AI model can help determine where a patient’s cancer arose
Predictions from the OncoNPC model could enable doctors to choose targeted treatments for difficult-to-treat tumors.
Predictions from the OncoNPC model could enable doctors to choose targeted treatments for difficult-to-treat tumors.
“PhotoGuard,” developed by MIT CSAIL researchers, prevents unauthorized image manipulation, safeguarding authenticity in the era of advanced generative models.
Researchers develop a machine-learning technique that can efficiently learn to control a robot, leading to better performance with fewer data.
The dataset, being collected as part of a US Coast Guard science mission, will be released open source to help advance naval mission planning and climate change studies.
A new technique helps a nontechnical user understand why a robot failed, and then fine-tune it with minimal effort to perform a task effectively.
Author and African American studies scholar Ruha Benjamin urges MIT Libraries staff to “re-imagine the default settings” of technology for a more just future.
EECS professor appointed to new professorship in the MIT Schwarzman College of Computing.
PIGINet leverages machine learning to streamline and enhance household robots' task and motion planning, by assessing and filtering feasible solutions in complex environments.
A new report by MIT researchers highlights the potential of generative AI to help workers with certain writing assignments.
Researchers create a privacy technique that protects sensitive data while maintaining a machine-learning model’s performance.
Abel Sanchez helps industries and executives shift their operations in order to make sense of their data and use it to help their bottom lines.
In China, the use of AI-driven facial recognition helps the regime repress dissent while enhancing the technology, researchers report.
“FrameDiff” is a computational tool that uses generative AI to craft new protein structures, with the aim of accelerating drug development and improving gene therapy.
Luca Carlone and Jonathan How of MIT LIDS discuss how future robots might perceive and interact with their environment.
This AI system only needs a small amount of data to predict molecular properties, which could speed up drug discovery and material development.