AI RESEARCH
Interestingness as an Inductive Heuristic for Future Compression Progress
arXiv CS.LG
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ArXi:2605.14831v1 Announce Type: cross One of the bottlenecks on the way towards recursively self-improving systems is the challenge of interestingness: the ability to prospectively identify which tasks or data hold the potential for future progress. We formalize interestingness as an inductive heuristic for future compression progress and investigate its predictability using tools from Kolmogoro Complexity and Algorithmic Statistics.