Sept. 22, 2022, 9:33 p.m. | Andrew Helton (noreply@blogger.com)

Google AI Blog ai.googleblog.com

Posted by Jeremy Maitin-Shepard and Laramie Leavitt, Software Engineers, Connectomics at Google

Many exciting contemporary applications of computer science and machine learning (ML) manipulate multidimensional datasets that span a single large coordinate system, for example, weather modeling from atmospheric measurements over a spatial grid or medical imaging predictions from multi-channel image intensity values in a 2d or 3d scan. In these settings, even a single dataset may require terabytes or petabytes of data storage. Such datasets are also challenging to …

cloud computing datasets open source performance scalable storage

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Applied Scientist, Control Stack, AWS Center for Quantum Computing

@ Amazon.com | Pasadena, California, USA

Specialist Marketing with focus on ADAS/AD f/m/d

@ AVL | Graz, AT

Machine Learning Engineer, PhD Intern

@ Instacart | United States - Remote

Supervisor, Breast Imaging, Prostate Center, Ultrasound

@ University Health Network | Toronto, ON, Canada

Senior Manager of Data Science (Recommendation Science)

@ NBCUniversal | New York, NEW YORK, United States