Posts in tag

BERT


Self-supervised learning — where machines learn by directly observing the environment rather than being explicitly taught through labeled images, text, audio, and other data sources — has powered many significant recent advances in AI. But while people appear to learn in a similar way regardless of how they get information — whether they use sight …

People use AI for a wide range of speech recognition and understanding tasks, from enabling smart speakers to developing tools for people who are hard of hearing or who have speech impairments. But oftentimes these speech understanding systems don’t work well in the everyday situations when we need them most: Where multiple people are speaking …

Virtually all companies face two broad challenges: to marshal data for smarter decision making, and to deliver more personalized and convenient experiences for customers. Artificial intelligence (AI) can help, but the path from AI investment to business outcome can be difficult to chart. To fast-track time to value, today, we’re pleased to announce new additions …

AI is integral to so much of the work we do at Google. Fundamental advances in computing are helping us confront some of the greatest challenges of this century, like climate change. Meanwhile, AI is also powering updates across our products, including Search, Maps and Photos — demonstrating how machine learning can improve your life in …

Just like an astronomer investigates outer space, a chemist explores chemical space — a theoretical territory with all possible known (and unknown) chemical compounds. Researchers estimate chemical space to contain up to 10180 compounds — more than twice the magnitude of the number of atoms in the universe. Currently, the largest public database of molecules synthesized so …

You don’t need a sledgehammer to crack a nut. Jonathan Frankle is researching artificial intelligence — not noshing pistachios — but the same philosophy applies to his “lottery ticket hypothesis.” It posits that, hidden within massive neural networks, leaner subnetworks can complete the same task more efficiently. The trick is finding those “lucky” subnetworks, dubbed …

In recent years the patent industry has begun to use machine-learning (ML) algorithms to add efficiency and insights to business practices. Any company, patent office, or academic institution that works with patents—generating them through innovation, processing applications about them, or developing sophisticated ways to analyze them—will benefit from doing patent analytics and machine learning in …