The Path Toward Embodied AI & AGI: IBB Integral Ontology (Vol. I): 通往具身智能与AGI之道: IBB一体本智 (上卷）

This visionary book confronts the defining question beyond today’s AI revolution:
Which of those emerging models (VLA, JEPA, World-Action etc) can realize Embodied General Intelligence, that leads to AGI? Or specifically, after a robot acquires the power to know through LLMs, how can knowing enter its body (embodiment), initiate action, learn through consequence, and evolve toward true general intelligence?

Unlocking Cognitive Intelligence revealed how AI moves from processing what is known toward exhibiting the power to know—and why cognition must become embodied before knowing can become action.

Unlocking Embodied Intelligence & Rehabilitation revealed that true embodied capability cannot simply be installed from outside; it must be regenerated and cultivated from within through IBB—Intention, Body, and Behavior as One. Rehabilitation therefore emerges as a prototype science of embodied intelligence: what patients must relearn to recover, machines must learn to become truly embodied.

This book builds upon these foundations AI x HAI Lab developed and takes the decisive next step. It presents a systematic path by which cognitive intelligence may become embodied intelligence, embodied intelligence may develop general capability, and AI may advance toward AGI.

Its governing progression is:

Knowledge → Knowing → Embodiment → Action → World-Generation

Large models have achieved a historic leap from processing the known toward exhibiting the power to know. Yet knowing is not acting. Representation is not reality. A world model is not yet a lived world—and attaching a robotic body to cognition does not make cognition embodied.

Intelligence becomes true only when knowing enters a body, bears weight, accepts limitation, acts amid uncertainty, risks failure, learns through consequence, and allows itself to be rewritten by the world.

Across twenty-one chapters, the book critically examines perception–action loops, temporality, physical intelligence, memory, VLA, JEPA, spatial intelligence, and world models. It then develops and operationalizes IBB through Human Body Modeling, Large Movement Models, brain–computer interfaces, CAREN, digital-intelligent twins, and human–machine–world co-learning—revealing how intention gains direction, the body gives intelligence weight, behavior brings it into reality, and the world returns consequence as learning.

The book ultimately advances beyond task intelligence toward the Seven Wisdoms and network-ontological intelligence: a vision of AGI not as an omnipotent system standing above the world, but as an intelligent ecology through which humans, machines, bodies, environments, institutions, and data participate, learn, bear responsibility, and generate reality together.

This is not merely another roadmap toward more capable robots. It is a new ontology and architecture of intelligence—a passage from abstract cognition to embodied truth, from world models to world-generation, and from artificial capability toward AI × HAI co-evolution.

The path to AGI does not begin by making models infinitely larger. It begins when knowing enters action, action submits to the judgment of reality, and intelligence learns to become true in the world.