Large Language Model

Gene editing, a vital aspect of modern biotechnology, allows scientists to precisely manipulate genetic material, which has potential applications in fields such as medicine and agriculture. The complexity of gene editing creates challenges in its design and execution process, necessitating deep scientific knowledge and careful planning to avoid adverse consequences. Existing gene editing research has…

Large Language Models (LLMs) represent a significant advancement across several application domains, delivering remarkable results in a variety of tasks. Despite these benefits, the massive size of LLMs renders substantial computational costs, making them challenging to adapt to specific downstream tasks, particularly on hardware systems with limited computational capabilities. With billions of parameters, these models…

Generative artificial intelligence's (AI) ability to create new text, images, videos, and other media represents a huge technological advancement. However, there's a downside: generative AI may unwittingly infrive on copyrights by using existing creative works as raw material without the original author's consent. This poses serious economic and legal challenges for content creators and creative…

Large language models (LLMs) are increasingly in use, which is leading to new cybersecurity risks. The risks stem from their main characteristics: enhanced capability for code creation, deployment for real-time code generation, automated execution within code interpreters, and integration into applications handling unprotected data. It brings about the need for a strong approach to cybersecurity…