A Review of the Latest Research Achievements in the Basic Theory of Generative AI and AGI

What is it about?

The research method involves a comparative analysis of the differences in underlying logic and formal understanding between traditional AI and Current AI, further exploring the distinctions between the three core viewpoints of traditional AI (symbolism, connectionism, behaviorism) and the three major schools of Current AI (generative AI/AGI based on large language models (LLMs) such as ChatGPT; new quality productive force AGI characterized by small models, such as I3DNA; and twin Turing machines based on dual formal understanding models that are compatible with both large and small models). The research reveals the core components of the basic theory of AI and AGI: bit-list logic, linkage functions, followed by generalized bilingualism or generalized translation based on digital and intelligent text with the three fundamental laws.

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Why is it important?

The significance of this research lies in not only enhancing the interpretability of generative AI/AGI based on LLMs represented by ChatGPT but also providing generalized translations for the new quality productive force AGI characterized by small models and its complex theories of cosmic intelligence and the universal model series. At the same time, it demonstrates the potential of twin Turing machines as inclusive intelligent agents in integrating data, knowledge, computing power, algorithms, and human-computer mutual assistance in the new era of cognitive paradigms, laying the foundation for constructing super intelligent systems.

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