Last year, MIT President Sally Kornbluth and Provost Cynthia Barnhart launched an initiative to compile and publish proposals on the subject of generative artificial intelligence (AI). They requested submissions of papers detailing effective roadmaps, policy recommendations, and calls for action to further develop and understand the field.
The appeal for the first round of papers generated…
Last year, MIT President Sally Kornbluth and Provost Cynthia Barnhart encouraged academics to submit papers outlining roadmaps, policy recommendations, and calls to action in the area of generative AI. This generated a strong response, with 75 submissions being made. 27 of these were selected to receive seed funding.
Due to the high interest and quality of…
The Massachusetts Institute of Technology (MIT) has announced its plan to fund 16 research proposals dedicated to exploring the potential of generative Artificial Intelligence (AI). The funding process began last summer when MIT President Sally Kornbluth and Provost Cynthia Barnhart invited research papers that could provide robust policy guidelines, efficient roadmaps, and calls to action…
In response to a call from MIT President Sally Kornbluth and Provost Cynthia Barnhart, researchers have submitted 75 proposals addressing the use of generative AI. Due to the overwhelming response, a second call was issued, with 53 submissions. A selected 27 from the initial call, and 16 from the second have been granted seed funding.…
Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart invited researchers to submit papers that lay out effective strategies, policy recommendations, and urgent actions within the field of generative artificial intelligence (AI). Among the 75 received proposals, 27 were selected for seed funding.
Impressed by the level of interest and the quality of ideas,…
MIT President, Sally Kornbluth, and Provost, Cynthia Barnhart, issued a call for papers last summer regarding “effective roadmaps, policy recommendations, and calls for action” in the field of generative AI. From the 75 proposals they received, 27 were chosen for seed funding. Following the enormous response, a second call for proposals was launched which resulted…
MIT President Sally Kornbluth and Provost Cynthia Barnhart launched a call for papers last summer to create policy recommendations and effective strategies in the realm of generative AI. The duo received 75 proposals, out of which 27 were picked for seed financing. Encouraged by the response, a second call was held in fall, resulting in…
Researchers at Massachusetts Institute of Technology (MIT) have developed an image dataset to simulate peripheral vision in artificial intelligence (AI) models. This step is aimed at helping such models detect approaching dangers more effectively, or predict whether a human driver would take note of an incoming object.
Peripheral vision in humans allows us to see…
Researchers from MIT have developed an image dataset that simulates peripheral vision in machine learning models, improving their object detection capabilities. However, even with this modification, the AI models still fell short of human performance. The researchers discovered that size and visual clutter, factors that impact human performance, largely did not affect the AI's ability.…
Peripheral vision, most humans' mechanism to see objects not directly in their line of sight, although with less detail, does not exist in AI. However, researchers at MIT have made significant progress towards this by developing an image dataset to simulate peripheral vision in machine learning models. The research indicated that models trained with this…
MIT researchers are replicating peripheral vision—a human's ability to detect objects outside their direct line of sight—in AI systems, which could enable these machines to more effectively identify imminent dangers or predict human behavior. By equipping machine learning models with an extensive image dataset to imitate peripheral vision, the team found these models were better…