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Research

To enhance an AI assistant’s capabilities, begin by simulating the unpredictable actions of human beings.

Researchers from MIT and the University of Washington have developed a model that predicts human behavior by considering computational constraints that limit an individual's problem-solving ability. This model can be used to estimate a person's ‘inference budget’, or time available for problem-solving, based on their past actions. It can then predict their future behavior. Drawing from…

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Begin the development of an improved AI assistant by imitating the unpredictable actions of humans.

Researchers at MIT and the University of Washington have created a model that considers the computational constraints whilst predicting human behavior, which in turn could potentially make AI more efficient collaborators. These constraints can affect an individual or system's problem-solving abilities. The model can automatically infer these constraints by observing only a few prior actions…

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For an improved AI assistant, begin by mirroring the unpredictable actions of people.

MIT and University of Washington researchers have developed a model to understand and predict human behavior, which could improve the effectiveness of AI systems in collaboration with humans. Recognizing the suboptimal nature of human decision-making often due to computational constraints, the researchers created a model that factors in these constraints observed from an agent's previous…

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This small microchip can protect user information while enhancing the computing performance on a mobile device.

Researchers from MIT and MIT-IBM Watson AI Lab have developed a machine-learning accelerator chip with enhanced security to guard against the two most common types of cyber attacks. The chip is designed to perform computations within a device, keeping crucial data like health records, financial information, or other sensitive information private. While this added security…

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To enhance the effectiveness of an AI assistant, begin by emulating the unpredictable actions of people.

Researchers at MIT and the University of Washington have developed a model that predicts the behavior of an agent (either human or machine) by accounting for unknown computational constraints that might hamper problem-solving abilities. This model, described as an agent's "inference budget", can infer these constraints from just a few prior actions and subsequently predict…

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This small microchip can protect user information and enhance influential computing on a mobile phone.

A team of researchers from the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that is resistant to the most common types of cyber attacks. This development could help secure sensitive health records, financial information and other private data while still allowing complicated artificial intelligence (AI) models…

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

Smartphone health-monitoring apps can be invaluable for managing chronic diseases or setting fitness goals. However, these applications often suffer from slowdowns and energy inefficiencies due to the large machine-learning models they use. These models are frequently swapped between a smartphone and a central memory server, hampering performance. One solution engineers have pursued is the use…

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For improving an AI assistant, begin by simulating the unpredictable actions of humans.

Researchers at MIT and the University of Washington have developed a model to estimate the computational limitations or "inference budget" of an individual or AI agent, with the ultimate objective of enhancing the collaboration between humans and AI. The project, spearheaded by graduate student Athul Paul Jacob, proposes that this model can greatly improve the…

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This minuscule microchip can protect the information of its users while facilitating effective processing on a mobile phone.

Researchers from MIT and the MIT-IBM Watson AI Lab have designed a machine-learning accelerator that is impervious to the two most common types of cyberattacks. Currently, healthcare apps that monitor chronic diseases or fitness goals are relying on machine learning to operate. However, the voluminous machine-learning models utilized need to be transferred between a smartphone…

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To enhance the proficiency of an AI assistant, it is essential to commence by mapping out the unpredictable actions of human beings.

Researchers at MIT and University of Washington have crafted a model for understanding the behavior of humans and machines in decision-making scenarios, even when this behavior is suboptimal due to computational constraints. The model is based on an agent's “inference budget”, predictive of future behavior derived from observations of previous actions. This model could potentially…

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This compact chip is capable of protecting user information, while also promoting effective computing on a mobile phone.

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that enhances the security of health-tracking apps. These apps can be slow and consume a lot of energy due to the data exchange requirements between the phone and a central server. “Machine-learning accelerators” are used to speed up such apps but…

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