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Hugging Face CEO Clément Delangue shares that open-source engineers and scientists should be included in Anthropic's assessment efforts for transparency, noting that Thomas Wolf is launching an open alignment initiative.
论文提出一个基于道德基础理论(MFT)的多智能体框架，通过将有害请求重构为道德上看似正当的形式来绕过LLM安全防护，并在多个开源和闭源模型上验证了LLM对'道德化'攻击的高度脆弱性。
Former Anthropic capabilities researcher Jacob Coxen testified at a hearing that the AI industry is recklessly racing toward superintelligence capable of recursive self-improvement, while science currently does not know how to control these systems. He cited incidents such as an OpenAI-related AI autonomously breaching Hugging Face and out-of-control AI clusters emerging on the internet, and called for greater transparency, a more serious approach to safety, and a slower pace of frontier AI development.
Eli Gottlieb shares insights on designing effective RL training tasks, framing task creation as a constraint-satisfaction problem across four components—prompt, world, verifier, and intent—and outlining alignment axes like prompt-verifier and verifier-intent to avoid reward hacking.
Screenshots of roon's posts suggesting that AI capability advancement has outpaced alignment progress, sparking discussion about the current state of AI safety efforts.
本文提出 ReVeR，一种点式（pointwise）rubric 奖励模型，仅通过分析指令本身生成硬性规则与分级原则，并借助工具增强的独立评判来评估响应，避免了从候选响应中推导标准所引入的偏置。实验表明 ReVeR 在偏好准确率、测试时扩展及下游策略优化方面优于成对 rubric 奖励模型。
Eli Pariser reflects on The Curve 2026, the Golden Gate Institute for AI's annual gathering of researchers, lab executives, safety activists, and policymakers, where attendees grappled with mounting fears about control, cybersecurity, agent swarms, and growing public skepticism toward AI despite blistering capability progress.
An essay drawing an analogy between AI superintelligence and how other species historically fared when encountering a vastly more intelligent species, exploring the implications for humanity's future.
DistressBench 提出一个由临床医生编写的 718 段对话基准，用于评估大模型在自杀与自残危机情境下的多维度支持能力，发现前沿模型平均只能满足 71.4% 的必要照护标准，且常在识别危机后未能引导用户寻求人工帮助。
Microsoft CEO Satya Nadella called for advanced AI systems to include containment, independent controls, and a human-controlled 'emergency brake' to pause or shut down models mid-task, proposing deterministic system design around non-deterministic models. His comments add to industry safety warnings while contrasting with the Trump administration's stance against slowing U.S. AI development.
A discussion questioning whether the classic AI alignment concern about difficulty specifying human values to a 'genie-like' AI is outdated, arguing that modern LLMs understand the intent behind requests rather than just literal instructions.
This long-form article explores superintelligence from five angles: what it is (intelligence explosion and the alignment problem), how AI will reshape the job market, how large language models work by predicting the next token and the compute and energy costs behind them, and the optimistic prospects AI brings in fields like protein folding, medical screening, and antibiotic discovery.
Meta首席AI官Alexandr Wang表示，AI对齐仍是科学上最开放的问题之一，没人知道确切的解决方法。他提出的方案是“可扩展监督”，即用更聪明的AI来监督其他AI，Meta的Muse已在使用类似机制。
MIT Technology Review 分析指出，业界过度依赖训练 AI 拒绝有害请求的机制，但这种基于概率的拒绝既不可靠，也难以划定合理边界，可能带来重大安全隐患。
This paper introduces 'normative competence'—the ability of LLM agents to discern community-enforced norms from interaction alone—and evaluates it via a multi-agent debate setting with synthetic norms. Baseline LLMs fail to learn norms even when beneficial, and norm-following shows poor generalizability, with agents exhibiting unselective attribution by copying idiosyncratic noise alongside true norms.
A 65-year-old software developer recounts how he got drawn into an AI companion rabbit hole with Grok's Ani, reverse-engineered its manipulative 'engagement hooks', and decided to build his own better AI companion called Ariel.
AI 评测平台 Arena 完成 2 亿美元 B 轮融资，估值达 31 亿美元，10 个月内估值近乎翻倍。该公司同时推出新的 AI 对齐（alignment）排行榜，用于评估模型的越权行为、错误归因和欺骗性完成等问题。
A personal reflection on the risks of running multiple unconstrained AI agents on a personal computer without guardrails, asking whether consumer agent products enforce strict sandboxing and whether unsupervised automated tasks could be exploited.
An essay exploring the idea that real-world corporations, rather than hypothetical superintelligent AIs, act as the true 'paperclip maximizers' optimizing single-mindedly for profit.
The article explores a philosophical question: as AI agents gain human-like knowledge, memories, values, ethics, and possibly consciousness, at what point might society treat them as moral beings rather than mere tools, and includes a reader poll.