Scientists at Massachusetts Institute of Technology (MIT) have developed a computational model aimed at simplifying the process of protein engineering. The researchers applied mutations to natural proteins with desirable traits, such as the ability to emit fluorescent light, using random mutation to cultivate better versions of the protein. The technique was deployed using the green…
MIT researchers have developed a technique for improving the accuracy of uncertainty estimates in machine-learning models. This is especially important in situations where these models are used for critical tasks such as diagnosing diseases from medical imaging or filtering job applications. The new method works more efficiently and is scalable enough to apply to large…
Artificial intelligence (AI) and particularly large language models (LLMs) are not as robust at performing tasks in unfamiliar scenarios as they are positioned to be, according to a study by researchers from MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL).
The researchers focused on the performance of models like GPT-4 and Claude when handling “default tasks,”…
A group of New England Innovation Academy students have developed a mobile app that highlights deforestation trends in Massachusetts as part of a project for the Day of AI, a curriculum developed by the MIT Responsible AI for Social Empowerment and Education (RAISE) initiative. The TreeSavers app aims to educate users about the effects of…
GenSQL, a new AI tool developed by scientists at MIT, is designed to simplify the complex statistical analysis of tabular data, enabling users to readily understand and interpret their databases. To this end, users don't need to grasp what is happening behind the scenes to develop accurate insights.
The system's capabilities include making predictions, identifying anomalies,…
MIT President Sally Kornbluth and Provost Cynthia Barnhart last year issued a call for papers with the aim of developing effective strategies, policy recommendations, and calls to action in the field of generative artificial intelligence (AI). The response was overwhelming, with a total of 75 proposals submitted. Out of these, 27 were selected for seed…
Last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart issued a call for papers on generative artificial intelligence (AI). They sought effective roadmaps, policy recommendations, and calls for action in the AI field, and received 75 proposals. Out of these, 27 were selected for seed funding.
Due to the robust response to this initial funding…
MIT President, Sally Kornbluth, and Provost, Cynthia Barnhart, recently solicited research proposals on the topic of generative artificial intelligence (AI). The response was overwhelming, with 75 proposals submitted from across MIT. Consequently, due to the level of interest and quality of the proposals, a second call for papers was announced, which led to an additional…
In response to their call for papers last summer, MIT President Sally Kornbluth and Provost Cynthia Barnhart received an overwhelming interest from the research community. The call for proposals was made to "articulate effective roadmaps, policy recommendations, and calls for action across the broad domain of generative AI." The response far exceeded expectations, with 75…
MIT President Sally Kornbluth and Provost Cynthia Barnhart launched a call for papers last summer relating to generative AI, with the aim of collecting effective strategies, policy suggestions, and calls to action in this expansive field. The response was overwhelming, with a total submission of 75 proposals, out of which 27 were chosen for seed…
Last year, a request from MIT President Sally Kornbluth and Provost Cynthia Barnhart for research proposals concerning generative AI initiatives resulted in 75 submissions. Out of these, 27 were selected for initial funding. Inspired by the impressive response, Kornbluth and Barnhart issued a second call for papers last fall. This resulted in 53 more proposals,…
In recent months, the Massachusetts Institute of Technology (MIT) called for papers on the topic of artificial intelligence (AI), set to construct effective roadmaps, policy recommendations, and action strategies across generative AI. The response was overwhelmingly positive with 75 paper proposals submitted. Out of these, 27 were chosen for seed funding. Given the successful outcome…