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School of Engineering

This small microchip can protect user information while facilitating effective processing on a mobile phone.

Health-monitoring applications have become pivotal in managing chronic diseases and tracking fitness goals, largely due to the advent of machine-learning powered tools. However, these applications are often slow and energy-inefficient, largely due to the massive machine-learning models that require transfer between a smartphone and a central memory server. Despite the development of machine-learning accelerators that…

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Julie Shah has been appointed as the director of the Aeronautics and Astronautics Department.

Julie Shah, a renowned leader in the field of aeronautics and astronautics, has been named the new head of the Department of Aeronautics and Astronautics (AeroAstro) at the Massachusetts Institute of Technology (MIT). The announcement, effective from May 1, was lauded by MIT's chief innovation and strategy officer, Anantha Chandrakasan, who highlighted Shah's substantial technical…

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To improve the creation of AI assistants, begin by imitating the unpredictable actions of humans.

Researchers at MIT and the University of Washington have devised a model to predict the behaviour of AI systems and humans. The model factors in the indefinite computational constraints which may hinder an agent's problem-solving skills. By analysing only a few instances of previous actions, the model can predict an agent's future behaviour. The findings…

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To enhance the development of more effective AI assistants, consider simulating the unpredictable actions of humans as a starting point.

To build an Artificial Intelligence (AI) system that can work effectively with humans, it's critical to have an accurate model of human behavior. However, humans often act less optimally when making decisions, and these irrational behaviors are challenging to imitate. This is due to computational constraints - a person cannot dedicate decades to finding an…

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To improve an AI assistant, initiate by simulating the unpredictable conduct of humans.

Researchers from MIT and the University of Washington have developed a computational model to predict human behavior while taking into account the suboptimal decisions humans often make due to computational constraints. The researchers believe such a model could help AI systems anticipate and counterbalance human-derived errors, enhancing the efficacy of AI-human collaboration. Suboptimal decision-making is characteristic…

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To create an improved AI assistant, begin by simulating the unpredictable actions of people.

Researchers at MIT and the University of Washington have successfully developed a model that can infer an agent's computational constraints from observing a few samples of their past actions. The findings could potentially enhance the ability of AI systems to collaborate more effectively with humans. The scientists found that human decision-making often deviates from optimal,…

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This miniature circuit can protect user information while facilitating effective calculations on a mobile phone.

A team of researchers from MIT and the MIT-IBM Watson AI Lab has developed a machine-learning accelerator that is resistant to the two most common types of cyberattacks. This ensures that sensitive information such as finance and health records remain private while still enabling large AI models to run efficiently on devices. The researchers targeted…

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Julie Shah has been appointed as the leader of the Department of Aeronautics and Astronautics.

Julie Shah, a distinguished scholar and academic thought-leader, is set to assume the role of head of the Department of Aeronautics and Astronautics (AeroAstro) at Massachusetts Institute of Technology (MIT), effective May 1. As affirmed by Anantha Chandrakasan, MIT’s chief innovation and strategy officer, Shah has a remarkable record of interdisciplinary leadership and visionary contributions…

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For improving an AI assistant, begin with simulating the unpredictable tendencies of human beings.

MIT and University of Washington researchers have created a method to model both human and machine behaviours, taking into account unknown computational constraints which can limited problem-solving skills. The model infers an "inference budget" from previous actions. The inference budget can then predict the agent's future behaviour. Their technique can be used to predict navigation…

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This small microchip can protect user information while facilitating effective computation on a mobile phone.

Health-monitoring apps can help individuals manage chronic diseases and keep up with their fitness goals. However, these apps can often be slow and energy-inefficient due to the machine-learning models they use, which need a significant amount of data shuffling between the smartphone and a central memory server. Engineers typically use hardware (machine-learning accelerators) to streamline…

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