11. Natural Language Processing and Deep Learning

This explores the challenges and recent advancements in natural language processing (NLP), a field of artificial intelligence focused on enabling computers to understand and use human language. The text uses a simple restaurant story to illustrate the complexities of language understanding, highlighting the need for sophisticated linguistic skills and world knowledge in AI systems. It then details the significant progress made in speech recognition using deep learning, contrasting this success with ongoing challenges in tasks like sentiment classification and question answering. The chapter introduces recurrent neural networks (RNNs) and word embedding techniques like Word2Vec, explaining how these methods represent words numerically to improve NLP performance, while acknowledging the presence of societal biases within these models. Finally, the text discusses the potential for encoding entire sentences and documents as vectors to further enhance semantic understanding.