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Ask HN: How to measure how much data one can effectively process or understand?

12•mbuda•3h ago
Is there a scale of how much data one can effectively process, something similar to the "Kardashev scale for data"? What would be a name for such a thing? During Memgraph's Community Call (https://youtu.be/ygr8yvIouZk?t=1307), the point is that AgenticRuntimes + GraphRAG moves you up on the "Kardashev scale for data" because you suddenly can get much more insight from any dataset, and everyone can use it (a large corporation does not control it). I found something similar under https://adamdrake.com/from-enterprise-decentralization-to-tokenization-and-beyond.html#productize, but the definition/example looks very narrow.

Comments

mbuda•3h ago
Here are clickable links: https://youtu.be/ygr8yvIouZk?t=1307, https://adamdrake.com/from-enterprise-decentralization-to-to...
kellkell•30m ago
The Kardashev scale measures energy control, not information processing. If we were to define a “Kardashev scale for data,” it wouldn’t be about raw volume, but about effective abstraction capacity.

Humans don’t process data directly — we process compressed representations. So a meaningful scale would measure:

1- Throughput — how much structured data an agent can analyze per unit time.

2- Compression efficiency — how much insight is extracted per unit of data.

3- Relational depth — how many meaningful relationships can be modeled simultaneously.

Tools like Agentic Runtimes + GraphRAG don’t just increase data volume access — they expand relational modeling capacity and contextual memory. In that sense, they move users up a scale of informational leverage, not just scale of data.

mbuda•6m ago
Yep, amazing points!

Agree with the measures; follow-up question: what's the insight definition? I think exposing some of those measures would help people better understand what the analysis covered, in other words, how much data was actually analyzed. Maybe an additional measure is some kind of breadth (I guess it could be derived from the throughput).

"Informational leverage" reminded me of "retrieval leverage" because yeah, the scale of data didn't change, the ability to extract insights did :D

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