한국어(KO) The dangerous unknowns at the heart of LLMs 2023년 이후 LLM(ChatGPT 등)의 급격한 발전에도 불구하고, 이들 모델은 인간과 같은 이해 능력을 갖추지 못하고 불규칙한 성능을 보인다. LLM은 방대한 텍스트 데이터를 기반으로 다음 단어를 예측하

LLMs show 'jagged intelligence' despite rapid advancement

By PulseAugur Editorial · [1 sources] · 2026-06-09 00:44

Large Language Models like ChatGPT have advanced rapidly since 2023, yet they lack true human-like understanding and exhibit inconsistent performance. These models, which predict the next word based on vast text data, can excel at certain tasks while failing unexpectedly on similar ones, a phenomenon termed 'jagged intelligence.' Despite the necessity of fine-tuning with human feedback and safety training, issues of manipulability and uncertainty persist. AI

IMPACT Highlights the inherent limitations and potential unreliability of current LLMs, urging caution in their application and development.

RANK_REASON The cluster discusses the conceptual limitations and ongoing uncertainties of LLMs, drawing on an analysis of their performance characteristics, rather than reporting on a specific release or event.

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Mastodon — fosstodon.org TIER_1 한국어(KO) · [email protected] · 2026-06-09 00:44

The dangerous unknowns at the heart of LLMs Despite the rapid development of LLMs (such as ChatGPT) since 2023, these models lack human-like understanding and exhibit erratic performance. LLMs predict the next word based on vast amounts of text data

The dangerous unknowns at the heart of LLMs 2023년 이후 LLM(ChatGPT 등)의 급격한 발전에도 불구하고, 이들 모델은 인간과 같은 이해 능력을 갖추지 못하고 불규칙한 성능을 보인다. LLM은 방대한 텍스트 데이터를 기반으로 다음 단어를 예측하는 확률 모델이며, 특정 문제에서는 뛰어난 성능을 내지만 유사한 문제에서는 갑작스러운 실패를 경험한다. 이러한 현상을 'jagged intelligence'라 부르며, 이는 LLM의 근본적 한계에서 기인한다. 추가로…

LINKS yalereview.org/…/melanie-mitchell-jagged-…

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The dangerous unknowns at the heart of LLMs Despite the rapid development of LLMs (such as ChatGPT) since 2023, these models lack human-like understanding and exhibit erratic performance. LLMs predict the next word based on vast amounts of text data

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