Facebook AI, AWS partner to release new PyTorch libraries

Facebook AI, AWS partner to release new PyTorch libraries

  • April 22, 2020
Table of Contents

Facebook AI, AWS partner to release new PyTorch libraries

Facebook AI and AWS have partnered to release new libraries that target high-performance PyTorch model deployment and large scale model training. As part of the broader PyTorch community, Facebook AI and AWS engineers have partnered to develop new libraries targeted at large-scale elastic and fault-tolerant model training and high-performance PyTorch model deployment. These libraries enable the community to efficiently productionize AI models at scale and push the state of the art on model exploration as model architectures continue to increase in size and complexity.

Today, we are sharing new details on these features. Available now, TorchServe is an easy-to-use, open source framework for deploying PyTorch models for high-performance inference. Cloud and environment agnostic, the framework’s library includes features such as multimodel serving, logging, metrics for monitoring, and the creation of RESTful endpoints for application integration.

With these features, TorchServe provides a clear path to deploying PyTorch models to production at scale. To get started, visit the AWS News blog for more information.

Source: facebook.com

Tags :
Share :
comments powered by Disqus

Related Posts

When machine learning packs an economic punch

When machine learning packs an economic punch

A new study co-authored by an MIT economist shows that improved translation software can significantly boost international trade online — a notable case of machine learning having a clear impact on economic activity. The research finds that after eBay improved its automatic translation program in 2014, commerce shot up by 10.9 percent among pairs of countries where people could use the new system. To put the results in perspective, he adds, consider that physical distance is, by itself, also a significant barrier to global commerce.

Read More
How Amazon is solving big-data challenges with data lakes

How Amazon is solving big-data challenges with data lakes

Back when Jeff Bezos filled orders in his garage and drove packages to the post office himself, crunching the numbers on costs, tracking inventory, and forecasting future demand was relatively simple. Fast-forward 25 years, Amazon’s retail business has more than 175 fulfillment centers (FC) worldwide with over 250,000 full-time associates shipping millions of items per day. Amazon’s worldwide financial operations team has the incredible task of tracking all of that data (think petabytes).

Read More
MIT CSAIL TextFooler Framework Tricks Leading NLP Systems

MIT CSAIL TextFooler Framework Tricks Leading NLP Systems

A team of researchers at the MIT Computer Science & Artificial Intelligence Lab (CSAIL) recently released a framework called TextFooler which successfully tricked state-of-the-art NLP models (such as BERT) into making incorrect predictions.

Read More