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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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Agent Poison: A Unique Approach for Red Teaming and Backdoor Assaults on Generic and RAG-based LLM Agents by Contaminating their Persistent Memory or RAG Information Repository.

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 24, 202432Views0Likes0Comments
Large Language Models (LLMs) have shown vast potential in various critical sectors, such as finance, healthcare, and self-driving cars. Typically, these LLM agents use external tools and databases to carry out tasks. However, this reliance on external sources has raised concerns about their trustworthiness and vulnerability to attacks. Current methods of attack against LLMs often…

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Google AI Unveils NeuralGCM: A Fresh Machine Learning (ML) Oriented Method for Imitating Earth’s Atmosphere

AI Paper Summary, AI Shorts, Applications, Artificial Intelligence, Editors Pick, Machine learning, Staff, Tech News, Technology, UncategorizedJuly 24, 202432Views0Likes0Comments
General circulation models (GCMs) are crucial in weather and climate prediction. They work using numerical solvers for big scale dynamics and parameterizations for smaller processes like cloud formation. Despite continuous enhancements, difficulties still persist, including errors, biases, and uncertainties in long-term weather projections and severe weather events. Recently introduced machine-learning models have shown excellent results…

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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, 202439Views0Likes0Comments

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Materials that conduct protons could potentially lead to the development of novel eco-friendly energy solutions.

Artificial Intelligence, DMSE, Energy, Machine learning, Materials science and engineering, Research, School of Engineering, Sustainability, UncategorizedJuly 24, 202439Views0Likes0Comments
MIT engineers have identified new materials that could be more efficient conductors of protons – the nucleus of a hydrogen atom – which could pave the way for a number of climate-protecting technologies. Today's proton-conducting materials require very high temperatures, but lower-temperature alternatives could boost new technologies such as fuel cells that produce clean electricity…

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