MIT researchers found that special kinds of neural networks, called encoders or “tokenizers,” can do much more than previously realized.
School of Engineering
The unique, mathematical shortcuts language models use to predict dynamic scenarios
Language models follow changing situations using clever arithmetic, instead of sequential tracking. By controlling when these approaches are used, engineers could improve the systems’ capabilities.
Read MoreThe simulations matched results from an underground lab experiment in Switzerland, suggesting modeling could be used to validate the safety of nuclear disposal sites.
Read MoreA team of researchers has mapped the challenges of AI in software development, and outlined a research agenda to move the field forward.
Read MoreHow to more efficiently study complex treatment interactions
A new approach for testing multiple treatment combinations at once could help scientists develop drugs for cancer or genetic disorders.
Read MoreCellLENS reveals hidden patterns in cell behavior within tissues, offering deeper insights into cell heterogeneity — vital for advancing cancer immunotherapy.
Read MoreThe Language/AI Incubator, an MIT Human Insight Collaborative project, is investigating how AI can improve communications among patients and practitioners.
Read MoreAI shapes autonomous underwater “gliders”
An AI pipeline developed by CSAIL researchers enables unique hydrodynamic designs for bodyboard-sized vehicles that glide underwater and could help scientists gather marine data.
Read MoreResearchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Read MoreLaunched with a gift from the Biswas Family Foundation, the Biswas Postdoctoral Fellowship Program will support postdocs in health and life sciences.
Read More
You must be logged in to post a comment.