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…
Large language models (LLMs) act as powerful tools for numerous tasks but their utilization as general-purpose decision-making agents poses unique challenges. In order to function effectively as agents, LLMs not only need to generate plausible text completions but they also need to show interaction and goal-directed behaviour to complete specific tasks. Two critical abilities required…
Artificial Intelligence (AI) and Machine Learning (ML) technologies have shown significant advancements, particularly via their application in various industries. Autonomous agents, a unique subset of AI, have the capacity to function independently, make decisions, and adapt to changing circumstances. These agents are vital for jobs requiring long-term planning and interaction with complex, unpredictable environments. A…
The increased use and reliance on artificial intelligence (AI) systems have come with its share of benefits and risks. More specifically, AI systems are considered vulnerable to cyber-attacks, often resulting in harmful repercussions. This is mainly because their construction is complex, their internal processes are not transparent, and they are regularly targeted by adversarial attacks…
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…
MIT and University of Washington researchers have developed a model to understand and predict human behavior, which could improve the effectiveness of AI systems in collaboration with humans. Recognizing the suboptimal nature of human decision-making often due to computational constraints, the researchers created a model that factors in these constraints observed from an agent's previous…
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…
The alarming phenomenon of AI model collapse, which occurs when AI models are trained on datasets that contain their outputs, has been a major concern for researchers. As such large-scale models are trained on ever-expanding web-scale datasets, concerns have been raised about the degradation of model performance over time, potentially making newer models ineffective and…