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…
Posted by Shaina Mehta, Program Manager, Google Google is proud to be a Platinum Sponsor of the European Conference on Computer Vision (ECCV 2022), a premier forum for the dissemination of research in computer vision and machine learning (ML). This year, ECCV 2022 will be held as a hybrid event, in person in Tel Aviv,…
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…
Ask a smart home device for the weather forecast, and it takes several seconds for the device to respond. One reason this latency occurs is because connected devices don’t have enough memory or power to store and run the enormous machine-learning models needed for the device to understand what a user is asking of it….
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…
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…
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…
“I am quitting because I’m tired,” Alex Hanna wrote on February 2, her last day on Google’s Ethical AI team. She felt that the company, and the tech industry as a whole, did little to promote diversity or mitigate the harms its products had caused to marginalized people. “In a word, tech has a whiteness…
Posted by Avi Singh, Research Scientist, and Laura Graesser, Research Engineer, Robotics at Google Robot learning has been applied to a wide range of challenging real world tasks, including dexterous manipulation, legged locomotion, and grasping. It is less common to see robot learning applied to dynamic, high-acceleration tasks requiring tight-loop human-robot interactions, such as table…
A recently passed law in New York City requires audits for bias in AI-based hiring systems. And for good reason. AI systems fail frequently, and bias is often to blame. A recent sampling of headlines features sociological bias in generated images, a chatbot, and a virtual rapper. These examples of denigration and stereotyping are troubling…