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- Artificial intelligence - MIT News
AI stirs up the recipe for concrete in MIT study With demand for cement alternatives rising, an MIT team uses machine learning to hunt for new ingredients across the scientific literature
- Explained: Generative AI’s environmental impact - MIT News
MIT News explores the environmental and sustainability implications of generative AI technologies and applications
- 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
- How we really judge AI - MIT News
A new study finds people are more likely to approve of the use of AI in situations where its abilities are perceived as superior to humans’ and where personalization isn’t necessary
- 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
- Graph-based AI model maps the future of innovation - MIT News
The new AI approach uses graphs based on methods inspired by category theory as a central mechanism to understand symbolic relationships in science This Illustration shows one such graph and how it maps key points of related ideas and concepts
- 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
- “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
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