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Artificial intelligence | MIT News | Massachusetts Institute of Technology
AI system learns from many types of scientific information and runs experiments to discover new materials The new “CRESt” platform could help find solutions to real-world energy problems that have plagued the materials science and engineering community for decades.
Using generative AI, researchers design compounds that can kill drug ...
Using generative AI algorithms, the research team designed more than 36 million possible compounds and computationally screened them for antimicrobial properties. The top candidates they discovered are structurally distinct from any existing antibiotics, and they appear to work by novel mechanisms that disrupt bacterial cell membranes.
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.
“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.
New AI system could accelerate clinical research - MIT News
MIT researchers developed an interactive, AI-based system that enables users to rapidly annotate areas of interest in new biomedical imaging datasets, without training a machine-learning model in advance. As the user uploads new images, the number of interactions needed to accurately segment the image drops, eventually to zero, enabling rapid annotation of the entire dataset.
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.
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.
Photonic processor could enable ultrafast AI computations with extreme ...
Researchers developed a fully integrated photonic processor that can perform all the key computations of a deep neural network on a photonic chip, using light. This advance could improve the speed and energy-efficiency of running intensive deep learning models for applications like lidar, astronomical research, and navigation.
New tool makes generative AI models more likely to create breakthrough ...
A new tool called SCIGEN allows researchers to implement design rules that AI models must follow when generating new materials. The advance could speed the development of materials that enable technological breakthroughs.
Have a damaged painting? Restore it in just hours with an AI-generated ...
A new method uses AI to physically restore a damaged painting much more quickly than what’s possible using manual techniques. A digitally generated “mask” in the form of thin film is applied directly to the original painting, and can also be easily removed.
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