Tag: ai/ml

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 “Leveraging artificial intelligence and machine learning at Parsons with AWS DeepRacer”

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 “How Thomson Reuters built an AI platform using Amazon SageMaker to accelerate delivery of ML projects”

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 a single site for rare events, regulatory guidelines that prohibit data sharing, infrastructure requirement, and cost incurred in creating a …

Read more “Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 2”

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 “Federated Learning on AWS with FedML: Health analytics without sharing sensitive data – Part 1”

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 “Multilingual customer support translation made easy on Salesforce Service Cloud using Amazon Translate”

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 “Redacting PII data at The Very Group with Amazon Comprehend”

Understanding protein geometries is essential to understanding a protein’s function, and thus essential to a range of disruptive research projects, from creating more sustainable materials to developing more effective treatments to diseases. For this reason, the “protein-folding problem” ranked for decades among biological science’s grand challenges—until Google’s DeepMind developed AlphaFold.   Widely hailed as a breakthrough …

Read more “RAD Lab AlphaFold module for researchers”

Using a pretrained AI model from NVIDIA, startup Evozyne created two proteins with significant potential in healthcare and clean energy. A joint paper released today describes the process and the biological building blocks it produced. One aims to cure a congenital disease, another is designed to consume carbon dioxide to reduce global warming. Initial results …

Read more “NVIDIA, Evozyne Create Generative AI Model for Proteins”