Retrieval Augmented Generation (RAG) Explained: Understanding Key Concepts
If all of these research ambitions were to come to fruition, the resulting system would be a very early version of the system that we envisioned in the introduction. That is, the resulting system would be able to provide domain expert answers to a wide range of information needs in a way that neither modern IR systems, question answering systems, o... See more
Donald Metzler • Rethinking Search: Making Domain Experts out of Dilettantes
The CoD prompt instructs highly powered LLMs such as GPT-4 to produce an initial sparse, verbose summary of an article containing only a few entities. It then iteratively identifies 1–3 missing entities and fuses them into a rewrite of the previous summary in the same number of words.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
By incorporating outside knowledge, RALMs generate text that is more useful, nuanced, and factually correct.
Ben Auffarth • Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
So right now, LLMs (Large Language Models) are all the rage. But in the future, it’s possible that the way we get things done is composing things with a combination of LLMs, SMMs (Small, Mighty Models), agents and tools.
It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).
This is how we... See more
It’s what I call Cognitive Composition (because it sounds cool and I have a longtime love affair with alliteration).
This is how we... See more