Massachusetts Institute of Technology - MIT News New AI agent learns to use CAD to create 3D objects from sketches The virtual VideoCAD tool could boost designers’ productivity and help train engineers learning computer-aided design
“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
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
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
What does the future hold for generative AI? - MIT News Hundreds of scientists, business leaders, faculty, and students shared the latest research and discussed the potential future course of generative AI advancements during the inaugural symposium of the MIT Generative AI Impact Consortium (MGAIC) on Sept 17
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
Charting the future of AI, from safer answers to faster thinking Five PhD students from the inaugural class of the MIT-IBM Watson AI Lab Summer Program are building AI pipelines with probes, routers, new attention mechanisms, synthetic datasets, and program-synthesis and more to improve safety, inference efficiency, multimodal data, and knowledge-grounded reasoning
Introducing the MIT Generative AI Impact Consortium The MIT Generative AI Impact Consortium is a collaboration between MIT, founding member companies, and researchers across disciplines who aim to develop open-source generative AI solutions, accelerating innovations in education, research, and industry