LLM extraction can confuse implication, motivation, analogy and true formal dependency.
A possibility worth exploring ●
Theorem Dependency Intelligence
A machine-readable graph showing which theorems, algorithms and claims depend on open conjectures, assumptions or formal lemmas.
The possibility
A machine-readable graph showing which theorems, algorithms and claims depend on open conjectures, assumptions or formal lemmas.
A breakthrough changes more than one page: it can alter the status of a network of conditional results.
When an assumption changes status, the graph can recalculate affected results and route users to the exact evidence.
What to keep in mind
What stands between here and there?
Every dependency must retain provenance and review state; an AI-inferred edge is not a verified theorem dependency.
Riemann Hypothesis
Many results are explicitly conditional on RH or related hypotheses.
Understand the question →P versus NP
Algorithms and security claims depend on precise complexity assumptions.
Understand the question →Twin Prime Conjecture
Bounded-gap results must be distinguished from the exact twin-prime target.
Understand the question →Ideas it sparks
Ways to start thinking today.
These are prompts for curiosity—not roadmaps or promises.
Theorem Dependency Auditor
Extract and review explicit dependency edges such as “assuming RH,” “uses bounded gaps,” or “requires this lemma,” with citations and review states.
Yes, with AI-assisted extraction plus expert or community correction.
Sources and uncertainty 5
AI summarized and source-backed · Qualified expert review pending.