Comment by gibsonf1
9 hours ago
The problem is that the relational database of tables has no relationship to how humans store information, we humans use graph structures to relate information. This is why RDBMS are a dead end in getting closer to understanding.
This is a system for teaching undergrad students how RDBMS work, not a DBMS for modeling human understanding.
A machine that makes ravioli also works in an unhumanlike manner. A tool should follow the tool's way, not human way.
Besides, I'd say that it's not quite clear how we store information. I myself would point to sets as to a worthy contender.
Relational algebraic model (which SQL is a debased form of) is literally based on propositional logic. Or at least that's the claim. Propositional & predicate logic is evidently part of human language, grammar, and present in human thinking systems. Though it would be -- as you are intimating -- insane hubris to make one singular claim about how the brain represents knowledge.
Commenter is self-promoting their "graph DB" related product.
Funny enough, GFQL (oss cypher on CPU/GPU dataframes, no DB needed) runs optimized graph queries with the usual CSR-like indexes... But underlying data is columnar as in duckdb. Likewise, for fast billionscale perf on single node, maps graph compute to pure vector ops. Storage, data representation, & reasoning are largely separated concepts.
Giant citation needed. This is completely unsubstantiated. And contrary also to whole schools of epistemology. Also nothing to do with TFA.
"Yeah, well, you know, that's just, like, your opinion, man"