Study Note 84 Generative AI for NLP | by Edward Yang | Jun, 2025

Study Note 84 Generative AI for NLP

Evolution of Generative AI for NLP

– Started with rule-based systems following predefined linguistic rules

– Progressed to machine learning approaches using statistical methods

– Advanced to deep learning, utilizing artificial neural networks with extensive datasets

– Latest development is the transformer architecture, designed for sequential data processing

Applications of Generative AI in NLP

– Enhances machine translation accuracy with context-aware conversions

– Improves chatbot and virtual assistant interactions, making them more natural and empathetic

– Enhances sentiment analysis by grasping subtle language expressions

– Enables more precise text summarization by recognizing core meanings in documents

Large Language Models (LLMs)

– Foundation models using AI and deep learning with vast datasets

– Characterized by large training datasets (up to petabytes) and billions of parameters

– Examples include GPT series, BERT, BART, and T5

– Capable of understanding language structures, contexts, and generating creative content

Types of LLMs and Their Architectures

– GPT: Primarily a decoder, excels in generating coherent text

– BERT: Encoder-only architecture, exceptional at understanding context within sentences

– BART and T5: Encoder-decoder architecture, versatile for various NLP tasks

Differences between GPT and ChatGPT

– GPT focuses on diverse text generation, while ChatGPT specializes in conversations

– ChatGPT incorporates reinforcement learning from human feedback (RLHF)

Advantages and Considerations of LLMs

– Versatility allows for pretraining and fine-tuning for specific tasks

– Potential for generating authoritative-sounding but inaccurate information

– Need to address biases and consider societal impact of generated content

Impact on NLP Tasks

– Significant advancements in machine translation, chatbot conversations, sentiment analysis, and text summarization

– Enables more natural and human-like interactions in various applications