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Massachusetts Institute of Technology - MIT News AI supports the clean energy transition as it manages power grid operations, helps plan infrastructure investments, guides development of novel materials, and more
Novel AI model inspired by neural dynamics from the brain Researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) have developed a novel artificial intelligence model inspired by neural oscillations in the brain, with the goal of significantly advancing how machine learning algorithms handle long sequences of data AI often struggles with analyzing complex information that unfolds over long periods of time, such as
Exploring how AI will shape the future of work - MIT News What happens when AI begins making many of our decisions?” These are some of the questions MIT Sloan School of Management PhD candidate Benjamin Manning is researching Part of his work investigates how to design and evaluate artificial intelligence agents that act on behalf of people, and how their behavior shapes markets and institutions
How we really judge AI - MIT News A new study finds people are more likely to approve of the use of AI in situations where its abilities are perceived as superior to humans’ and where personalization isn’t necessary
MIT researchers “speak objects into existence” using AI and robotics MIT researchers at the School of Architecture and Planning developed a speech-to-reality system that combines generative AI, natural language processing, and robotic assembly to fabricate physical objects from spoken prompts
“Periodic table of machine learning” could fuel AI discovery After uncovering a unifying algorithm that links more than 20 common machine-learning approaches, MIT researchers organized them into a “periodic table of machine learning” that can help scientists combine elements of different methods to improve algorithms or create new ones
AI tool generates high-quality images faster than state-of-the-art . . . A hybrid AI approach known as hybrid autoregressive transformer can generate realistic images with the same or better quality than state-of-the-art diffusion models, but that runs about nine times faster and uses fewer computational resources The new tool uses an autoregressive model to quickly capture the big picture and then a small diffusion model to refine the details of the image