New preprint links intelligence to learnable novelty across machine learning and complex systems
drmichaellevin · x · 2026-07-22
- A new preprint, “Intelligence from Learnable Novelty,” argues that seemingly different notions of intelligence across statistics, machine learning, complex systems, and agent behavior can be unified by a single principle: the pursuit of learnable novelty.
- The authors derive a closed-form approximation of Epiplexity and claim it reveals a deep connection between Epiplexity and intelligence.
- By maximizing Epiplexity in different systems, they report interesting emergent behaviors, including complex soliton interactions in cellular automata and effects in image encoders.
- The thread suggests the paper offers a new lens for thinking about intelligence, novelty, and objective functions across disciplines.
Related event: New Paper Unifies Intelligence Concepts via Learnable Novelty(7 posts)→
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