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…
Researchers at MIT and the University of Washington have developed a computational model that can predict an intelligent agent's behaviors based on its "inference budget" (i.e. the limits on its computational resources). This was accomplished by using an algorithm that recorded all the decisions made by the agent within a given period of time. They…
Health-monitoring applications have become pivotal in managing chronic diseases and tracking fitness goals, largely due to the advent of machine-learning powered tools. However, these applications are often slow and energy-inefficient, largely due to the massive machine-learning models that require transfer between a smartphone and a central memory server. Despite the development of machine-learning accelerators that…
Researchers at MIT and the University of Washington have devised a model to predict the behaviour of AI systems and humans. The model factors in the indefinite computational constraints which may hinder an agent's problem-solving skills. By analysing only a few instances of previous actions, the model can predict an agent's future behaviour. The findings…
To build an Artificial Intelligence (AI) system that can work effectively with humans, it's critical to have an accurate model of human behavior. However, humans often act less optimally when making decisions, and these irrational behaviors are challenging to imitate. This is due to computational constraints - a person cannot dedicate decades to finding an…
Researchers from MIT and the University of Washington have developed a computational model to predict human behavior while taking into account the suboptimal decisions humans often make due to computational constraints. The researchers believe such a model could help AI systems anticipate and counterbalance human-derived errors, enhancing the efficacy of AI-human collaboration.
Suboptimal decision-making is characteristic…
Researchers at MIT and the University of Washington have successfully developed a model that can infer an agent's computational constraints from observing a few samples of their past actions. The findings could potentially enhance the ability of AI systems to collaborate more effectively with humans. The scientists found that human decision-making often deviates from optimal,…
A team of researchers from MIT and the MIT-IBM Watson AI Lab has developed a machine-learning accelerator that is resistant to the two most common types of cyberattacks. This ensures that sensitive information such as finance and health records remain private while still enabling large AI models to run efficiently on devices.
The researchers targeted…
MIT and University of Washington researchers have created a method to model both human and machine behaviours, taking into account unknown computational constraints which can limited problem-solving skills. The model infers an "inference budget" from previous actions. The inference budget can then predict the agent's future behaviour. Their technique can be used to predict navigation…
Health-monitoring apps can help individuals manage chronic diseases and keep up with their fitness goals. However, these apps can often be slow and energy-inefficient due to the machine-learning models they use, which need a significant amount of data shuffling between the smartphone and a central memory server. Engineers typically use hardware (machine-learning accelerators) to streamline…
Researchers at MIT and the University of Washington have developed a model that accounts for the sub-optimal decision-making processes in humans, potentially improving the way artificial intelligence can predict human behavior.
Named 'inference budget,' the model infers an agent's computational constraints, whether human or machine, after observing a few traces of their past actions. It…