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Until recently, it was just a fascinating theory, known among a select few as “Gödel’s Machines”. It was a kind of the Holy Grail of computer science: a hypothetical, perfect AI that could solve any problem optimally, and first mathematically prove the changes in its own code.
It was this very last “proof” requirement that turned out to be the Achilles’ heel of the whole concept. Because in practice, proving that a minor change in millions of lines of code will definitely bring improvement is almost an impossible task. For decades, the idea of a fully self-improving AI remained in the realm of dreams.