Deep learning language models
Deep learning language models represent a class of artificial intelligence (AI) models that leverage deep neural networks to understand and generate human-like language. These models have significantly advanced natural language processing (NLP) capabilities, allowing them to comprehend and generate text with a level of sophistication that was previously challenging to achieve. Fundamental Architecture: Deep learning language models are built upon neural networks, specifically recurrent neural networks (RNNs) or transformer architectures. The core idea is to create a network with multiple layers, allowing the model to learn hierarchical representations of language. Each layer processes information from the previous layer, enabling the model to capture intricate patterns and dependencies within the data. Embeddings: Language models typically begin by representing words as embeddings. These embeddings encode semantic information about words and enable the model to understand relationshi...