Study could lead to LLMs that are better at complex reasoning
Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Researchers developed a way to make large language models more adaptable to challenging tasks like strategic planning or process optimization.
Developed to analyze new semiconductors, the system could streamline the development of more powerful solar panels.
The MIT Energy Initiative’s annual research symposium explores artificial intelligence as both a problem and a solution for the clean energy transition.
MIT CSAIL researchers combined GenAI and a physics simulation engine to refine robot designs. The result: a machine that out-jumped a robot designed by humans.
Researchers find nonclinical information in patient messages — like typos, extra white space, and colorful language — reduces the accuracy of an AI model.
Presentations targeted high-impact intersections of AI and other areas, such as health care, business, and education.
Composed of “computing bilinguals,” the Undergraduate Advisory Group provides vital input to help advance the mission of the MIT Schwarzman College of Computing.
In a new study, researchers discover the root cause of a type of bias in LLMs, paving the way for more accurate and reliable AI systems.
By performing deep learning at the speed of light, this chip could give edge devices new capabilities for real-time data analysis.
A new book from Professor Munther Dahleh details the creation of a unique kind of transdisciplinary center, uniting many specialties through a common need for data science.