Building upon the foundational principles of the attention mechanism discussed in the previous section, the Transformer architecture represents a paradigm shift by leveraging attention exclusively, completely replacing the recurrent structures that once dominated sequence modeling. This architectural innovation, first unveiled by Vaswani et al. (2017), has since catalysed a seismic
The transformative potential of Natural Language Processing (NLP), as a cornerstone of artificial intelligence, lies in its ability to enable machines to understand and generate human language, facilitating advanced human-computer interaction and knowledge extraction. However, the complexity of human language presents significant obstacles, particularly in managing linguistic ambiguity, contextual nuances,
The evolution of learning machines, a cornerstone of Artificial Intelligence (AI), represents one of the most transformative developments in modern science and technology. From rudimentary rule-based systems to sophisticated pattern recognition models capable of processing vast datasets, the trajectory of AI reflects both technological innovation and shifting conceptual paradigms. Defining
Having examined the diverse definitional approaches to AI, we now turn to the historical trajectory that has shaped these conceptual frameworks. The theoretical foundations discussed above—particularly Turing's behavioural criterion and the Dartmouth Conference's formalisable intelligence hypothesis—provided the intellectual scaffolding for AI's subsequent
