AI Dictionary › AI Fundamentals
Auto-miglioramento ricorsivo
Recursive self-improvement is the scenario in which an AI system improves its own ability to improve: each version designs the next, slightly more capable one, which in turn designs the one after. The result, in theory, is an acceleration that escapes human pace. The idea goes back to I. J. Good (1965) and sits at the center of the debate on the so-called intelligence explosion.
The laboratory version remains a hypothesis. The office version already exists, in miniature: the agent that rewrites its own prompts, updates its own instructions, builds itself new skills and reuses them. Each cycle starts from what the previous cycle produced, and a mistake that entered on the first pass grows stronger on every pass after, because nobody reads it from outside.
The operating rule: every change a system makes to itself needs a reader outside the loop. A version saved before the change, a comparison with the previous one, a person or a check that took no part in the change.
From our network
Magellano GPS: Fleet Tracking Made Simple
Real-time GPS tracking, remote engine lock, fuel and CO₂ reporting for your fleet.
Visit magellanogps.com →From the Agora Intelligence blog
Say what you mean. Get what you need.
Grace Certified, the AI coach that trains and certifies your prompt engineering, by Agora Intelligence.