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National Science Foundation (NSF)

For the improvement of AI assistance, initially emulate the unpredictable actions of humans.

Researchers from MIT and the University of Washington have developed a model to predict human behavior that accounts for computational constraints. These constraints can impact the problem-solving abilities of both human and artificial intelligences (AI). The model can infer an “inference budget”, a computation of the possible constraints on an agent’s problem-solving methods, by observing…

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

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that combats cyber threats, thereby protecting sensitive user data. While certain health or fitness apps employ these vast machine-learning models to provide insights, they can sometimes prove to be sluggish and consume a large amount of energy due to the shifting…

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To develop a superior artificial intelligence assistant, commence by replicating the illogical actions exhibited by humans.

Researchers from MIT and the University of Washington have created a model that considers the computational constraints of an agent, which could be a human or a machine, resulting in a more accurate prediction of the agent's actions. Humans, despite having sophisticated decision-making abilities, are often irrational and tend to behave suboptimally due to computational constraints.…

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This compact microchip can protect user information and boost effective computing on a mobile phone.

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that strengthens the security of health-monitoring apps and other AI-powered devices. These apps and devices, which can help manage chronic diseases or track fitness progress, run on complex machine-learning models. This requires substantial data transfer between a central memory server and…

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To create a superior AI assistant, begin by replicating the unpredictable actions of human beings.

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This small microchip can protect user information while aiding in the effective operation of a mobile phone.

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a hardware solution that enhances the security of machine-learning applications on smartphones. Current health-monitoring apps require large amounts of data to be transferred back and forth between the phone and a central server, which can create security vulnerabilities and inefficiency. To counter this, the…

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

Researchers from MIT and MIT-IBM Watson AI Lab have created a machine-learning accelerator that is resistant to the most common types of cyber attacks. The chip can hold users' sensitive data such as health records and financial information, enabling large AI models to run efficiently on devices while maintaining privacy. The accelerator maintains strong security,…

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To enhance AI assistant development, begin by emulating the unpredictable conduct of humans.

Artificial Intelligence (AI) that can work effectively with humans requires a robust model of human behaviour. However, humans often behave irrationally, limiting their decision-making abilities. Researchers at MIT and the University of Washington have developed a model for predicting an agent's behaviour (whether human or machine) by considering computational constraints that affect problem-solving, which they refer…

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This compact semiconductor provides protection for user information while facilitating streamlined computation on a mobile device.

Health-monitoring apps powered by advanced machine-learning (ML) models could be more secure and still run efficiently on devices, according to researchers from MIT and the MIT-IBM Watson AI Lab. Though the models require vast amounts of data shuttling between a smartphone and a central memory server, using a machine-learning accelerator can speed up the process…

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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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