LLMs Are Not All You Need | Pinecone
updated 1y ago
LLMs Are Not All You Need | Pinecone
- 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 morefrom Shortwave — rajhesh.panchanadhan@gmail.com [Gmail alternative]
Nicolay Gerold added
- AutoGen's design offers multiple advantages: a) it gracefully navigates the strong but imperfect generation and reasoning abilities of these LLMs; b) it leverages human understanding and intelligence, while providing valuable automation through conversations between agents; c) it simplifies and unifies the implementation of complex LLM workflows as... See more
from r/singularity - Reddit
Nicolay Gerold added
Chaining LLM Agents instead of LLM calls. Seems like a pretty heavy prompt engineering effort. They are pushing for agents that are specialized in a certain tasks through RAG / finetuning, where CAMEL and other frameworks failed. One interesting area for exploration might be finetuning LLMs for collaboration before finetuning them for tasks. - LLM agents rely on their Long-Term Memory (LTM) to store and retrieve crucial memories. Conversations, thoughts, plans, actions, observations, skills, and behaviors are all stored within a vector database. The LTM enables pre-processing and post-processing of memories, ensuring optimal retrieval. By considering factors such as context, recency, imp... See more
from Introducing our work on general-purpose LLM Agents | GoodAI
Nicolay Gerold added