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This miniature microchip has the capability to protect user information while also enhancing the effectiveness of computations on a mobile device.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedJuly 25, 202434Views0Likes0Comments

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In order to improve an AI assistant, initiate by imitating the unpredictable actions of humans.

Algorithms, Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 25, 202428Views0Likes0Comments
Researchers from MIT and the University of Washington have developed a method to model the behaviour of an agent, including its computational limitations, predicting future behaviours by examining prior actions. The method applies to both humans and AI, and has a wide range of potential applications, including predicting navigation goals from past routes and forecasting…

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This miniature microchip can protect user information while facilitating effective computing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedJuly 25, 202431Views0Likes0Comments
Health-monitoring apps that assist people in managing chronic diseases or tracking fitness goals work with the help of large machine-learning models, which are often shuttled between a user's smartphone and a central memory server. This process can slow down the app's performance and drain the energy of the device. While machine-learning accelerators can help to…

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To develop a superior AI assistant, begin by simulating the unpredictable actions of humans.

Algorithms, Artificial Intelligence, Computer modeling, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Human-computer interaction, Machine learning, MIT Schwarzman College of Computing, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 24, 202434Views0Likes0Comments
In an effort to improve AI systems and their ability to collaborate with humans, scientists are trying to better understand human decision-making, including its suboptimal aspects, and model it in AI. A model for human or AI agent behaviour, developed by researchers at MIT and the University of Washington, takes into account an agent’s unknown…

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This compact semiconductor ensures the protection of user information while facilitating proficient processing on a mobile phone.

Artificial Intelligence, Computer science and technology, Cybersecurity, Data, Electrical Engineering & Computer Science (eecs), Electronics, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Privacy, Research, School of Engineering, UncategorizedJuly 24, 202436Views0Likes0Comments
Researchers at the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab have developed a machine learning accelerator chip that is resistant to the most common types of cyberattacks, ensuring data privacy while supporting efficient AI model operations on devices. The chip can be used in demanding AI applications like augmented and virtual…

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Researchers from MIT have made significant progress in enhancing the automatic understanding in AI models.

Algorithms, Artificial Intelligence, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Computer vision, Electrical Engineering & Computer Science (eecs), Language, Machine learning, MIT Schwarzman College of Computing, MIT-IBM Watson AI Lab, National Science Foundation (NSF), Research, School of Engineering, UncategorizedJuly 24, 202435Views0Likes0Comments
As AI models become increasingly integrated into various sectors, understanding how they function is crucial. By interpreting the mechanisms underlying these models, we can audit them for safety and biases, potentially deepening our understanding of intelligence. Researchers from MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL) have been working to automate this interpretation process, specifically…

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A novel computational method 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 16, 202440Views0Likes0Comments
MIT researchers have developed a computational model that helps predict mutations leading to better proteins, based on a relatively small dataset. In the current process of creating proteins with useful functions, scientists usually start with a natural protein and put it through numerous rounds of random mutation to generate an optimized version. This process has led…

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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 15, 202436Views0Likes0Comments
In a search to create more effective proteins for various purposes, including research and medical applications, researchers at MIT have developed a new computational approach aimed at predicting beneficial mutations based on limited data. Modeling this technique, they produced modified versions of green fluorescent protein (GFP), a protein found in certain jellyfish, and explored its…

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A novel computational method may simplify the process of engineering 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 15, 202435Views0Likes0Comments
Scientists at the Massachusetts Institute of Technology (MIT) have developed a computational tool that can predict mutations to help create better proteins. The tool facilitates the creation of improved versions of proteins through strategic mutations and could offer significant advancements in neuroscience research and medical applications. One common procedure for producing improved proteins involves introducing…

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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 14, 202433Views0Likes0Comments
Researchers at MIT have developed a computational method to hasten the process of generating optimized versions of proteins, using only a small amount of data. The researchers have generated proteins with mutations capable of improving Green Fluorescent Protein (GFP) and a protein used to deliver DNA for gene therapy from an adeno-associated virus (AAV). The process…

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A novel computational method might 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 14, 202438Views0Likes0Comments
Protein engineering is a complicated process, typically involving the random mutation of a natural protein with a desirable function, repeated until an optimal version of the protein is developed. This process has proven successful for proteins like the green fluorescent protein (GFP), but this isn't the case for all proteins. Researchers at MIT have developed…

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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,…

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