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- Massachusetts Institute of Technology - MIT News
A “scientific sandbox” lets researchers explore the evolution of vision systems The AI-powered tool could inform the design of better sensors and cameras for robots or autonomous vehicles December 17, 2025 Read full story
- Explained: Generative AI’s environmental impact - MIT News
MIT News explores the environmental and sustainability implications of generative AI technologies and applications
- 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
- 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
- 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
- “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
- Responding to the climate impact of generative AI - MIT News
MIT experts discuss strategies and innovations aimed at mitigating the amount of greenhouse gas emissions generated by the training, deployment, and use of AI systems, in the second in a two-part series on the environmental impacts of generative artificial intelligence
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