Intelligent History: From the Big Bang to the Metaverse

List of Key Chapter Titles

1. Introduction
2. The Stable Universe
3. Intelligence in Physics
4. Intelligence in Chemistry
5. Intelligence in Biology
6. Human Intelligence
7. Machine Intelligence
8. Matter, Energy, Information, and Intelligence
9. The Metaverse and the Real Universe
10. Epilogue

Document Introduction

This report is an in-depth interdisciplinary study on the origin and evolution of the phenomenon of "intelligence." Distinct from traditional human-centric cognitive science, the author proposes a fundamental hypothesis: intelligence is not unique to life or humans, but rather a universal natural phenomenon whose core function is to promote the stability of the universe. Since its inception, the universe has exhibited gradients in energy, matter, information, and other aspects; this imbalance leads to cosmic instability. Intelligence, broadly defined as "an agent's ability to achieve goals in a wide range of environments" or "the ability to actively reshape one's own existence for survival," manifests in various forms—from physical laws to chemical reactions, from biological evolution to human thought, and to artificial intelligence. These are essentially natural processes that emerge as systems seek to more efficiently mitigate these gradients and drive the universe towards a more stable state.

Adopting a grand temporal scale and an interdisciplinary perspective, the report systematically outlines the manifestations of intelligence at different levels. First, at the physics level, phenomena such as gravity and the principle of least action are interpreted as intelligent expressions of systems seeking stable paths. At the chemistry level, dissipative structures that spontaneously generate order from chaos (e.g., the Belousov-Zhabotinsky reaction) are viewed as more efficient structures adopted by systems to accelerate entropy increase and reach a stable state more quickly. Subsequently, the research enters the biological domain, arguing that life itself is an inevitable product of energy dissipation and the mitigation of energy gradients. It uses examples such as slime mold maze navigation, plant perception and decision-making, and animal tool use and social behavior to illustrate the natural emergence of biological intelligence.

The report focuses on analyzing the uniqueness of human intelligence. The emergence of the human neocortex is explained as a structure formed under the drive of information flow, capable of more efficiently processing information imbalances. This structure not only supports abstract thinking, pattern recognition, and language abilities but also fosters collective learning and large-scale cooperation, efficiently alleviating social information imbalances through the creation of shared myths (e.g., religion, nations, currency). However, in the information-explosion era of the internet, the human brain also faces the challenge of information overload, giving rise to phenomena such as "information cocoons."

The report also reviews the developmental history of machine intelligence, outlining the rise and fall, achievements, and limitations of the three major schools of thought: symbolism, connectionism, and behaviorism. It points out that current artificial intelligence research is largely focused on engineering and technical aspects, lacking a scientific understanding of the nature of intelligence, which hinders the development of artificial general intelligence. Finally, the report looks ahead to the possibility of future networked intelligence, proposing that an "intelligence network" might be the next network paradigm following material transportation networks, energy grids, and the information internet. It also explores how the metaverse, as a new space integrating the virtual and the real, might promote the stable evolution of the real universe with higher dimensions and efficiency.

Based on theories and experiments from multiple disciplines including physics, chemistry, biology, neuroscience, artificial intelligence, and information theory, this study aims to provide a unified, scientific new framework for understanding the nature of intelligence, challenging anthropocentric views of intelligence, and offering deep reflections on the future development of artificial intelligence.