Latest from MIT : 3 Questions: How AI image generators could help robots

AI image generators, which create fantastical sights at the intersection of dreams and reality, bubble up on every corner of the web. Their entertainment value is demonstrated by an ever-expanding treasure trove of whimsical and random images serving as indirect portals to the brains of human designers. A simple text prompt yields a nearly instantaneous…

Latest from Google AI – Natural Language Assessment: A New Framework to Promote Education

Posted by Kedem Snir, Software Engineer, and Gal Elidan, Senior Staff Research Scientist, Google Research Whether it’s a professional honing their skills or a child learning to read, coaches and educators play a key role in assessing the learner’s answer to a question in a given context and guiding them towards a goal. These interactions…

Latest from Google AI – Open Images V7 — Now Featuring Point Labels

Posted by Rodrigo Benenson, Research Scientist, Google Research Open Images is a computer vision dataset covering ~9 million images with labels spanning thousands of object categories. Researchers around the world use Open Images to train and evaluate computer vision models. Since the initial release of Open Images in 2016, which included image-level labels covering 6k…

Latest from MIT Tech Review – Machine learning could vastly speed up the search for new metals

Machine learning could help develop new types of metals with useful properties, such as resistance to extreme temperatures and rust, according to new research. This could be useful in a range of sectors—for example, metals that perform well at lower temperatures could improve spacecraft, while metals that resist corrosion could be used for boats and…

Latest from Google AI – PI-ARS: Accelerating Evolution-Learned Visual-Locomotion with Predictive Information Representations

Posted by Wenhao Yu, Research Scientist, Robotics at Google, and Kuang-Huei Lee, Research Engineer, Google Research, Brain team Evolution strategy (ES) is a family of optimization techniques inspired by the ideas of natural selection: a population of candidate solutions are usually evolved over generations to better adapt to an optimization objective. ES has been applied…

Latest from Google AI – MUSIQ: Assessing Image Aesthetic and Technical Quality with Multi-scale Transformers

Posted by Junjie Ke, Senior Software Engineer, and Feng Yang, Senior Staff Software Engineer, Google Research Understanding the aesthetic and technical quality of images is important for providing a better user visual experience. Image quality assessment (IQA) uses models to build a bridge between an image and a user’s subjective perception of its quality. In…

Latest from MIT Tech Review – A bias bounty for AI will help to catch unfair algorithms faster

AI systems are deployed all the time, but it can take months or even years until it becomes clear whether, and how, they’re biased.  The stakes are often sky-high: unfair AI systems can cause innocent people to be arrested, and they can deny people housing, jobs, and basic services.   Today a group of AI and…

Latest from Google AI – Do Modern ImageNet Classifiers Accurately Predict Perceptual Similarity?

Posted by Manoj Kumar, Research Engineer, and Ekin Dogus Cubuk, Research Scientist, Google Research The task of determining the similarity between images is an open problem in computer vision and is crucial for evaluating the realism of machine-generated images. Though there are a number of straightforward methods of estimating image similarity (e.g., low-level metrics that…