Latest from Google AI – Infinite Nature: Generating 3D Flythroughs from Still Photos

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…

Latest from Google AI – Beyond Tabula Rasa: Reincarnating Reinforcement Learning

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….

Latest from Google AI – Characterizing Emergent Phenomena in Large Language Models

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….

Latest from Google AI – Multi-layered Mapping of Brain Tissue via Segmentation Guided Contrastive Learning

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…

Latest from MIT : Ensuring AI works with the right dose of curiosity

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,…

Latest from MIT Tech Review – Where will AI go next?

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,…

Latest from MIT : A whole new world of learning via MIT OpenCourseWare videos

Like millions of others during the global Covid-19 lockdowns, Emmanuel Kasigazi, an entrepreneur from Uganda, turned to YouTube to pass the time. But he wasn’t following an influencer or watching music videos. A lifelong learner, Kasigazi was scouring the video-sharing platform for educational resources. Since 2013, when he got his first smartphone, Kasigazi has been…

Latest from MIT : In machine learning, synthetic data can offer real performance improvements

Teaching a machine to recognize human actions has many potential applications, such as automatically detecting workers who fall at a construction site or enabling a smart home robot to interpret a user’s gestures. To do this, researchers train machine-learning models using vast datasets of video clips that show humans performing actions. However, not only is…

Latest from MIT : Study urges caution when comparing neural networks to the brain

Neural networks, a type of computing system loosely modeled on the organization of the human brain, form the basis of many artificial intelligence systems for applications such speech recognition, computer vision, and medical image analysis. In the field of neuroscience, researchers often use neural networks to try to model the same kind of tasks that…