AWS Machine Learning Blog
Category: Artificial Intelligence
Announcing availability of Inf1 instances in Amazon SageMaker for high performance and cost-effective machine learning inference
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. Tens of thousands of customers, including Intuit, Voodoo, ADP, Cerner, Dow Jones, and Thompson Reuters, use Amazon SageMaker to remove the heavy lifting from each step of the […]
Deploying PyTorch models for inference at scale using TorchServe
Many services you interact with today rely on machine learning (ML). From online search and product recommendations to speech recognition and language translation, these services need ML models to serve predictions. As ML finds its way into even more services, you face the challenge of taking the results of your hard work and deploying the […]
Using Amazon Textract with Amazon Augmented AI for processing critical documents
Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, medical, legal, and real estate. For example, millions of mortgage applications and hundreds of millions of tax forms are processed each year. Documents are often unstructured, which means the content’s location or format may vary between two otherwise […]
Smarter FAQ bots with Amazon Kendra
We often have questions when making a choice about a product or service. When was the last time you found yourself at the IT help desk at work? You probably had questions like “What time does the IT Help Desk open?” or “Can I get a temporary machine while you repair my laptop?” Quick and […]
Translating your website or application automatically with Amazon Translate in your CI/CD pipeline
AWS allows you to deploy websites and applications globally in minutes. This means that both large enterprises and individual developers can reach users, and thus potential customers, all over the world. However, to provide the best experience, you should not only serve content close to your customers, but also make that content available in their […]
AWS IQ waives fees until June 30, 2020, to help you stand up and scale remote work initiatives
The recent post Working from Home? Here’s How AWS Can Help shared several ways AWS is helping you set up and scale remote work and work-from-home initiatives. Getting these solutions set up is sometimes best—and achieved more quickly—with expert help. You can get the help you need with AWS IQ, which connects you to AWS […]
Spanish Newscaster speaking style now available in Amazon Polly
Amazon Polly is launching its first non-English Newscaster speaking style voice, Lupe. This female US Spanish voice is the third Newscaster speaking style voice in Amazon Polly, following the launches of US English voices Matthew and Joanna. All Newscaster voices are made possible by the Neural Text-to-Speech (NTTS) technology of Amazon Polly. News content is […]
Reduce inference costs on Amazon EC2 for PyTorch models with Amazon Elastic Inference
Note: Amazon Elastic Inference is no longer available. Please see Amazon SageMaker for similar capabilities. You can now use Amazon Elastic Inference to accelerate inference and reduce inference costs for PyTorch models in both Amazon SageMaker and Amazon EC2. PyTorch is a popular deep learning framework that uses dynamic computational graphs. This allows you to […]
Amazon Translate added to Memsource Translate, Memsource’s machine translation management feature
This is a guest post from Memsource. In their own words, “By leading the industry in AI-powered translation technology, we make localization easier, faster, and more cost-effective.” Memsource and Amazon Translate are strengthening their partnership. You can now use Amazon Translate with Memsource Translate, Memsource’s machine translation (MT) management feature. Many Memsource users share a […]
Bring your own model for Amazon SageMaker labeling workflows with active learning
With Amazon SageMaker Ground Truth, you can easily and inexpensively build accurately labeled machine learning (ML) datasets. To decrease labeling costs, SageMaker Ground Truth uses active learning to differentiate between data objects (like images or documents) that are difficult and easy to label. Difficult data objects are sent to human workers to be annotated and […]