AWSML

Recent developments in deep learning have led to increasingly large models such as GPT-3, BLOOM, and OPT, some of which are already in excess of 100 billion parameters. Although larger models tend to be more powerful, training such models requires significant computational resources. Even with the use of advanced distributed training libraries like FSDP and … Read more

Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning. They can process various types of input data, including tabular, … Read more

Amazon Forecast is a fully managed service that uses machine learning (ML) to generate highly accurate forecasts, without requiring any prior ML experience. Forecast is applicable in a wide variety of use cases, including estimating supply and demand for inventory management, travel demand forecasting, workforce planning, and computing cloud infrastructure usage. You can use Forecast … Read more

This post is co-authored by Tristan Miller from Best Egg. Best Egg is a leading financial confidence platform that provides lending products and resources focused on helping people feel more confident as they manage their everyday finances. Since March 2014, Best Egg has delivered $22 billion in consumer personal loans with strong credit performance, welcomed … Read more

Today, gaining customer loyalty cannot be a one-off thing. A brand needs a focused and integrated plan to retain its best customers—put simply, it needs a customer loyalty program. Earn and burn programs are one of the main paradigms. A typical earn and burn program rewards customers after a certain number of visits or spend. … Read more

Model explainability refers to the process of relating the prediction of a machine learning (ML) model to the input feature values of an instance in humanly understandable terms. This field is often referred to as explainable artificial intelligence (XAI). Amazon SageMaker Clarify is a feature of Amazon SageMaker that enables data scientists and ML engineers … Read more

In November 2022, we announced that AWS customers can generate images from text with Stable Diffusion models in Amazon SageMaker JumpStart. Today, we announce a new feature that lets you upscale images (resize images without losing quality) with Stable Diffusion models in JumpStart. An image that is low resolution, blurry, and pixelated can be converted … Read more

This is a guest post by Sudip Roy, Manager of Technical Staff at Cohere. It’s an exciting day for the development community. Cohere’s state-of-the-art language AI is now available through Amazon SageMaker. This makes it easier for developers to deploy Cohere’s pre-trained generation language model to Amazon SageMaker, an end-to-end machine learning (ML) service. Developers, … Read more

Amazon SageMaker Studio is a fully integrated development environment (IDE) for machine learning (ML) partly based on JupyterLab 3. Studio provides a web-based interface to interactively perform ML development tasks required to prepare data and build, train, and deploy ML models. In Studio, you can load data, adjust ML models, move in between steps to adjust experiments, … Read more

Amazon SageMaker JumpStart is the Machine Learning (ML) hub of SageMaker providing pre-trained, publicly available models for a wide range of problem types to help you get started with machine learning. Understanding customer behavior is top of mind for every business today. Gaining insights into why and how customers buy can help grow revenue. Customer churn is … Read more

This post is co-written with Jennifer Bergstrom, Sr. Technical Director, ParsonsX. Parsons Corporation (NYSE:PSN) is a leading disruptive technology company in critical infrastructure, national defense, space, intelligence, and security markets providing solutions across the globe to help make the world safer, healthier, and more connected. Parsons provides services and capabilities across cybersecurity, missile defense, space ground … Read more

This post is co-written by Ramdev Wudali and Kiran Mantripragada from Thomson Reuters. In 1992, Thomson Reuters (TR) released its first AI legal research service, WIN (Westlaw Is Natural), an innovation at the time, as most search engines only supported Boolean terms and connectors. Since then, TR has achieved many more milestones as its AI … Read more

Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a centralized data repository. Because they’re in a highly regulated domain, HCLS partners and … Read more

This blog post is co-written with Chaoyang He and Salman Avestimehr from FedML. Analyzing real-world healthcare and life sciences (HCLS) data poses several practical challenges, such as distributed data silos, lack of sufficient data at any single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a … Read more

This post was co-authored with Mark Lott, Distinguished Technical Architect, Salesforce, Inc. Enterprises that operate globally are experiencing challenges sourcing customer support professionals with multi-lingual experience. This process can be cost-prohibitive and difficult to scale, leading many enterprises to only support English for chats. Using human interpreters for translation support is expensive, and infeasible since … Read more

This is guest post by Andy Whittle, Principal Platform Engineer – Application & Reliability Frameworks at The Very Group. At The Very Group, which operates digital retailer Very, security is a top priority in handling data for millions of customers. Part of how The Very Group secures and tracks business operations is through activity logging … Read more

This post is co-authored by Marios Skevofylakas, Jason Ramchandani and Haykaz Aramyan from Refinitiv, An LSEG Business. Financial service providers often need to identify relevant news, analyze it, extract insights, and take actions in real time, like trading specific instruments (such as commodities, shares, funds) based on additional information or context of the news item. … Read more

Amazon SageMaker is a fully managed machine learning (ML) service. With SageMaker, data scientists and developers can quickly and easily build and train ML models, and then directly deploy them into a production-ready hosted environment. It provides an integrated Jupyter authoring notebook instance for easy access to your data sources for exploration and analysis, so … Read more

If you’ve had the opportunity to build a search application for unstructured data (i.e., wiki, informational web sites, self-service help pages, internal documentation, etc.) using open source or commercial-off-the-shelf search engines, then you’re probably familiar with the inherent accuracy challenges involved in getting relevant search results. The intended meaning of both query and document can … Read more

Machine learning (ML) applications are complex to deploy and often require the ability to hyper-scale, and have ultra-low latency requirements and stringent cost budgets. Use cases such as fraud detection, product recommendations, and traffic prediction are examples where milliseconds matter and are critical for business success. Strict service level agreements (SLAs) need to be met, … Read more

Amazon Lex is an AWS service for building conversational interfaces into any application using voice and text, enabling businesses to add sophisticated, natural language chatbots across different channels. Amazon Lex uses machine learning (ML) to understand natural language (normal conversational text and speech). In this post, we go through a set of best practices for … Read more

This three-part series demonstrates how to use graph neural networks (GNNs) and Amazon Neptune to generate movie recommendations using the IMDb and Box Office Mojo Movies/TV/OTT licensable data package, which provides a wide range of entertainment metadata, including over 1 billion user ratings; credits for more than 11 million cast and crew members; 9 million … Read more

The recently published IDC MarketScape: Asia/Pacific (Excluding Japan) AI Life-Cycle Software Tools and Platforms 2022 Vendor Assessment positions AWS in the Leaders category. This was the first and only APEJ-specific analyst evaluation focused on AI life-cycle software from IDC. The vendors evaluated for this MarketScape offer various software tools needed to support end-to-end machine learning … Read more

This post is co-written by Hesham Fahim from Thomson Reuters. Thomson Reuters (TR) is one of the world’s most trusted information organizations for businesses and professionals. It provides companies with the intelligence, technology, and human expertise they need to find trusted answers, enabling them to make better decisions more quickly. TR’s customers span across the … Read more

Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) … Read more

The last decade of the Industry 4.0 revolution has shown the value and importance of machine learning (ML) across verticals and environments, with more impact on manufacturing than possibly any other application. Organizations implementing a more automated, reliable, and cost-effective Operational Technology (OT) strategy have led the way, recognizing the benefits of ML in predicting … Read more

Documents are a primary tool for record keeping, communication, collaboration, and transactions across many industries, including financial, medical, legal, and real estate. The millions of mortgage applications and hundreds of millions of W2 tax forms processed each year are just a few examples of such documents. Critical business data remains unlocked in unstructured documents such … Read more

Customer service interactions often contain personally identifiable information (PII) such as names, phone numbers, and dates of birth. As organizations incorporate machine learning (ML) and analytics into their applications, using this data can provide insights on how to create more seamless customer experiences. However, the presence of PII information often restricts the use of this … Read more

Launched at AWS re:Invent 2021, Amazon SageMaker Ground Truth Plus helps you create high-quality training datasets by removing the undifferentiated heavy lifting associated with building data labeling applications and managing the labeling workforce. All you do is share data along with labeling requirements, and Ground Truth Plus sets up and manages your data labeling workflow … Read more