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To construct an advanced AI assistant, initiate the process by imitating the erratic 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 at MIT and the University of Washington have developed a model that accounts for the sub-optimal decision-making processes in humans, potentially improving the way artificial intelligence can predict human behavior. Named 'inference budget,' the model infers an agent's computational constraints, whether human or machine, after observing a few traces of their past actions. It…

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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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Research: The use of randomness in AI can enhance equity when distributing limited resources.

Algorithms, 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, UncategorizedJuly 24, 202438Views0Likes0Comments
Machine learning (ML) models are increasingly used by organizations to allocate scarce resources or opportunities, such as for job screening or determining priority for kidney transplant patients. To avoid bias in a model's predictions, users may adjust the data features or calibrate the model's scores to ensure fairness. However, researchers at MIT and Northeastern University…

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AI model recognizes specific stages of breast tumor that may evolve into aggressive cancer.

Artificial Intelligence, Broad Institute, Cancer, Computer science and technology, Diagnostics, Disease, Electrical Engineering & Computer Science (eecs), Health, Health care, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 24, 202438Views0Likes0Comments

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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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Even though we may anticipate large language models to operate similarly to humans, they do not.

Algorithms, Artificial Intelligence, Computer science and technology, Economics, Human-computer interaction, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, Research, School of Engineering, School of Humanities Arts and Social Sciences, UncategorizedJuly 23, 202432Views0Likes0Comments
Large language models (LLMs), such as GPT-3, are powerful tools due to their versatility. They can perform a wide range of tasks, ranging from helping draft emails to assisting in cancer diagnosis. However, their wide applicability makes them challenging to evaluate systematically, as it would be impossible to create a benchmark dataset to test a…

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A novel artificial intelligence approach accurately interprets ambiguity in medical imaging.

Artificial Intelligence, Broad Institute, Computer Science and Artificial Intelligence Laboratory (CSAIL), Computer science and technology, Electrical Engineering & Computer Science (eecs), Health care, Imaging, Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 23, 202433Views0Likes0Comments
Artificial intelligence (AI) tools have great potential in the field of biomedicine, particularly in the process of segmentation or annotating the pixels of an important structure in a medical image. Segmentation is critical for the identification of possible diseases or anomalies in body organs or cells. However, the challenge lies in the variability of the…

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The AI model is capable of recognizing specific stages of breast tumors that have a high probability of developing into invasive cancer.

Artificial Intelligence, Broad Institute, Cancer, Computer science and technology, Diagnostics, Disease, Electrical Engineering & Computer Science (eecs), Health, Health care, IDSS, Laboratory for Information and Decision Systems (LIDS), Machine learning, MIT Schwarzman College of Computing, National Institutes of Health (NIH), Research, School of Engineering, UncategorizedJuly 23, 202438Views0Likes0Comments
Ductal carcinoma in situ (DCIS), a type of tumor that can develop into an aggressive form of breast cancer, accounts for approximately 25% of all breast cancer diagnoses. DCIS can be challenging for clinicians to accurately categorize, leading to frequent overtreatment for patients. A team of researchers from the Massachusetts Institute of Technology (MIT) and…

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