Artificial Intelligence as A Learning Strategy in Higher Education

Abstract

The article focuses on the use of DALL-E, an artificial intelligence system created by OpenAI, for the identification of virus structures. The accurate identification of these structures is essential for understanding and effectively treating diseases. Unlike traditional methods, artificial intelligence offers novel solutions. This tool employs deep learning algorithms and text-based image generation techniques to create customized images from detailed descriptions. This allows users to generate specific images that fit their needs, saving time and costs associated with manual image creation. Furthermore, DALL-E can combine concepts, styles, and attributes to create unique and diverse images. The application of this tool in virus structure identification offers several advantages, such as the ability to generate realistic and detailed images, explore a wide variety of styles and designs, and promote creativity and accessibility in the field of healthcare. However, further research and validation are required to fully evaluate its effectiveness and accuracy. The application in virus structure identification through artificial intelligence represents an innovative and promising perspective in the field of health. This technological advancement has the potential to improve the understanding and treatment of diseases by providing healthcare professionals with more efficient and precise tools to combat infectious diseases.