Data

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…