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…
From the search for a new recipe, a restaurant, a fashionable outfit, or an understanding of a particular topic, humans are innately curious creatures, always in pursuit of something. This constant quest for knowledge or new experiences is not only limited to physical search, but has significantly permeated different aspects of online platforms, since the…
The field of large language models (LLMs) is developing at a rapid pace due to the need to process extensive text inputs and deliver accurate, efficient responses. Open-access LLMs and proprietary models like GPT-4-Turbo must handle substantial amounts of information that often exceed a single prompt’s limitations. This is key for tasks like document summarisation,…
As AI systems continue to advance, researchers and policymakers are concerned about ensuring their safe and ethical use. The main issues center around the potential risks posed by ever-evolving and increasingly powerful AI systems. These risks involve potential misuse, ethical issues, and unexpected consequences stemming from AI's expanding abilities. Several strategies are being explored by…