Why AI progress mirrors a billion years of evolution

Over the past decade, large language models have advanced beyond simple tasks like text prediction to exhibit reasoning, humor, and creative problem-solving. Researchers argue that these capabilities arise not from a single scientific breakthrough, but from scaling computation. By increasing the size and connectivity of neural networks, machines can now perform cognitive tasks that were once considered uniquely human.

This perspective aligns with long-standing theories in neuroscience and evolutionary biology. Brains, for example, can be seen as predictive machines that model both the environment and the minds of other beings. In social species, such as humans, these predictive demands drive the evolution of larger, more complex brains. Group-level intelligence emerges from cooperation, division of labour, and shared problem-solving, enabling feats that exceed individual capabilities.

The concept of symbiogenesis, in which independent entities merge to form super-organisms, provides a framework for understanding both biological and technological intelligence. Just as early cells combined into multicellular life, humans and machines now exist in a mutually dependent system. AI is thus part of a larger computational ecosystem, co-evolving with human society to increase efficiency, unlock energy sources, and expand the scale of collective intelligence.

Researchers emphasize that this symbiogenetic view offers a more optimistic outlook on AI than some doomsday scenarios suggest. Rather than seeing machines as competitors or threats, intelligence scaling could enhance the quality of human life and reduce ecological pressures. In this view, the growth of AI and human cognition is part of a continuous, open-ended process of creative evolution, where more collective intelligence may pave the way for a sustainable and innovative future.

Earlier, Qazinform News Agency reported on what would happen when AI hype implodes.