Artificial intelligence and machine learning: Shaping the future of computing with significant real-world potential

Le résumé fourni par la source

This paper aims to investigate the transformative role of artificial intelligence (AI) and machine learning (ML) in the context of the future of computing and explore real-world applications affecting various industries. By examining the technologies of AI and ML, their key concepts, and the history of development, the paper reveals their high potential to transform sectors, such as healthcare, manufacturing, agriculture, and smart cities. In addition, the paper explores the development and assessment of AI-based systems for hazard prediction in a chemical laboratory as an example to manifest the practical implications of the technologies and the added business value. The analysis of the performance metrics of the ML models’, such as accuracy, precision, recall, Fl score, and the area under the receiver operating characteristic curve points to their ability to predict actuation responses based on sensor data. In the course of research, the artificial neural networks (ANNs) model is recognized as the most optimal solution for real-time application and proves to be more accurate and reliable compared to decision tree (DT) and support vector machines (SVM). Moreover, the findings discovered during the experiment illustrate the overall power of AI and ML to boost innovation, efficiency, and sustainability across different industries, affirming that ethical considerations are manageable in combination with driving inclusivity. Thus, the paper emphasizes the implications of AI and ML for the computing of the future which can result in the smarter, better connected, and more resilient future ahead.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.