- Natural Language Generation (NLG) focuses on predicting the next word or token in a sequence based on trained data probabilities.
- ChatGPT, a breakthrough in large language models (LLMs), combines Generative Pre-trained Transformers (GPT) with reinforcement learning via human feedback (RLHF).
- Key advancements in GPT-3.5 include RLHF and enhanced safety guardrails.
- Generative AI in enterprise use cases includes document processing, knowledge search, and conversational agents.
- LLM-based conversational agents differ from rule-based systems, offering more advanced responses.
- Retrieval-Augmented Generation (RAG) pipeline integrates data sources, NLP methods, and vector databases for enhanced query processing.
- LLMs face challenges like hallucinations, especially with outdated data, leading to the need for tools and agents to access current information.
- LLMs and agents are crucial in DeFi for analyzing transaction records, enhancing security, and automating workflows.
- LLM plugins like those from ChatGPT and DeFi Llama offer advanced analytics, investment insights, and transaction summaries.
- Potential LLM use cases in DeFi include smart contract analysis, converting complex terms into natural language, and community engagement through Q&A systems.
- Intent-based LLMs are fine-tuned for specific tasks, offering efficient and focused solutions in areas like blockchain and DeFi.
