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- Artificial intelligence | MIT News | Massachusetts Institute of Technology
NSF renews support for MIT-led AI and physics institute, expanding a new model for discovery IAIFI enters its second phase with increased funding, broader ambitions, and a growing community at the frontier of AI and fundamental physics
- 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
- 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
- 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
- Creating AI that matters - MIT News
The MIT-IBM Watson AI Lab bridges research and deployment in AI through advances like smaller, efficient foundation models, vision and multimodal systems, and causal discovery
- 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
- Teaching AI models what they don’t know - MIT News
A team of MIT researchers founded Themis AI to quantify artificial intelligence model uncertainty and address knowledge gaps
- 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
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