Tag: faang

In the past decade, we have seen Deep learning (DL) science adopted at a tremendous pace by AWS customers. The plentiful and jointly trained parameters of DL models have a large representational capacity that brought improvements in numerous customer use cases, including image and speech analysis, natural language processing (NLP), time series processing, and more. …

Read more “Reduce deep learning training time and cost with MosaicML Composer on AWS”

When two technologies converge, they can create something new and wonderful — like cellphones and browsers were fused to forge smartphones. Today, developers are applying AI’s ability to find patterns to massive graph databases that store information about relationships among data points of all sorts. Together they produce a powerful new tool called graph neural …

Read more “What Are Graph Neural Networks?”

An estimated 12 million people have fled their homes since Russia’s brutal invasion of Ukraine began, according to the United Nations — resulting in one of the largest humanitarian catastrophes since the Second World War. With countries in Europe and beyond stepping up to come to the assistance of Ukraine and those displaced, the UK government launched …

Read more “Ensuring the Resettling and Safeguarding of Refugees Fleeing the War in Ukraine”

Posted by Wenhao Yu, Research Scientist, Robotics at Google, and Kuang-Huei Lee, Research Engineer, Google Research, Brain team Evolution strategy (ES) is a family of optimization techniques inspired by the ideas of natural selection: a population of candidate solutions are usually evolved over generations to better adapt to an optimization objective. ES has been applied …

Read more “PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations”

Posted by Junjie Ke, Senior Software Engineer, and Feng Yang, Senior Staff Software Engineer, Google Research Understanding the aesthetic and technical quality of images is important for providing a better user visual experience. Image quality assessment (IQA) uses models to build a bridge between an image and a user’s subjective perception of its quality. In …

Read more “MUSIQ: Assessing Image Aesthetic and Technical Quality with Multi-scale Transformers”

Collecting and annotating image data is one of the most resource-intensive tasks on any computer vision project. It can take months at a time to fully collect, analyze, and experiment with image streams at the level you need in order to compete in the current marketplace. Even after you’ve successfully collected data, you still have …

Read more “Create synthetic data for computer vision pipelines on AWS”

Amazon SageMaker and SageMaker inference endpoints provide a capability of training and deploying your AI and machine learning (ML) workloads. With inference endpoints, you can deploy your models for real-time or batch inference. The endpoints support various types of ML models hosted using AWS Deep Learning Containers or your own containers with custom AI/ML algorithms. …

Read more “Enable CI/CD of multi-Region Amazon SageMaker endpoints”

There’s a lot of talk about the positive impact that machine learning can have on our lives as citizens and consumers. But did you know that it can reduce complexity and toil for cloud administrators? Google Cloud Active Assist uses data, intelligence, and ML to optimize the security, performance, and cost of your cloud environment. …

Read more “How ML-fueled recommendations help developers optimize security, price-performance, and carbon reduction”