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Artificial intelligence | MIT News | Massachusetts Institute of Technology
The philosophical puzzle of rational artificial intelligence As AI technology advances, a new interdisciplinary course seeks to equip students with foundational critical thinking skills in computing. January 30, 2026 Read full story
What do we know about the economics of AI? - MIT News
Since much economic growth comes from tech innovation, the way societies use artificial intelligence is of keen interest to MIT Institute Professor Daron Acemoglu, who has published several papers on AI economics in recent months.
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.
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 ...
Algorithms and AI for a better world - MIT News
MIT Assistant Professor Manish Raghavan uses computational techniques to push toward better solutions to long-standing societal problems.
MIT researchers develop an efficient way to train more reliable AI ...
MIT researchers developed an efficient approach for training more reliable reinforcement learning models, focusing on complex tasks that involve variability. This could enable the leverage of reinforcement learning across a wide range of applications.
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.
“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.
MIT researchers advance automated interpretability in AI models
MAIA is a multimodal agent for neural network interpretability tasks developed at MIT CSAIL. It uses a vision-language model as a backbone and equips it with tools for experimenting on other AI systems.
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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