New dataset of “illusory” faces reveals differences between human and algorithmic face detection, links to animal face recognition, and a formula predicting where people most often perceive faces.
By analyzing X-ray crystallography data, the model could help researchers develop new materials for many applications, including batteries and magnets.
This new tool offers an easier way for people to analyze complex tabular data.
Co-hosted by the McGovern Institute, MIT Open Learning, and others, the symposium stressed emerging technologies in advancing understanding of mental health and neurological conditions.
A new downscaling method leverages machine learning to speed up climate model simulations at finer resolutions, making them usable on local levels.
Fifteen new faculty members join six of the school’s academic departments.
A new technique that can automatically classify phases of physical systems could help scientists investigate novel materials.
The conversation in Kresge Auditorium touched on the promise and perils of the rapidly evolving technology.
Three neurosymbolic methods help language models find better abstractions within natural language, then use those representations to execute complex tasks.
At MIT’s Festival of Learning 2024, panelists stressed the importance of developing critical thinking skills while leveraging technologies like generative AI.
