In this article, we showcase a powerful new query engine ( SQLAutoVectorQueryEngine ) in LlamaIndex that can leverage both a SQL database as well as a vector store to fulfill complex natural language queries over a combination of structured and unstructured data. This query engine can leverage the expressivity of SQL over structured data, and join it with unstructured context from a vector database. We showcase this query engine on a few examples and show that it can handle queries that make use of both structured/unstructured data, or either.
Check out the full guide here: https://gpt-index.readthedocs.io/en/latest/examples/query_engine/SQLAutoVectorQueryEngine.html.
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Daily Archives: May 29, 2023
Falcon: New Open Source LLMs
A PhD Student’s Perspective on Research in NLP in the Era of Very Large Language Models
Recent progress in large language models has enabled the deployment of many generative NLP applications. At the same time, it has also led to a misleading public discourse that “it’s all been solved.” Not surprisingly, this has in turn made many NLP researchers — especially those at the beginning of their career — wonder about what NLP research area they should focus on. This document is a compilation of NLP research directions that are rich for exploration, reflecting the views of a diverse group of PhD students in an academic research lab. While we identify many research areas, many others exist; we do not cover those areas that are currently addressed by LLMs but where LLMs lag behind in performance, or those focused on LLM development. — Read More
Lawyer cites fake cases invented by ChatGPT, judge is not amused
Legal Twitter is having tremendous fun right now reviewing the latest documents from the case Mata v. Avianca, Inc. (1:22-cv-01461). Here’s a neat summary:
So, wait. They file a brief that cites cases fabricated by ChatGPT. The court asks them to file copies of the opinions. And then they go back to ChatGPT and ask it to write the opinions, and then they file them?
– Beth Wilensky, May 26 2023
Here’s a New York Times story about what happened. — Read More
An Elo Style Leaderboard for Language Models
We use the Elo rating system to calculate the relative performance of the models. Elo is a method for calculating the relative skill levels of players in zero-sum games, which was invented as an improved chess-rating system. The difference in the ratings between two models serves as a predictor of the model’s relative performance.You can view the voting data, basic analyses, and calculation procedure in this notebook. We will periodically release new leaderboards. — Read More
You can compare models’ relative performance for yourself, or add new models, here.
Rick's Cafe AI 