Large language models (LLMs) have a dirty secret: they require vast amounts of energy to train and run. What’s more, it’s still a bit of a mystery exactly how big these models’ carbon footprints really are. AI startup Hugging Face believes it’s come up with a new, better way to calculate that more precisely, by…
Nearly 75% of the world’s largest companies have already integrated AI and machine learning (ML) into their business strategies. As more and more companies — and their customers — gain increasing value from ML applications, organizations should be considering new security best practices to keep pace with the evolving technology landscape. Companies that utilize dynamic…
Posted by Jacky Liang, Research Intern, and Andy Zeng, Research Scientist, Robotics at Google <!—-><!—-> A common approach used to control robots is to program them with code to detect objects, sequencing commands to move actuators, and feedback loops to specify how the robot should perform a task. While these programs can be expressive, re-programming…
Posted by Rishabh Agarwal, Senior Research Scientist, and Max Schwarzer, Student Researcher, Google Research, Brain Team Reinforcement learning (RL) is an area of machine learning that focuses on training intelligent agents using related experiences so they can learn to solve decision making tasks, such as playing video games, flying stratospheric balloons, and designing hardware chips….
Posted by Noah Snavely and Zhengqi Li, Research Scientists, Google Research We live in a world of great natural beauty — of majestic mountains, dramatic seascapes, and serene forests. Imagine seeing this beauty as a bird does, flying past richly detailed, three-dimensional landscapes. Can computers learn to synthesize this kind of visual experience? Such a…
Posted by Shunyu Yao, Student Researcher, and Yuan Cao, Research Scientist, Google Research, Brain Team <!—-> Recent advances have expanded the applicability of language models (LM) to downstream tasks. On one hand, existing language models that are properly prompted, via chain-of-thought, demonstrate emergent capabilities that carry out self-conditioned reasoning traces to derive answers from questions,…
Posted by Peter H. Li, Research Scientist, and Sven Dorkenwald, Student Researcher, Connectomics at Google Mapping the wiring and firing activity of the human brain is fundamental to deciphering how we think — how we sense the world, learn, decide, remember, and create — as well as what issues can arise in brain disease or…
Posted by Jason Wei and Yi Tay, Research Scientists, Google Research, Brain Team The field of natural language processing (NLP) has been revolutionized by language models trained on large amounts of text data. Scaling up the size of language models often leads to improved performance and sample efficiency on a range of downstream NLP tasks….
It’s a dilemma as old as time. Friday night has rolled around, and you’re trying to pick a restaurant for dinner. Should you visit your most beloved watering hole or try a new establishment, in the hopes of discovering something superior? Potentially, but that curiosity comes with a risk: If you explore the new option,…
To receive The Algorithm newsletter in your inbox every Monday, sign up here. Welcome to the Algorithm! This year we’ve seen a dizzying number of breakthroughs in generative AI, from AIs that can produce videos from just a few words to models that can generate audio based on snippets of a song. Last week, Google held an AI event in its swanky,…