← All IntelClip / AI ToolsBenchmarking retrieval shapes against vector search
From AI on Your Lakehouse: Context Comes in Shapes, Not Queries — Zach Blumenfeld, Neo4j · ≈1:55:33
“I haven't run any specific benchmarking on like exactly what I've shown you today.”
“Here for this course this is more conceptual to understand kind of like the different shapes that you would use to help ground your data.”
What’s in it
- Explains why knowledge-graph accuracy wasn't formally benchmarked in this demo
- Shows how real customers test custom ontologies against vector search
- Frames this segment as conceptual, not an empirical performance study
Clip transcript
Do do I have a sense of accuracy of how well these do when the knowledge bases expand? Um, for this I haven't run any specific benchmarking on like exactly what I've shown you today. But I will say that when we do have customers that run these, they'll often come up with their own custom ontologies and then they will run benchmarks uh that will basically say like how effective is this query pattern against you know ordinary vector search for example and you would use that to prove it out on on a specific type of data set. Here for this course this is more conceptual to understand kind of like the different shapes that you would use to help ground your data. Um, and it can always use work in terms of how you were to like build the skill, right? To make sure it guides through the right thing so it uses, you know, each step efficiently essentially.
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