Posted by Pete Florence, Research Scientist and Corey Lynch, Research Engineer, Robotics at Google Despite considerable progress in robot learning over the past several years, some policies for robotic agents can still struggle to decisively choose actions when trying to imitate precise or complex behaviors. Consider a task in which a robot tries to slide…
Posted by David Ha, Staff Research Scientist and Yujin Tang, Research Software Engineer, Google Research, Tokyo <!– “The brain is able to use information coming from the skin as if it were coming from the eyes. We don’t see with the eyes or hear with the ears, these are just the receptors, seeing and hearing…
Posted by Sian Gooding, Intern, Google Research Illiteracy affects at least 773 million people globally, both young and old. For these individuals, reading information from unfamiliar sources or on unfamiliar topics can be extremely difficult. Unfortunately, these inequalities have been further magnified by the global pandemic as a result of unequal access to education in…
Posted by Rishabh Agarwal, Research Scientist and Pablo Samuel Castro, Staff Software Engineer, Google Research, Brain Team Reinforcement learning (RL) is an area of machine learning that focuses on learning from experiences to solve decision making tasks. While the field of RL has made great progress, resulting in impressive empirical results on complex tasks, such…
Posted by Nal Kalchbrenner and Lasse Espeholt, Google Research Deep learning has successfully been applied to a wide range of important challenges, such as cancer prevention and increasing accessibility. The application of deep learning models to weather forecasts can be relevant to people on a day-to-day basis, from helping people plan their day to managing…
Posted by Artem Dementyev, Hardware Engineer, Google Research Most wearable smart devices and mobile phones have the means to communicate with the user through tactile feedback, enabling applications from simple notifications to sensory substitution for accessibility. Typically, they accomplish this using vibrotactile actuators, which are small electric vibration motors. However, designing a haptic system that…
Posted by Jason Wei, AI Resident and Dan Garrette, Research Scientist, Google Research In recent years, pre-trained language models, such as BERT and GPT-3, have seen widespread use in natural language processing (NLP). By training on large volumes of text, language models acquire broad knowledge about the world, achieving strong performance on various NLP benchmarks….
Posted by Sabela Ramos, Software Engineer and Léonard Hussenot, Student Researcher, Google Research, Brain Team Most reinforcement learning (RL) and sequential decision making algorithms require an agent to generate training data through large amounts of interactions with their environment to achieve optimal performance. This is highly inefficient, especially when generating those interactions is difficult, such…
Posted by Aashi Jain, AI Resident and Yinfei Yang, Staff Research Scientist, Google Research For many concepts, there is no direct one-to-one translation from one language to another, and even when there is, such translations often carry different associations and connotations that are easily lost for a non-native speaker. In such cases, however, the meaning…
Defining what is, or isn’t artificial intelligence can be tricky (or tough). So much so, even the experts get it wrong sometimes. That’s why MIT Technology Review’s Senior AI Editor Karen Hao created a flowchart to explain it all. In this bonus content our host and her team reimagined Hao’s original reporting, gamifying it into…