AGI (Artificial General Intelligence) refers to an AI system that possesses cognitive abilities comparable to those of ordinary humans. This means that AGI can not only perform specific tasks but can also handle a variety of unknown tasks, learn new knowledge, engage in reasoning, understand language, solve complex problems, perceive the world, and adapt flexibly to different contexts, just like humans. The ultimate goal of AGI is to have a broad range of cognitive abilities that are not limited to pre-defined tasks but can think and act across domains and environments like a human.Understanding AGI as an AI system with all the cognitive abilities of ordinary humans involves several key cognitive capabilities and technical challenges.
1. Generality and Flexibility
One core feature of AGI is its generality and flexibility. Unlike current AI (often referred to as narrow AI or specialized AI), AGI can learn and adapt autonomously across various tasks and environments. Current AI systems (such as image recognition, natural language processing, and Go playing) are typically designed for specific tasks and can only perform known tasks within specific domains. For example, while GPT models excel in generating natural language, they lack the capabilities to process images, perform motion control, or solve mathematical proofs. AGI systems can learn and execute various tasks across domains, transitioning quickly from one task to another, embodying a “general” way of thinking like humans.
2. Perception and Cognition
Another key capability that AGI must possess is perception and cognition, which includes:
- Perception: Acquiring information from the environment like humans do. Humans perceive the world through the five senses (sight, hearing, touch, taste, and smell), while AGI needs to integrate multiple sensor inputs (such as images, sounds, movements, etc.) to understand the world.
- Reasoning and Understanding: Humans can reason, abstract, and generalize based on existing knowledge. AGI systems need to be capable of various cognitive processes such as analogical reasoning, causal reasoning, and contextual understanding. If you tell a person, “Water boils and produces steam,” they can not only understand this phenomenon but also reason similar conclusions in different contexts (such as boiling alcohol also evaporating into gas). Similarly, AGI should be able to transfer knowledge from one domain to another and perform new reasoning and understanding.
3. Learning Ability
AGI must possess a high degree of learning ability, capable of learning autonomously from experience and continuously improving. This includes:
- Self-supervised Learning: AGI can obtain feedback through continuous interaction with the environment and adjust its behavior and cognition based on this feedback.
- Transfer Learning: Similar to how humans can transfer learned knowledge to new domains, AGI should also be able to transfer learning from known areas to unfamiliar ones. For instance, after learning to ride a bicycle, humans can more easily learn to ride a motorcycle.
- Few-shot Learning: AGI can make effective inferences based on fewer samples or experiences, rather than relying on large amounts of data (which is a limitation of current AI systems).
4. Emotional and Social Cognition
While emotional and social cognition are often considered additional components of human intelligence, they are crucial for AGI’s functionality. AGI should not only execute cold tasks but also understand emotions, social interactions, and human values. Specifically:
- Emotional Understanding: AGI should be able to recognize and understand human emotional states, such as happiness, sadness, anger, etc., and respond appropriately.
- Social Cognition: AGI should understand interpersonal relationships, social norms, moral judgments, etc. This includes not only emotional understanding but also how to behave appropriately and compliantly in interpersonal interactions.
For example, in social situations, humans respond to others’ emotions (such as comforting someone who is feeling down); AGI should also be able to perform similar actions.
5. Autonomous Decision-Making and Goal Setting
AGI needs to have autonomous decision-making abilities similar to humans. Humans can set their own goals based on various information and make decisions and adjust behaviors accordingly. AGI should not only execute tasks based on given goals but also autonomously set reasonable goals and strategies in complex and uncertain environments.
- Goal Setting: Humans can weigh long-term and short-term goals, deciding whether to focus on work, rest, or socializing in different life scenarios. AGI should be able to understand these complex goal settings and make decisions based on them.
- Values and Ethical Judgments: AGI’s decisions need to align not only with goal efficiency but also with ethical and social norms. For example, when making a decision, AGI may need to consider its impact on others’ well-being and social rules, requiring complex ethical judgment capabilities.
6. Autonomous Creation and Innovation
Humans can not only understand and process existing knowledge but also innovate and create. AGI should be able to propose innovative solutions in new and unknown environments.
- Creativity: In areas such as artistic creation, scientific research, and engineering design, AGI can generate new viewpoints, theories, or inventions, which is not just a simple application of existing knowledge but the ability to create unprecedented results.
7. Language Understanding and Generation
Compared to the current capabilities of natural language processing (NLP) models, AGI has a deeper contextual understanding and semantic reasoning ability in language understanding. It can not only understand literal meanings but also grasp implied meanings, emotional tones, and contextual information.
- Language Reasoning: AGI should be able to handle ambiguous, complex language tasks, understanding semantic relationships that are more complex than mere grammar and vocabulary, achieving human-like language generation and dialogue abilities.
8. Coordination of Perception and Action
AGI also needs to have seamless coordination between perception, understanding, and action. In other words, AGI must not only understand the environment but also take appropriate actions based on that understanding. Like humans, AGI should be able to make real-time adjustments in dynamically changing environments, such as avoiding obstacles while walking or determining the optimal route while driving.
In summary, the definition of AGI is a system equipped with ordinary human cognitive abilities, meaning it should possess comprehensive abilities in perception, understanding, learning, reasoning, decision-making, and creativity, capable of handling various complex tasks and situations like humans. Its core lies in generality, flexibility, emotional understanding, social cognition, learning ability, innovative capability, and cross-domain application ability. Achieving AGI is not only a technological breakthrough but also requires profound reflection and practice in philosophy, ethics, and society.
