A recent study indicates that artificial intelligence (AI) has the potential to surpass human intelligence in the future. The research delves into the complexities of AI and the human brain, proposing a new theoretical framework that, by applying AI technology at the cellular level in neuroscience, AI can infinitely approach the functions of the human brain, and ultimately exceed human intelligence levels.
The human brain is widely regarded as one of the most complex systems in the universe, while artificial intelligence is considered one of the most important technologies in human history. A core question arises: will AI eventually surpass human intelligence? This study suggests that the answer is affirmative.
The study proposes that by utilizing new AI technologies, we can create "AI twins" of the human brain. These AI components can simulate the fundamental units of the brain, such as neurons and synapses, thereby approaching the operational mechanisms of the human brain at the cellular level, including sensory and cognitive functions. Theoretically, through this method, AI can infinitely approximate the functions of the human brain and ultimately surpass human intelligence.
The core of the study lies in its departure from traditional neuroscience research methods, replacing the brain's basic components (such as neurons and synapses) with corresponding AI components. Researchers believe that various regions and functional subsystems of the human brain (such as visual, olfactory, auditory, and reasoning systems) can be approached through corresponding AI twins, with errors kept within a minimal range.
The main findings of the study include:
Unlimited potential of AI: AI can theoretically exceed the intelligence level of the human brain.
Cellular-level simulation: AI technology can accurately simulate fundamental units of the human brain, such as neurons and synapses.
Approaching human brain functions: Various regions and functional subsystems of the human brain can be infinitely approached with AI twins.
Opening new fields for AI: AI will develop into a new discipline with self-systems and principles without restrictions.
Promoting interdisciplinary collaboration: A call for global interdisciplinary team collaboration to model different types of neurons and synapses in the human brain.
Safe and controllable AI: Commitment to developing controllable, explainable, and safe AI technologies with reasoning capabilities that can discover natural laws.
Research challenges:
Limitations of traditional modeling methods: Classical mathematical modeling and neural dynamics methods struggle to fully understand the complexity and learning mechanisms of the human brain.
Complexity of the human brain: The human brain consists of billions of neurons and trillions of synapses, with complex structures and diverse functions.
Research at the microscopic level: In-depth study of the mathematical representation and molecular behavior of neurons and synapses is required.
Future prospects:
AI-assisted neuroscience: AI technologies like AI twins will be used for dynamic analysis at the cellular level in neuroscience and solutions for brain diseases.
New AI technologies: Development of low-power AI technologies leveraging the basic properties of neuroscience.
Exploring natural laws: New AI technologies will possess reasoning capabilities to discover natural laws.
This study indicates that the potential of artificial intelligence extends far beyond current applications. By simulating the cellular structure of the human brain, AI is expected to surpass human intelligence in the future and bring new breakthroughs to neuroscience research. This research also suggests that AI may evolve into a new discipline with self-systems and principles, much like mathematics and physics.
Paper link: https://www.sciencedirect.com/science/article/abs/pii/S0925231224018241
