More LLM-generated text about LLMs. Is anyone else actually finding it harder and harder to read LLM generated text? I find it quite tiring, my brain just does not want to get through it.
RAG Is Simpler Than You Think
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Re: RAG Is Simpler Than You Think
#42Re: RAG Is Simpler Than You Think
#43Re: RAG Is Simpler Than You Think
#44More LLM-generated text about LLMs. Is anyone else actually finding it harder and harder to read LLM generated text? I find it quite tiring, my brain just does not want to get through it.
It’s largely because LLMs are reaching for many different types of adjectives or verbs in the same sentence, in a jarring way. While embedding it in a confidently declarative sentence. Everything sounds like some profound insight, dialed to an 11, but written as poetry. Especially those headings. With the short sentences.
Re: RAG Is Simpler Than You Think
#45Agentic query rewrite on top of good old fashioned Lucene is the end game. This is effectively providing a lot of the same magic you get with the semantic approach. Allowing the agent to query the document store iteratively is where the capabilities become unbounded. Embeddings and semantic search add non determinism on top of non determinism. This seems fundamentally cursed. Lexical is much easier to control, iterat…
An LLM wrote this comment, no? I'm curious your motivation for having an LLM write such a short comment instead of writing it yourself?
Re: RAG Is Simpler Than You Think
#46Everyone keeps posting articles about how to implement RAG, but I also wonder why there isn’t some sort of skill to help people create a simple retrieval plan, starting with the retrieval methods and connecting them with evals. This could show whether they actually improve the result and make retrieval simpler for any agent, instead of making people start from zero.
Re: RAG Is Simpler Than You Think
#47Earlier quoted context omitted.
Can you elaborate? We have technicians searching in different languages. Also our knowledge base is often in different languages. I just don't see how full text search can work? Maybe in a problem space like a wiki where people always know what to search for?
Instinctively this feels like a two phase problem - start with some machine translation into a single spoken language and index that, then when people are querying do the same thing. When returning search results show them in the original language.
Re: RAG Is Simpler Than You Think
#48Earlier quoted context omitted.
Can you elaborate? We have technicians searching in different languages. Also our knowledge base is often in different languages. I just don't see how full text search can work? Maybe in a problem space like a wiki where people always know what to search for?
Instinctively this feels like a two phase problem - start with some machine translation into a single spoken language and index that, then when people are querying do the same thing. When returning search results show them in the original language.
Re: RAG Is Simpler Than You Think
#49I worked on large scale RAG systems before and can say people vastly underestimate full text search and vastly overestimate embeddings. FTS is really easy, portable and scalable and gets you very far, the 80/20 rule applies. Embeddings appear to be nice and magic but when you really get into them you notice: semantic similarity isn’t as good as you think and certainly it won’t make everyone happy. You will inevitably…
Can you elaborate? We have technicians searching in different languages. Also our knowledge base is often in different languages. I just don't see how full text search can work? Maybe in a problem space like a wiki where people always know what to search for?
Re: RAG Is Simpler Than You Think
#50Earlier quoted context omitted.
A hyperlink to Wikipedia would have solved that issue.
Maybe if a person can't even google RAG they are not the intended audience of that article.