Golden Encyclopedia | Can general artificial intelligence really think like humans?

Author: Jules Winnfield, CoinTelegraph; Translated by: Wu Zhu, Jinse Finance

I. What is AGI?

When the boundaries between humans and machines become blurred, we see Artificial General Intelligence (AGI). Unlike Narrow Artificial Intelligence (ANI), which uses AI to solve a single problem, AGI refers to artificial intelligence that can understand, learn, and apply knowledge in a way that is difficult to distinguish from human cognition.

AGI is still in the theoretical stage, but the prospect of artificial intelligence completely replacing human input and judgment naturally attracts widespread attention, with researchers, technology experts, and scholars working to turn the concept of AGI into reality.

Currently, another mainstream research tries to explore the feasibility and impact of AGI and ANI in an increasingly AI-influenced world.

In fact, while ANI has already changed various industries, the potential of AGI goes far beyond that. Imagine a world where a machine can not only assist humans in completing tasks but also proactively understand the driving factors behind specific tasks, predict outcomes, and autonomously create innovative solutions to achieve the best results. This paradigm shift could completely transform healthcare, education, transportation, and countless other fields.

II. Why is AGI so powerful?

Unlike ANI, AGI is not limited to performing pre-programmed tasks or predefined responses within a limited domain. Instead, it has the potential to generate and apply knowledge in various contexts.

Imagine a self-driving car driven by AGI. It can not only pick up passengers from a train station but also personalize your journey through customized suggestions, such as stopping at the train station, choosing a sightseeing route, or navigating unfamiliar roads, ultimately reaching the destination. Moreover, as AGI is a machine, it does not feel fatigue and can continuously learn and improve at an exponential speed.

Vitalik Buterin provided the following definition of AGI, emphasizing its enormous potential:

This example highlights some interesting characteristics of AGI, including:

• Learning Ability: AGI can learn from experience and continuously improve its performance over time without additional dataset training by human programmers. This learning is not limited to specific tasks but covers a wide range of activities.

• Problem-Solving Ability: AGI can use logical reasoning like humans to solve complex problems. This includes considering non-traditional variables such as emotional influences, thereby revealing broader potential outcomes.

• Adaptability: AGI can adapt to new situations and environments without explicit programming, meaning it can thrive in dynamic and unpredictable environments.

• Understanding and Interpretation: AGI can understand natural language, abstract concepts, and emotional nuances, enabling complex human-machine interactions.

III. The Pursuit of AGI: Where Will It Stand by April 2025?

AGI is currently a sci-fi version of AI. However, despite being in the theoretical stage, its enormous potential makes it a sci-fi version of artificial intelligence.

While existing models like ChatGPT are continuously developing and improving, the journey to making AGI a reality still requires overcoming significant technical challenges, such as:

• Defining the Technology Stack: The purely hypothetical nature of Artificial General Intelligence (AGI) makes it difficult, or even completely impossible, to determine the exact nature of the technology stack required for actual implementation.

• Neural Networks: Advances in deep learning have driven development in this field, but AGI still needs specialized neural networks to simulate brain structure for processing information and introduce emotions and nuances.

• Natural Language Processing (NLP): The NLP field needs to make significant progress to enable machines to better understand and generate human language, incorporating nuances, emotions, and complexity. This includes more complex analysis of language grammar, semantics, and context, which are still evolving in traditional machine learning models using NLP.

• Reinforcement Learning: Using reward-based mechanisms to train machines in decision-making will enable AGI to learn optimal behavior through trial and error.

Despite progress, creating an AGI that can truly think like humans remains a challenging goal.

IV. Can AGI Think Like Humans?

The question of whether Artificial General Intelligence can think like humans delves into the core of human cognition. The hallmarks of human thinking are consciousness, emotional depth, creativity, and subjectivity. While AGI can simulate certain aspects of human thinking, replicating the full range of human cognition is a formidable challenge.

Several dimensions of human cognition are particularly difficult to mimic:

• Consciousness and Self-Awareness: One of the distinctive features of human thinking is consciousness, the awareness of oneself and one's environment. No matter how complex, AGI lacks the intrinsic introspective ability of human consciousness. AGI operates on a set of underlying algorithms and complex learning patterns, lacking subjectivity or genuine emotions.

• Emotional Intelligence: Humans experience a wide range of emotions that influence their decisions, behaviors, and interactions. While AGI can be trained to recognize and respond to these emotions, the lack of genuine emotional experience means it cannot fully replicate them. Human emotional intelligence includes empathy, compassion, and moral considerations, which are difficult to encode in machines.

• Creativity and Innovation: Creativity involves generating novel ideas and solutions, often achieved through intuitive leaps and imaginative thinking. AGI can simulate creativity by combining existing knowledge in new ways, but it lacks the intrinsic motivation and subjective insights that drive human innovation. True creativity stems from emotional experiences, personal reflection, and cultural context, which AGI cannot authentically replicate.

V. The Main Advantages of AGI

The litmus test for Artificial General Intelligence is whether it can fully replicate human experiences. Once achieved, its potential benefits will be immense and will benefit various industries, affecting every aspect of daily life.

Despite its limitations, AGI is increasingly seen as a positive force across industries, including:

• Healthcare: AGI can use massive foundational training data to assist in disease diagnosis, develop personalized treatment plans, and predict personalized health outcomes.

• Education: AGI can provide customized learning experiences, tutoring, and academic research support. AGI can adapt to individual learning styles and learning progress, thereby enhancing educational outcomes.

• Economics: AGI can optimize financial models, predict market trends, and improve productivity. It can analyze economic data, forecast market trends, and guide investment decisions.

• Environmental Science: AGI can analyze climate data, simulate ecological impacts, and propose sustainable solutions.

Moreover, the potential of AGI extends to transportation, communication, and entertainment, providing new frontiers for innovation.

VI. Ethical and Social Considerations

The rise of AGI raises significant ethical and social questions.

Although AGI is powerful, its safe use requires careful consideration, which has prompted the establishment of some non-profit associations, such as the AGI Association shown in the image below.