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Massachusetts Institute of Technology - MIT News MIT researchers “speak objects into existence” using AI and robotics The speech-to-reality system combines 3D generative AI and robotic assembly to create objects on demand
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
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
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
Explained: Generative AI | MIT News | Massachusetts Institute of Technology What do people mean when they say “generative AI,” and why are these systems finding their way into practically every application imaginable? MIT AI experts help break down the ins and outs of this increasingly popular, and ubiquitous, technology
MIT researchers introduce generative AI for databases Researchers from MIT and elsewhere developed an easy-to-use tool that enables someone to perform complicated statistical analyses on tabular data using just a few keystrokes Their method combines probabilistic AI models with the programming language SQL to provide faster and more accurate results than other methods
Can AI really code? Study maps the roadblocks to autonomous software . . . An AI that can shoulder the grunt work — and do so without introducing hidden failures — would free developers to focus on creativity, strategy, and ethics” says Gu “But that future depends on acknowledging that code completion is the easy part; the hard part is everything else Our goal isn’t to replace programmers It’s to