Tag: Amazon Quantum Solutions Lab

Using AWS advanced computing, the Australian Red Cross Lifeblood achieved theoretical cost reductions of up to 46% by optimizing nurse scheduling – key to meeting rising blood donation demand affordably.

Researchers made breakthroughs in distributing, storing, & processing quantum data across a network in Boston. Discover the tech that might power a future secure quantum internet.

Want the details on using quantum optimization for finance? New research from Amazon QSL and JPMorgan Chase maps out pathways to quantum advantage. Their post analyzes problem classes inspired by real-world use cases, setting the stage for impactful future experiments.

Check out our latest blog to learn how we implemented a cost-effective development cycle for training a hybrid quantum-classical algorithm using Amazon Braket and hyperparameter optimization.

Discover how Airbus and BMW Group are harnessing quantum computing to tackle industry challenges. Join the Airbus-BMW Group Quantum Mobility Quest and help shape the future of transportation.

In this post we’ll walk you through some key takeaways from a paper published today by scientists from Goldman Sachs and AWS describing a quantum algorithm for portfolio optimization.

BMW sponsors PhD students to research novel approaches to computational challenges. Today we’ll show you how they bridge the gap between academia and industry, to solve some of the hardest problems in industry using Bayesian protocols for quantum optimization problems.

This blog post is an introduction to HPC on AWS for quantum computing researchers who are seeking to compare their quantum or hybrid algorithms against classical calculations.

In this post we show how physics-inspired graph neural networks can be used to solve the notoriously hard graph-coloring problem, at scale. This can help in an huge number of familiar resource-allocation problems from sports to rental cars.

Introduction The problem of robot motion planning is pervasive across many industry verticals, including (for example) automotive, manufacturing, and logistics. In the automotive industry, robotic path optimization problems can be found across the value chain in body shops, paint shops, assembly, and logistics, among others [1]. Typically, hundreds of robots operate in a single plant […]