Intelligent History: From the Big Bang to the Metaverse

Key Chapter Title List

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. Metaverse and the Real Universe
10. Epilogue

Document Introduction

This report is an interdisciplinary, in-depth 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 exclusive to life or humans, but is a universal natural phenomenon whose core role is to promote the stability of the universe. Since its inception, the universe has had gradient distributions 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 to actively reshape its 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 toward a more stable state.

From a grand temporal scale and interdisciplinary perspective, the report systematically outlines the manifestations of intelligence at different levels. First, at the physics level, phenomena such as universal gravitation 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 seen as more efficient structures adopted by systems to accelerate entropy increase and reach a stable state more quickly. Subsequently, the research enters the field of biology, arguing that life itself is an inevitable product of energy dissipation and gradient mitigation. Using examples such as slime mold navigating mazes, plant perception and decision-making, and animal tool use and social behaviors, it demonstrates 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 processing information imbalances more efficiently. This structure not only supports abstract thinking, pattern recognition, and language abilities but also fosters collective learning and large-scale cooperation by creating shared myths (such as religion, nation-states, and currency) to efficiently alleviate social information imbalances. However, in the information-explosion era of the internet, the human brain also faces challenges like information overload, giving rise to phenomena such as information cocoons.

The report also reviews the history of machine intelligence, outlining the rise and fall, achievements, and limitations of the three major schools: symbolism, connectionism, and behaviorism. It points out that current artificial intelligence research is mostly focused on engineering and technical aspects, lacking a scientific understanding of the nature of intelligence, which constrains the development of Artificial General Intelligence (AGI). Finally, the report looks ahead to the possibility of future networked intelligence, proposing that an intelligence network could be the next paradigm following material transport networks, energy grids, and the information internet. It explores the metaverse as a new space integrating virtual and real worlds, potentially promoting 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.