Privacy

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a secure and efficient machine-learning accelerator. This would help avoid common cyber threats and ensure sensitive data, like health records and financial information, remain private while still enabling AI models to run on devices. The development represents a significant step in guaranteeing the security…

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator capable of maintaining user privacy while running large AI models efficiently on devices. Although it might increase device cost and reduce energy efficiency, lead author Maitreyi Ashok, an electrical engineering and computer science (EECS) graduate student at MIT, believes these are…

MIT and MIT-IBM Watson AI Lab researchers have invented a machine-learning chip resistant to the most common forms of cyberattacks. The technology caters to increasing demand for secure health-monitoring apps for individuals with chronic diseases or fitness goals, as well as for hardware-heavy uses such as autonomous vehicles and virtual reality. Health records and other…

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that can resist the two most common types of cyberattacks while maintaining the functionality of large Artificial Intelligence (AI) models, according to senior author Anantha Chandrakasan, MIT’s chief innovation and strategy officer, dean of the School of Engineering, and the Vannevar…

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that provides security against the two most common types of attacks. This chip can keep sensitive data, such as health records or financial information, private while allowing AI models to run efficiently on devices. The increased security doesn't affect the accuracy…

Researchers from the MIT-IBM Watson AI Lab and MIT have developed a secure machine-learning accelerator that can efficiently run large AI models while protecting user data. The device keeps user medical records, personal finance information, and other sensitive data confidential, and it is currently resistant to two of the most common security threats. The team…

Health-monitoring apps that use machine learning can be helpful in managing chronic diseases and fitness goals; however, they can also be slow and use a lot of energy. This is mainly due to machine learning models being shuttled between a smartphone and a central memory server. While machine-learning accelerators are often used to streamline computations,…

Researchers from MIT and the MIT-IBM Watson AI Lab have developed a machine-learning accelerator that provides strong data protection while allowing massive AI models to run effectively on individual devices. The innovations applied in developing the chip help protect sensitive information such as health records or financial data against common cyber-attacks, without negatively affecting the…

Researchers at MIT and the IBM Watson AI lab have developed a machine-learning accelerator chip which is more resilient to common types of cyber attacks. The chip is designed to protect sensitive user data, such as health records or financial information, whilst also enabling large-scale AI models to run efficiently on devices. The design of…

MIT and the MIT-IBM Watson AI Lab researchers have developed a machine-learning accelerator ingrained with defenses against the most common cyber-attacks. The device, which could find use in advanced AI applications like VR/AR and autonomous vehicles, offers robust security at the cost of increased power consumption and a slightly higher price tag. But maintaining optimum…

Researchers from MIT and the MIT-IBM Watson AI Lab have designed a machine-learning accelerator that can improve the security of health-monitoring apps. These applications can be slow and inefficient due to the large machine-learning models that need to be transferred between a smartphone and a central memory server. Instead, the team developed a chip that…

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…