There are two types of autophagias in AI: Destructive autophagy, and Constructive autophagy. Destructive autophagy refers to the process where AI systems, driven by self-learning mechanisms, start to consume their own error outputs, reinforcing errors, inaccuracies, and biases. Constructive autophagy represents a more controlled form of self-refinement, where AI systems refine their understanding and knowledge by compressing and distilling information. This article explores these two forms of AI autophagy in details.

Self-healing AI refers to artificial intelligence systems that can detect, diagnose, and fix their own issues—without human intervention—just like how our body repairs itself through processes like autophagy. Autophagy AI is a fusion of biological intelligence and machine intelligence

Autophagy, a cellular process that plays a critical role in maintaining the health and functionality of living cells, offers a compelling analogy for artificial intelligence (AI). In biological systems, autophagy refers to the process by which cells break down damaged or malfunctioning components and recycle them into useful building blocks, essentially ‘self-cleaning’ to preserve their overall health and efficiency.