Classical Natural Language Processing (NLP) techniques often rely on hand-crafted rules, statistical methods, and simpler machine learning algorithms to process and understand text. These methods are limited in their ability to handle the complexity and variability of human language. However, the advent of Large Language Models (LLMs) like GPT-3 and GPT-4 has revolutionized the field. LLMs use deep learning and vast amounts of data to learn language patterns, enabling them to generate coherent text, understand context, and perform a wide range of NLP tasks with unprecedented accuracy and flexibility. This shift has upended classical NLP by providing more powerful and generalizable solutions, making manual rule creation and simpler algorithms largely obsolete.
Many professors and leaders in the NLP literally woke up one morning to find themselves obsolete in a world of CHATGPT!
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