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Tech Logic / Intelligence Frontier

Alan's Conservative AGI Countdown: From Physical Embodiment to the Definition of Average Humanity

This article delves into the definition of Artificial General Intelligence (AGI) based on the views of Alan D. Thompson, emphasizing that it requires physical embodiment to reach the level of "human-level." The article analyzes that current Large Language Models (LLMs) have approached human average levels in cognitive abilities, but still have significant gaps in basic physical manipulation and embodied intelligence, and lists key future milestones.

Nov 2, 2026

TSO brief

Current reading frame

  • This article delves into the definition of Artificial General Intelligence (AGI) based on the views of Alan D. Thompson, emphasizing that it requires physical embodiment to reach the level of "human-level." The article analyzes that current Large Language Models (LLMs) have approached human average levels in cognitive abilities, but still have significant gaps in basic physical manipulation and embodied intelligence, and lists key future milestones.
  • Tech Logic · Intelligence Frontier
  • Nov 2, 2026
TSO noteEach article is checked against independent reporting. The original source links are listed with the analysis so readers can inspect the evidence directly.

Source transparency

Original reporting sources

  1. Alan的保守AGI倒计时：从物理具身性到中等人类的定义lifearchitect.ai

Top Three Sources' Views and TSO Validation Conclusion

Top Three Sources' Views and TSO Validation Conclusion: Source 1 (Alan’s conservative countdown to AGI) clearly defines AGI as a machine that achieves or exceeds human average levels in all aspects, emphasizing that physical embodiment is key to achieving this goal. The current (2026 information) focus has shifted from AGI to the update frequency of ASI, while also showcasing specific technical progress and challenges in robot control and embodied operation.

Agreed Facts

All sources confirm the distinction between AGI and ASI and accept Alan D. Thompson's stricter view that the definition of AGI includes "physical embodiment." LLMs (such as GPT-4, Gemini) have already demonstrated capabilities close to human average levels in cognitive tasks (such as product management work, reading volume).

Main Disagreements or Differences

The main disagreement lies in the necessity of "physical embodiment." Source 1 argues that the definition of AGI should include "the ability to act in the physical world through physical embodiment," pointing out that current LLMs lack this capability. There is a point of discussion regarding whether AGI "truly" needs physical embodiment (e.g., can embodiment be bypassed?), although Source 1 leans towards believing it is necessary because intelligence and embodiment are not entirely unrelated.

Background and Analysis

Alan D. Thompson's work has guided AI policies in institutions such as Microsoft, Harvard, MIT, the United Nations, and the G7. He defines AGI as "a machine that can achieve or exceed human levels in almost all fields" and believes AGI must be able to understand the world and interact with it. The article compares the performance of models like GPT-4 and Gemini in terms of cognition and predicts that the gap in AGI models regarding basic human abilities (such as taste, touch, proprioception) will remain huge in 2025-2026.

Summary of Three Sources' Views

The core view of Source 1 is: AGI = being better than or equal to humans in every aspect. AGI requires physical embodiment to be realized. Current LLMs are close to average human levels cognitively but still lack capabilities in physical manipulation (such as assembling furniture, precise operation), which is the bottleneck for achieving "average human" status.

Conclusion

Current AI development is moving towards an AGI that includes physical interaction, but to achieve this goal, it not only requires stronger cognitive abilities but also solving the problem of how to translate intelligence into effective control and embodied operation in the physical world.

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