Posted by William J. Huggins, Research Scientist, Google Quantum AI The intersection between the computational difficulty and practical importance of quantum chemistry challenges run on quantum computers has long been a focus for Google Quantum AI. We’ve experimentally simulated simple models of chemical bonding, high-temperature superconductivity, nanowires, and even exotic phases of matter such as…
Andrea Henshall, a retired major in the U.S. Air Force and current MIT PhD student, has completed seven tours of combat, two years of aerial circus performance, and three higher education degrees (so far). But throughout each step of her journey, all roads seemed to point to MIT. Currently working on her doctoral degree with…
Posted by Arsha Nagrani and Chen Sun, Research Scientists, Google Research, Perception Team People interact with the world through multiple sensory streams (e.g., we see objects, hear sounds, read words, feel textures and taste flavors), combining information and forming associations between senses. As real-world data consists of various signals that co-occur, such as video frames…
Huge amounts of data are needed to train machine-learning models to perform image classification tasks, such as identifying damage in satellite photos following a natural disaster. However, these data are not always easy to come by. Datasets may cost millions of dollars to generate, if usable data exist in the first place, and even the…
Metal-organic frameworks, a class of materials with porous molecular structures, have a variety of possible applications, such as capturing harmful gases and catalyzing chemical reactions. Made of metal atoms linked by organic molecules, they can be configured in hundreds of thousands of different ways. To help researchers sift through all of the possible metal-organic framework…
Posted by Emily Masten, Software Engineer, Google Research, Operations Research Team Airlines around the world are exploring several tactics to meet aggressive CO2 commitments set by the International Civil Aviation Organization (ICAO). This effort has been emphasized in Europe, where aviation accounts for 13.9% of the transportation industry’s carbon emissions. The largest push comes from…
Running a healthcare system is like juggling bees. Millions of moving pieces—from mobile clinics to testing kits—need to be in the right places at the right time. That’s even harder to do in countries with limited resources and endemic disease. But getting stuff where it’s needed is a problem big companies deal with all the…
Posted by Bryan Perozzi, Research Scientist and Qi Zhu, Research Intern, Google Research Graph Neural Networks (GNNs) are powerful tools for leveraging graph-structured data in machine learning. Graphs are flexible data structures that can model many different kinds of relationships and have been used in diverse applications like traffic prediction, rumor and fake news detection,…
Summary In the healthcare domain, there is a lot of real-time data that is generated. This data needs to be monitored to generate predictions and alerts for healthcare professionals. Manual monitoring of such data is difficult. In this code pattern, we add AI-based predictions and automate the monitoring of healthcare data. To demonstrate IBM Cloud…
Posted by Zizhao Zhang and Guanhang Wu, Software Engineers, Google Research, Cloud AI Team Video recognition is a core task in computer vision with applications from video content analysis to action recognition. However, training models for video recognition often requires untrimmed videos to be manually annotated, which can be prohibitively time consuming. In order to…