Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
Ben Auffarthamazon.com
Generative AI with LangChain: Build large language model (LLM) apps with Python, ChatGPT, and other LLMs
These new types of AI, called Large Language Models (LLMs), are still doing prediction, but rather than predicting the demand for an Amazon order, they are analyzing a piece of text and predicting the next token, which is simply a word or part of a word. Ultimately, that is all ChatGPT does technically—act as a very elaborate autocomplete like you
... See moreEthan Mollick • Co-Intelligence: Living and Working with AI
Rather than using these tools in isolation, I've connected them into a seamless ecosystem. I use Perplexity and ChatGPT’s o3 to research topics, import findings into NotebookLM where I can analyze patterns across multiple sources, then summarize everything in Google Docs connected to Claude's Project Knowledge.
Wyndo • I Stopped Chasing AI Tools and Started Building AI Spaces, Here's What I Learned
1. Synthetic Data for Baseline Metrics¶
Synthetic data can be used to establish baseline precision and recall metrics for your reverse search. The simplest kind of synthetic data is to take existing text chunks, generate synthetic questions, and verify that when we query our synthetic questions, the sourced text chunk is retrieved correctly.
Benefi... See more
Synthetic data can be used to establish baseline precision and recall metrics for your reverse search. The simplest kind of synthetic data is to take existing text chunks, generate synthetic questions, and verify that when we query our synthetic questions, the sourced text chunk is retrieved correctly.
Benefi... See more
Low-Hanging Fruit for RAG Search - jxnl.co
