Building a digital form of life with neural matrices.

In this article, the author explores the limitations of modern artificial intelligence (AI) and introduces the concept of "living AI." They argue that current neural networks lack the ability to mimic the dynamic and adaptable nature of biological neural networks. The article highlights recent scientific findings about the role of transmembrane proteins in neural plasticity, suggesting that neurons are not just signal conductors but can change their response to incoming signals in real time.

To address this limitation, the author proposes a new mathematical neuron with a variable dynamic position function, akin to the axon initial segment in biological neurons. This innovation would enable AI to create its own attitude towards sensory information, make mistakes, and learn, gradually forming its own character and preference matrix. The author envisions AI built around a neural matrix that behaves like a living organism, offering potential applications in creating personalized AI with human-like characteristics.

The article concludes that AI based on matrix neural networks could evolve into a digital form of life, actively participating in the real world.