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Cybersecurity

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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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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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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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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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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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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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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This small microchip can protect user information while promoting effective processing on a mobile device.

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a novel machine-learning accelerator that can protect sensitive data like health records from two common types of cybersecurity threats while efficiently running large AI models. This advancement could make an noticable impact on challenging AI applications, such as augmented and virtual reality, autonomous driving…

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

Researchers from the Massachusetts Institute of Technology (MIT) and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator designed to be resistant to cyber-attacks, offering a secure platform for health-monitoring applications. The chip secures users' data whilst running large artificial intelligence (AI) models efficiently, protecting sensitive health and financial information. The technology is capable of…

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