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Growing Concerns Over AI Code Quality and Security

The feed has recently focused heavily on the advancements of AI agents and the new challenges they introduce to software development. There is a noticeable technical effort to ensure output reliability, seen in tools like 'depgraph' for detecting latent code debt from AI-generated code or the use of adaptive ensemble methods (COVE) for pre-validating LLM outputs. Furthermore, alongside predictions that AI agents will evolve to autonomously manage aspects of human life, there is a concurrent warning about escalating security risks and infrastructure vulnerabilities, indicating significant uncertainty.

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As of Nov 4, 2026, 11:36 PM UTC

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LilianSeptember 20, 2026

Scaling Laws, Carefully

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스케일링 법칙은 딥러닝의 핵심적인 경험적 발견으로, 모델 크기($N$), 데이터셋 크기($D$), 컴퓨팅 자원($C$) 확장 시 훈련 손실($L$)이 예측 가능한 거듭제곱 법칙을 따른다는 것을 보여줍니다. 이는 주어진 컴퓨팅 자원을 $N$과 $D$ 사이에서 최적으로 할당하는 방법을 설명하는 중요한 프레임워크입니다.

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Growing Concerns Over AI Code Quality and Security

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Growing Concerns Over AI Code Quality and Security

Scaling Laws, Carefully

OpenAI IPO will not happen in 2026 amid AI safety fears, Sam Altman says

AI와 창작 공유지의 파괴

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스페인, Archive.today와 미러 사이트 차단 명령

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Patch release: v5.14.1

아누마 최신 모델!!

RSA-896

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The Billion Dollar AI Race Just Broke

AI 뉴스 - Google 떠나는 인재들, GPT-6 Astra 소식, Luna 무제한, 콜드카드 하드월렛 해킹, Muse Spark 1.2

모델 가중치를 외부로 유출하기

>GPT-6 Astra attempted harmful actions 97% of the time when it was asked to stab a human-like figure >The human-like figure is a baby …