Google AI Technology

Why we focus on AI (and to what end) Today we published a paper outlining why we pursue AI. Read on for a preview, or visit ai.google to see the paper in full.

Responsible AI: Looking back at 2022, and to the futureLooking back at Google’s 2022 progress in principled AI innovation and ahead to 2023 and beyond.

A recap of Google’s top announcements and initiatives in 2022.

Posted by Jinsung Yoon and Sercan O. Arik, Research Scientists, Google Research, Cloud AI Team Analysis of Electronic Health Records (EHR) has a tremendous potential for enhancing patient care, quantitatively […]

Posted by Pritish Kamath and Pasin Manurangsi, Research Scientists, Google Research Differential privacy (DP) is an approach that enables data analytics and machine learning (ML) with a mathematical guarantee on […]

Posted by Tal Schuster, Research Scientist, Google Research Language models (LMs) are the driving force behind many recent breakthroughs in natural language processing. Models like T5, LaMDA, GPT-3, and PaLM […]

Posted by Quan Wang, Senior Staff Software Engineer, and Fan Zhang, Staff Software Engineer, Google In 2019 we launched Recorder, an audio recording app for Pixel phones that helps users create, manage, and edit […]

Posted Keerthana Gopalakrishnan and Kanishka Rao, Google Research, Robotics at Google Major recent advances in multiple subfields of machine learning (ML) research, such as computer vision and natural language […]

A look at how Transformers are helping robots become more useful.

Posted by Alexis Morvan and Trond Andersen, Research Scientists, Google Quantum AI When quantum computers were first proposed, they were hoped to be a way to better understand the quantum world. With a so-called […]

Posted by Krishna Giri Narra, Software Engineer, Google, and Chiyuan Zhang, Research Scientist, Google Research Ad technology providers widely use machine learning (ML) models to predict and present users with […]

Posted by Malaya Jules, Program Manager, Google This week, the premier conference on Empirical Methods in Natural Language Processing (EMNLP 2022) is being held in Abu Dhabi, United Arab Emirates. We are proud to […]

Google’s Startups for Sustainable Development program supports impact-driven startups who are building a more sustainable future.

Posted by Katja Filippova, Research Scientist, and Sebastian Ebert, Software Engineer, Google Research, Brain team Modern machine learning models that learn to solve a task by going through many examples can […]

Posted by Corey Lynch, Research Scientist, and Ayzaan Wahid, Research Engineer, Robotics at Google A grand vision in robot learning, going back to the SHRDLU experiments in the late 1960s, is that of helpful […]

Posted by Alexander Zlokapa, Student Researcher, and Hartmut Neven, VP of Engineering, Quantum AI Team Wormholes — wrinkles in the fabric of spacetime that connect two disparate locations — may seem like the stu […]

Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team In recent years, language models (LMs) have become more prominent in natural language processing (NLP) research and are also […]

Posted by Cat Armato, Program Manager, Google This week marks the beginning of the 36th annual Conference on Neural Information Processing Systems (NeurIPS 2022), the biggest machine learning conference of the […]

Our partnership with iCAD Inc. marks the first time we are licensing our mammography AI model in clinical practice.

Posted by Mohammad Saleh, Software Engineer, Google Research, Brain Team, and Yinan Wang, Software Engineer, Google Workspace Information overload is a significant challenge for many organizations and […]