Skip to content Skip to sidebar Skip to footer
Only AI Stuff
Only AI Stuff

Electrical Engineering & Computer Science (eecs)

Close

A novel computational method could simplify the process of designing beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), McGovern Institute, MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedJuly 13, 202433Views0Likes0Comments
MIT researchers have developed a computational approach to help predict mutations that can create optimized versions of certain proteins, working with a relatively small amount of data. The team believes the system could lead to potential medical applications and neuroscience research tools. Usually, protein engineering begins with a natural protein that already has a desirable function,…

Read More

A novel computational algorithm could simplify the process of creating beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), McGovern Institute, MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedJuly 13, 202435Views0Likes0Comments
MIT researchers have developed a computational approach that predicts protein mutations, based on limited data, that would enhance their performance. The researchers used their model to create optimized versions of proteins derived from two naturally occurring structures. One of these was the green fluorescent protein (GFP), a molecule used to track cellular processes within the…

Read More

Celebrating a significant event: A dedication ceremony applauds the inauguration of the new Schwarzman College of Computing building at MIT.

Artificial Intelligence, Boston and region, Cambridge, Campus buildings and architecture, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, President L. Rafael Reif, President Sally Kornbluth, School of Engineering, Special events and guest speakers, Technology and society, UncategorizedJuly 13, 202440Views0Likes0Comments
The MIT Stephen A. Schwarzman College of Computing recently celebrated the completion of its new Vassar Street building. The dedication ceremony was attended by members of the MIT community, distinguished guests, and supporters, reflecting on the transformative gift from Stephen A. Schwarzman that initiated the biggest change to MIT’s institutional structure in over 70 years.…

Read More

A novel computational method may simplify the process of designing beneficial proteins.

Artificial Intelligence, Biological engineering, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Defense Advanced Research Projects Agency (DARPA), DNA, Electrical Engineering & Computer Science (eecs), McGovern Institute, MIT Schwarzman College of Computing, National Institutes of Health (NIH), National Science Foundation (NSF), Proteins, Research, School of Engineering, School of Science, UncategorizedJuly 12, 202434Views0Likes0Comments
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…

Read More

When should you rely on an AI model?

Artificial Intelligence, Computer science and technology, Data, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, Technology and society, UncategorizedJuly 12, 202441Views0Likes0Comments
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…

Read More

The cognitive abilities of extensive linguistic models are frequently exaggerated.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Quest for Intelligence, Research, School of Engineering, UncategorizedJuly 12, 202446Views0Likes0Comments
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,”…

Read More

Researchers from MIT present a generative artificial intelligence for databases.

Algorithms, Artificial Intelligence, Brain and cognitive sciences, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Data, Defense Advanced Research Projects Agency (DARPA), Electrical Engineering & Computer Science (eecs), Machine learning, MIT Schwarzman College of Computing, Programming, Programming languages, Research, School of Engineering, School of Science, UncategorizedJuly 8, 202432Views0Likes0Comments
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,…

Read More

MIT scholars researching generative AI’s implications and uses received the second round of seed fund allocations.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 8, 202440Views0Likes0Comments
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…

Read More

MIT researchers studying the implications and uses of generative AI receive a second phase of seed funds.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 7, 202432Views0Likes0Comments
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…

Read More

MIT researchers studying the effects and uses of generative AI have received a second round of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 7, 202437Views0Likes0Comments
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…

Read More

MIT researchers studying the effects and usage of generative AI receive another round of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 6, 202439Views0Likes0Comments
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…

Read More

MIT researchers examining the influence and uses of generative AI have received a second batch of seed funding.

Administration, Algorithms, Artificial Intelligence, Community, Computer science and technology, Electrical Engineering & Computer Science (eecs), Faculty, Funding, Grants, Machine learning, MIT Schwarzman College of Computing, President Sally Kornbluth, Provost, Research, School of Architecture and Planning, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Technology and policy, Technology and society, UncategorizedJuly 6, 202440Views0Likes0Comments
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…

Read More

+60 12-462 2768
hello@goacademyai.com