-
emerging-trajectories
Open source framework for using LLMs to forecast political, economic, and social events.
-
-
InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
RAG will have a place in the LLM world, since it's a way to obtain data/facts/info for relevant queries.
Since you asked about alternatives...
(a) "World models" where LLMs structure information into code, structured data, etc. and query those models will likely be a thing. AlphaGeometry uses this[1], and people have tried to abstract this in different ways[2].
(b) Depending on how you define RAG, knowledge graphs could be a form of RAG or alternatively an alternative to them. Companies like Elemental Cognition[3] are building distinct alternatives to RAG that use such graphs and give LLMs the ability to run queries on said graphs. Another approach here is to build "fact databases" where, you structure observations about the world into standalone concepts/ideas/observations and reference those[4]. Again, similar to RAG but not quite RAG as we know it today.
[1] https://deepmind.google/discover/blog/alphageometry-an-olymp...
[2] https://arxiv.org/abs/2306.12672
[3] https://ec.ai/
[4] https://emergingtrajectories.com/
Fast changing libraries are a huge pain. That's why a no-code approach like Unstract (https://github.com/zipstack/unstract) makes sense.
Related posts
-
Large language models (e.g., ChatGPT) as research assistants
-
Long-form factuality in large language models
-
Ask HN: What are some actual use cases of AI Agents?
-
Show HN: LLMWhisperer – Prep complex documents ready for use in LLMs
-
RAGFlow is an open-source RAG engine based on deep document understanding