Crypto Merges with AI Finance: A Convergence Driven by Mathematical Asymmetry

Crypto and AI are two seemingly unrelated fields - one generates text and code using algorithms, while the other facilitates transactions on blockchain.

However, upon closer inspection, they share a common foundation: both rely on mathematical asymmetry to function.

AI uses this asymmetry to create cognitive functions, while crypto leverages it to establish trust.

The author argues that the proximity of these two fields is not a business choice but rather an inevitability, with their convergence being only a matter of time.

The first principle behind this convergence lies in the use of the same mathematical asymmetry - one creates cognition, while the other creates trust.

This asymmetry is rooted in complexity theory and modern cryptography: some problems are hard to solve but easy to verify.

Crypto's proof-of-work (PoW) mechanism exemplifies this principle, requiring immense computational power to find a valid block header yet only two SHA-256 hashes for verification.

A similar asymmetry is observed in AI, where training a model requires significant computational resources, but executing the resulting predictions is relatively inexpensive.

The author concludes that since both AI and crypto rely on this mathematical asymmetry, they are inherently connected and will eventually merge.