The article provides an overview of key terms in the field of artificial intelligence, explaining that AI is a broad research area encompassing methods that enable machines to perform human-like tasks, a concept first coined by John McCarthy in 1956 and discussed earlier by Alan Turing. Machine learning (ML), a subset of AI, allows computers to learn from data without explicit programming, as described by Arthur Samuel in 1959. A more technical definition by Tom Mitchell highlights the improvement of a program's performance based on experience. Deep learning (DL), a more recent and popular subset of ML, involves neural networks with multiple layers, facilitated by advances in processing power and data availability. The article notes that DL gained prominence after the success of the AlexNet architecture in the 2012 ImageNet competition and has since been applied in various fields, including translation, speech recognition, computer vision, and bioinformatics, among others, marking a significant advancement in AI capabilities.