Researchers present bold ideas for AI at MIT Generative AI Impact Consortium kickoff event
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Trained with a joint understanding of protein and cell behavior, the model could help with diagnosing disease and developing new drugs.
New type of “state-space model” leverages principles of harmonic oscillators.
Merging design and computer science in creative ways
MAD Fellow Alexander Htet Kyaw connects humans, machines, and the physical world using AI and augmented reality.
Could LLMs help design our next medicines and materials?
A new method lets users ask, in plain language, for a new molecule with certain properties, and receive a detailed description of how to synthesize it.
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AI model deciphers the code in proteins that tells them where to go
Whitehead Institute and CSAIL researchers created a machine-learning model to predict and generate protein localization, with implications for understanding and remedying disease.
Creating a common language
New faculty member Kaiming He discusses AI’s role in lowering barriers between scientific fields and fostering collaboration across scientific disciplines.
Can deep learning transform heart failure prevention?
A deep neural network called CHAIS may soon replace invasive procedures like catheterization as the new gold standard for monitoring heart health.