services that are […]

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Managing conversation flow with a fallback intent on Amazon Lex

Ever been stumped by a question? Imagine you’re in a business review going over weekly numbers and someone asks, “What about expenses?” Your response might be, “I don’t know. I wasn’t prepared to have that discussion right now.” Bots aren’t fortunate enough to have the same comprehension capabilities, so how should they respond when they […]

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Generating searchable PDFs from scanned documents automatically with Amazon Textract

Amazon Textract is a machine learning service that makes it easy to extract text and data from virtually any document. Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables. This allows you to use Amazon Textract to instantly “read” virtually any type […]

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Transcribe speech to text in real time using Amazon Transcribe with WebSocket

Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to applications. In November 2018, we added streaming transcriptions over HTTP/2 to Amazon Transcribe. This enabled users to pass a live audio stream to our service and, in return, receive text transcripts in real time. We […]

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Using Amazon Polly in Windows Applications

AWS offers a vast array of services that allow developers to build applications in the cloud. At the same time, Windows desktop applications can take advantage of these services as well. Today, we are releasing Amazon Polly for Windows, an open-source engine that allows users to take advantage of Amazon Polly voices in SAPI-compliant Windows […]

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Build your ML skills with AWS Machine Learning on Coursera

Machine learning (ML) is one of the fastest growing areas in technology and a highly sought after skillset in today’s job market. Today, I am excited to announce a new education course, built in collaboration with Coursera, to help you build your ML skills: Getting started with AWS Machine Learning. You can access the course […]

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Build, test, and deploy your Amazon Sagemaker inference models to AWS Lambda

Amazon SageMaker is a fully managed platform that enables developers and data scientists to quickly and easily build, train, and deploy machine learning (ML) models at any scale. When you deploy an ML model, Amazon SageMaker leverages ML hosting instances to host the model and provides an API endpoint to provide inferences. It may also […]

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Multiregion serverless distributed training with AWS Batch and Amazon SageMaker

Creating a global footprint and access to scale are one of the many best practices at AWS. By creating architectures that take advantage of that scale and also efficient data utilization (in both performance and cost), you can start to see how important access is at scale. For example, within autonomous vehicles (AV) development, data is geographically […]

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