Artificial Intelligence

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 for 3D reconstruction, hand and body…

This article is from The Checkup, MIT Technology Review’s weekly biotech newsletter. To receive it in your inbox every Thursday, sign up here. Would you trust medical advice generated by artificial intelligence? It’s a question I’ve been thinking over this week, in view of yet more headlines proclaiming that AI technologies can diagnose a range…

Property assessments sit at the center of home appraisals, insurance claims, renovation projects, and a number of other important processes. Inaccurate or delayed assessments can set projects back and stick consumers with higher costs. Now, a platform first developed at MIT makes creating detailed property assessments as easy as snapping a few pictures. The alumni-founded…

Posted by Rajat Sen and Abhimanyu Das, Research Scientists, Google Research Time-series forecasting is an important research area that is critical to several scientific and industrial applications, like retail supply chain optimization, energy and traffic prediction, and weather forecasting. In retail use cases, for example, it has been observed that improving demand forecasting accuracy can…

MIT researchers are using artificial intelligence to design new proteins that go beyond those found in nature. They developed machine-learning algorithms that can generate proteins with specific structural features, which could be used to make materials that have certain mechanical properties, like stiffness or elasticity. Such biologically inspired materials could potentially replace materials made from…

Posted by Lauren Wilcox, Senior Staff Research Scientist, on behalf of the Technology, AI, Society and Culture Team Google sees AI as a foundational and transformational technology, with recent advances in generative AI technologies, such as LaMDA, PaLM, Imagen, Parti, MusicLM, and similar machine learning (ML) models, some of which are now being incorporated into…

In the vast, expansive skies where birds once ruled supreme, a new crop of aviators is taking flight. These pioneers of the air are not living creatures, but rather a product of deliberate innovation: drones. But these aren’t your typical flying bots, humming around like mechanical bees. Rather, they’re avian-inspired marvels that soar through the…

OpenAI has just over a week to comply with European data protection laws following a temporary ban in Italy and a slew of investigations in other EU countries. If it fails, it could face hefty fines, be forced to delete data, or even be banned.  But experts have told MIT Technology Review that it will…

Posted by Badih Ghazi, Staff Research Scientist, and Nachiappan Valliappan, Staff Software Engineer, Google Research Recently, differential privacy (DP) has emerged as a mathematically robust notion of user privacy for data aggregation and machine learning (ML), with practical deployments including the 2022 US Census and in industry. Over the last few years, we have open-sourced…

Posted by Matthew Streeter, Software Engineer, Google Research Derivatives play a central role in optimization and machine learning. By locally approximating a training loss, derivatives guide an optimizer toward lower values of the loss. Automatic differentiation frameworks such as TensorFlow, PyTorch, and JAX are an essential part of modern machine learning, making it feasible to…