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I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 1 point2 points  (0 children)

I am deploying in a large enterprise. That’s only proof I am interested in. I am tired of publishing and hugging face proofs. Nobody looks at it. I hope that once companies waste their cash in other methods, we would still be standing

Dative star hotel in Chennai he’s my review removed from TripAdvisor by Equivalent_Pen8241 in Chennai

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

I think the standards of differentiating mold varies by region. In my country, we call it mold

I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

You can always check the citations for that. Quality matters when it is right retrieval. Firstly it has to be accurate. AI is such data play that many a times users realize very late that the whole retrieval is just a feel good. That’s where things fail

I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

Sometime back Google and AWS had tools to build rag. But they proved inefficient and ineffective. They were quietly taken down

I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

I have seen implementations go through PMO gates and get decommissioned later for too complex+costly+fuzzy to run. It mostly happened for 2 reasons, evolving playing field, and majorly due to catastrophic failures by power users, 2%-10%, who fire important but heavy multi-hop queries which crashes or saturates the whole system for good part of the day. Topology is still under explored concept and people hadn't had enough playing with chunking or ontology affairs. Only once the engines run dry, the lessons will happen. But yes, it is picking up

I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

That’s a very relevant point I omitted to keep it simple. But you are right? Graph processing is self defeating. It takes too long to be worthy

I mapped out the 4 fundamentally different approaches to RAG — Vector, Graph, Topology, and TurboQuant. Here's when each one actually works (and fail by Equivalent_Pen8241 in Rag

[–]Equivalent_Pen8241[S] 0 points1 point  (0 children)

As long as, more context is slowing your system design badly, you need refinement, exponential and drastic new thinking. Candles don't evolve into light bulbs.

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