Favorite Posted by AJ Piergiovanni and Anelia Angelova, Research Scientists, Google Research Vision-language foundational models are built on the premise of a single pre-training followed by subsequent adaptation to multiple downstream tasks. Two main and disjoint training scenarios are popular: a CLIP-style contrastive learning and next-token prediction. Contrastive learning trains

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Shared by Google AI Technology May 4, 2023

Favorite Posted by Joanne Truong, Student Researcher, and Wenhao Yu, Research Scientist, Robotics at Google Teaching mobile robots to navigate in complex outdoor environments is critical to real-world applications, such as delivery or search and rescue. However, this is also a challenging problem as the robot needs to perceive its

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Shared by Google AI Technology May 3, 2023

Favorite Checks takes the complexity out of compliance, using AI to help companies quickly discover, communicate and fix issues. View Original Source (blog.google/technology/ai/) Here.

Favorite Four new online interactive artworks from Google Arts & Culture Lab artists in residence View Original Source (blog.google/technology/ai/) Here.

Favorite Posted by Catherine Armato, Program Manager, Google The Eleventh International Conference on Learning Representations (ICLR 2023) is being held this week as a hybrid event in Kigali, Rwanda. We are proud to be a Diamond Sponsor of ICLR 2023, a premier conference on deep learning, where Google researchers contribute

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Shared by Google AI Technology May 1, 2023

Favorite Posted by Babak Behsaz, Software Engineer, and Andrew Carroll, Product Lead, Genomics The combination of the environment an individual experiences and their genetic predispositions determines the majority of their risk for various diseases. Large national efforts, such as the UK Biobank, have created large, public resources to better understand

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Shared by Google AI Technology April 27, 2023

Favorite 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

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Shared by Google AI Technology April 26, 2023

Favorite Posted by Yicheng Fan and Dana Alon, Software Engineers, Google Research Every byte and every operation matters when trying to build a faster model, especially if the model is to run on-device. Neural architecture search (NAS) algorithms design sophisticated model architectures by searching through a larger model-space than what

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Shared by Google AI Technology April 25, 2023

Favorite 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.

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Shared by Google AI Technology April 23, 2023

Favorite Posted by Ruofei Du, Interactive Perception & Graphics Lead, Google Augmented Reality, and Na Li, Tech Lead Manager, Google CoreML Recent deep learning advances have enabled a plethora of high-performance, real-time multimedia applications based on machine learning (ML), such as human body segmentation for video and teleconferencing, depth estimation

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Shared by Google AI Technology April 21, 2023