Google AI Blog Posted by Greg Corrado, Head of Health AI, Google Research, and Yossi Matias, VP, Engineering and Research, Google Research Medicine is an inherently multimodal discipline. When providing care, clinicians routinely interpret data from a wide range of modalities including medical images, clinical notes, lab tests, electronic health records, genomics, and more. Over […]Continue reading

Google AI Blog Posted by Cat Armato, Program Manager, Google Groups across Google actively pursue research in the field of machine learning (ML), ranging from theory and application. We build ML systems to solve deep scientific and engineering challenges in areas of language, music, visual processing, algorithm development, and more. We aim to build a […]Continue reading

Google AI Blog Posted by Sanjay Subramanian, PhD student, UC Berkeley, and Arsha Nagrani, Research Scientist, Google Research, Perception Team Visual question answering (VQA) is a machine learning task that requires a model to answer a question about an image or a set of images. Conventional VQA approaches need a large amount of labeled training […]Continue reading

Google AI Blog Posted by Natalia Ponomareva and Alex Kurakin, Staff Software Engineers, Google Research Large machine learning (ML) models are ubiquitous in modern applications: from spam filters to recommender systems and virtual assistants. These models achieve remarkable performance partially due to the abundance of available training data. However, these data can sometimes contain private […]Continue reading

Google AI Blog Posted by Jerry Wei, Student Researcher, and Denny Zhou, Principal Scientist, Google Research There have recently been tremendous advances in language models, partly because they can perform tasks with strong performance via in-context learning (ICL), a process whereby models are prompted with a few examples of input-label pairs before performing the task […]Continue reading

Google AI Blog Posted by Shekoofeh Azizi, Senior Research Scientist, and Laura Culp, Senior Research Engineer, Google Research Despite recent progress in the field of medical artificial intelligence (AI), most existing models are narrow, single-task systems that require large quantities of labeled data to train. Moreover, these models cannot be easily reused in new clinical […]Continue reading

Google AI Blog Posted by Malaya Jules, Program Manager, Google This week, the Conference on Human Factors in Computing Systems (CHI 2023) is being held in Hamburg, Germany. We are proud to be a Hero Sponsor of CHI 2023, a premier conference on human-computer interaction, where Google researchers contribute at all levels. This year we […]Continue reading

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