Image
The models were trained on a dataset of synthetic images like the ones pictured, with objects such as tea kettles or calculators superimposed on different backgrounds. Researchers trained the model to identify one or more spatial features of an object, including rotation, location, and distance (Credits: Courtesy of the researchers).
CSAIL article

When visual information enters the brain, it travels through two pathways that process different aspects of the input. For decades, scientists have hypothesized that one of these pathways, the ventral visual stream, is responsible for recognizing objects, and that it might have been optimized by evolution to do just that.

Image
Ray and Maria Stata Center exterior
External articles

"The net effect [of DeepSeek] should be to significantly increase the pace of AI development, since the secrets are being let out and the models are now cheaper and easier to train by more people." ~ Associate Professor Phillip Isola

Image
In a recent commentary, a team from MIT, Equality AI, and Boston University highlights the gaps in regulation for AI models and non-AI algorithms in health care (Credit: Adobe Stock).
CSAIL article

One might argue that one of the primary duties of a physician is to constantly evaluate and re-evaluate the odds: What are the chances of a medical procedure’s success? Is the patient at risk of developing severe symptoms? When should the patient return for more testing? Amidst these critical deliberations, the rise of artificial intelligence promises to reduce risk in clinical settings and help physicians prioritize the care of high-risk patients.