A new report by MIT researchers highlights the potential of generative AI to help workers with certain writing assignments.
MIT postdoc Ziv Epstein SM ’19, PhD ’23 discusses issues arising from the use of generative AI to make art and other media.
Selecting the right method gives users a more accurate picture of how their model is behaving, so they are better equipped to correctly interpret its predictions.
A new study finds human supervisors have the potential to reduce barriers to deploying autonomous vehicles.
The CSAIL scientist describes natural language processing research through state-of-the-art machine-learning models and investigation of how language can enhance other types of artificial intelligence.
Models trained using common data-collection techniques judge rule violations more harshly than humans would, researchers report.
Experts convene to peek under the hood of AI-generated code, language, and images as well as its capabilities, limitations, and future impact.
The method enables a model to determine its confidence in a prediction, while using no additional data and far fewer computing resources than other methods.
New fellows are working on health records, robot control, pandemic preparedness, brain injuries, and more.