前沿人工智能框架与新时代的曙光 ✍ Demis Hassabis🕐 2026-07-15📦 9.3 KB 🟢 已读 𝕏 文章列表 Demis Hassabis 探讨了通用人工智能(AGI)的临近及其对人类社会的深远影响。文章提出建立一个由公私合营的前沿 AI 标准机构,负责评估模型能力、制定安全标准,并建议在保持创新的同时,通过国际合作应对潜在风险,确保技术造福全人类。 AGI前沿AI安全标准标准机构技术治理人工智能Demis Hassabis # A Framework for Frontier AI and the Dawning of a New Age **作者**: Demis Hassabis **日期**: 2026-07-14T09:10:16.000Z **来源**: [https://x.com/demishassabis/status/2076957440109625718](https://x.com/demishassabis/status/2076957440109625718) ---  This is a pivotal moment in human history. Artificial General Intelligence (AGI), a system that exhibits all the cognitive capabilities the brain has, is probably only a few short years away. When we look back on this time in the decades to come, I think we will realise we were standing in the foothills of the singularity - nothing less than the dawning of a new age for humanity. I’ve spent my whole life working on AGI because I’ve always had a deep conviction that, if built and deployed responsibly, it would prove to be one of the most beneficial and transformative technologies ever invented. AGI cannot be compared to standard technological breakthroughs, not even ones as consequential as the internet or mobile - it is much more akin to the discovery of electricity or fire. If you stop to think about it, we’ve essentially found a way to make sand think. It’s miraculous. The magnitude of this technology’s impact will be unprecedented, perhaps 10x of the Industrial Revolution at 10x the speed. It will help us solve some of the biggest problems society faces from accelerating drug discovery to developing new clean energy sources to creating novel advanced materials. We could even reach a point where resources are no longer the limiting factor for human progress, leading to an amazing new era of abundance. ## The Challenges of the Frontier AI is already starting to deliver real-world benefits but to realise its immense promise, we have to navigate this critical period of development thoughtfully and carefully. Urgent action is needed to address risks that might arise as we get closer to AGI. We’ve already seen the challenges frontier models pose for cybersecurity, and other threats including nuclear and bio risks may soon emerge as capabilities continue to advance. On the horizon, we will need robust safeguards to maintain control of increasingly agentic, recursively self-improving systems - and tackle unknown issues that will only become clearer over time. I’ve always believed in the power of human ingenuity and creativity to solve any problem. I’m confident that mitigating the technical risks related to AI is a challenge we can collectively address, but only if we give ourselves the time and space to get this next crucial step right. Currently, as a field and as a wider society, we aren’t doing that. At the moment, we are locked in an extremely intense, multilayered commercial and geopolitical race. While these competitive dynamics fuel rapid progress and accelerate the incredible upsides, advances on the frontier are outpacing our understanding of the technology. Nobody in the world knows for sure what is going to happen from here, and even the experts disagree. When there is a large degree of uncertainty and the stakes are this high, proceeding with cautious optimism is the sensible and correct strategy. That calls for public policy that promotes innovation while also incentivising responsibility and security, fosters international collaboration on key safety issues, and encourages careful consideration of how AI is deployed for the benefit of society. ## A Framework for a Frontier AI Standards Body The rapid progress we’re seeing in AI requires a new approach to testing frontier AI model capabilities that is dynamic, adaptable, and rigorous. The US is well positioned, given its economic and technical standing, to take the first step in developing such a framework. It could establish a new Standards Body modelled on a federally overseen public-private partnership or self-regulatory organisation, much like the Financial Industry Regulatory Authority (FINRA), with a board that includes independent leading technical experts and open-source representatives. Funding would need to be substantial and likely mostly come from industry, in order to attract world-class technical talent and provide the necessary compute resources for large-scale testing. The Standards Body would be responsible for developing assessment protocols and working with appropriate federal agencies and the US National Labs to conduct testing in areas relevant to national security. A model would qualify as ‘Frontier-class’ if it meets certain thresholds on a set of benchmarks determined by the Standards Body and regularly updated to keep pace with evolving AI capabilities. Organisations with ‘Frontier Models’ as defined by those benchmarks would be deemed ‘Frontier Labs’, and be encouraged to adopt best practices, such as publishing model cards with technical details, maintaining strong internal cybersecurity, vetting key personnel, and providing sufficient resourcing for safety and security research, and more. Initially, Frontier Labs would voluntarily share models with the Standards Body for review up to 30 days before release. Once the assessment protocol is shown to be effective and robust, formalisation could quickly follow, meaning that Frontier Models would be required to pass it to be deployed in the US market. Labs would also work with the Standards Body to address any critical post-release vulnerabilities. Model assessments should include rigorous scientific evaluations of capabilities in cybersecurity, biological threats and other high-risk domains. Specific agentic AI tests could look for attempts to bypass safety guardrails or signs of deception, and ensure best practices, such as digitally watermarking AI-generated images and generating human-readable output tokens to understand model reasoning. These evaluations would be regularly updated, perhaps quarterly to start, with outdated or saturated benchmarks being deprecated and replaced. Initially, they would be developed in consultation with Frontier Labs, but eventually the Standards Body should build up the technical capacity to create its own held-out tests independent of the Labs to prevent overfitting. Working with the US government, it could promote an ecosystem of third-party auditors to help with the assessments and development of new benchmarks and evaluations. The strength of this approach is it would be technically focused, while at the same time supporting innovation and incentivising responsible behaviour. It is designed to keep up with the field’s acceleration and adapt to the biggest risks as they are identified, and could be ratcheted up if the seriousness of the situation demands, including coordinating a slowdown in development among the Frontier Labs if deemed necessary. Being designated a Frontier Lab would carry significant prestige and be open to any organisation by building models that meet the benchmark criteria. The framework could apply to Frontier-class models no matter their country of origin or whether they are open or closed, but any non-frontier models, say from startups or academia, would be exempt from this process. This US-initiated effort would provide a strong starting point for creating shared international standards on Frontier AI. Since this technology is going to affect the entire planet, ideally this framework would spur the international community to reach a consensus on how to manage the most serious risks while ensuring everyone has access to and can benefit from the opportunities that AI brings. ## The Future Is Not Yet Written AGI has the potential to be the ultimate tool for advancing science and medicine, and to drive enormous productivity gains and economic growth. But in order to achieve this, we need to get the technical foundations right by coordinating around a shared global framework, using the most rigorous scientific methods, and bringing the best minds together to work on the challenges we face. Even if we solve these hard technical challenges, there will be further complex economic and philosophical questions to tackle: what sorts of new economic models will be needed to help everyone thrive in a post-scarcity world? What values do we want to live by, what will meaning and purpose be, and how might even the human condition itself change? Resolving these questions obviously cannot and should not be left to technologists alone. It requires every part of society to come together to help define this new chapter. There is both huge excitement and uncertainty around AI, and both are warranted. But the future is not yet written, we must use this precious window before AGI arrives to shape this technology for the benefit of all humanity. What we collectively do now will determine how the next phase of civilisation unfolds. By safely stewarding AGI into the world, we can enter a new golden age of scientific discovery and progress, and usher in a bright future of incredible human flourishing. ## 相关链接 - [Demis Hassabis](https://x.com/demishassabis) - [@demishassabis](https://x.com/demishassabis) - [6.4M](https://x.com/demishassabis/status/2076957440109625718/analytics) - [Upgrade to Premium](https://x.com/i/premium_sign_up) - [5:10 PM · Jul 14, 2026](https://x.com/demishassabis/status/2076957440109625718) - [6.4M Views](https://x.com/demishassabis/status/2076957440109625718/analytics) - [View quotes](https://x.com/demishassabis/status/2076957440109625718/quotes) --- *导出时间: 2026/7/15 12:28:53* --- ## 中文翻译 # 前沿人工智能框架与新时代的黎明 **作者**: Demis Hassabis **日期**: 2026-07-14T09:10:16.000Z **来源**: [https://x.com/demishassabis/status/2076957440109625718](https://x.com/demishassabis/status/2076957440109625718) ---  这是人类历史上的一个关键时刻。人工通用智能(AGI),一种展现出大脑所有认知能力的系统,可能只需要短短几年就能实现。当我们几十年后回首这段时光时,我想我们会意识到,我们正站在奇点的山麓脚下——这无异于人类新时代的黎明。 我毕生都在致力于AGI的研究,因为我始终坚信,如果能够负责任地构建和部署它,它将被证明是有史以来最有益、最具变革性的技术之一。AGI无法与标准的技术突破相提并论,即使是像互联网或移动通信那样具有深远影响的突破也不例外——它更像是对电或火的发现。如果你停下来想一想,我们本质上找到了一种让沙子思考的方法。这简直是个奇迹。 这项技术的影响力将是前所未有的,其规模可能是工业革命的10倍,速度也是10倍。它将帮助我们解决社会面临的一些最大问题,从加速药物发现到开发新的清洁能源,再到创造新颖的先进材料。我们甚至可能达到一个地步,即资源不再是人类进步的限制因素,从而开启一个令人惊叹的富足新时代。 ## 前沿的挑战 人工智能已经开始带来现实世界的益处,但要实现其巨大的潜力,我们必须深思熟虑、小心翼翼地度过这一关键的发展时期。迫切需要采取行动来解决随着我们接近AGI而可能出现的风险。我们已经看到了前沿模型在网络安全方面构成的挑战,随着能力的不断进步,其他威胁包括核风险和生物风险可能很快就会出现。在不久的将来,我们需要强有力的保障措施来维持对日益具有代理性、递归自我改进系统的控制——并解决那些只有随着时间推移才会变得清晰的未知问题。 我一直相信人类智慧和创造力解决问题的力量。我相信,缓解与AI相关的技术风险是我们能够共同应对的挑战,但前提是我们要给自己时间和空间,把这关键的一步走对。目前,作为一个领域和更广泛的社会,我们并没有做到这一点。 目前,我们正处于一场极其激烈、多层次的商业和地缘政治竞赛中。虽然这些竞争动态推动了快速进步并加速了令人难以置信的利好,但前沿的进步已经超过了我们对技术的理解。世界上没有人确切知道接下来会发生什么,即使是专家们也存在分歧。当存在巨大的不确定性且风险如此之高时,抱着谨慎乐观的态度前行是明智且正确的策略。这需要公共政策既能促进创新,又能激励责任和安全,促进在关键安全问题上的国际合作,并鼓励审慎考虑如何部署AI以造福社会。 ## 前沿人工智能标准机构的框架 我们在人工智能领域看到的快速进展,需要一种新的方法来测试前沿AI模型的能力,这种方法必须是动态的、适应性强且严谨的。鉴于其经济和技术地位,美国完全有条件迈出第一步,制定这样一个框架。它可以通过建立一个模仿联邦监督下的公私合作伙伴关系或自律组织(如美国金融业监管局FINRA)的新标准机构,其董事会包括独立的顶尖技术专家和开源代表。资金需要充足,且可能主要来自行业,以吸引世界一流的技术人才,并为大规模测试提供必要的计算资源。 该标准机构将负责制定评估协议,并与适当的联邦机构和美国国家实验室合作,在与国家安全相关的领域进行测试。如果一个模型在标准机构确定的一组基准上达到了特定阈值,并且定期更新以跟上不断发展的AI能力,它将有资格被称为“前沿级”。那些拥有根据这些基准定义的“前沿模型”的组织将被视为“前沿实验室”,并被鼓励采用最佳实践,例如发布包含技术细节的模型卡片、维持强大的内部网络安全、审查关键人员、以及为安全和安保研究提供充足的资源等。 最初,前沿实验室将在发布前最多30天内自愿与标准机构共享模型以供审查。一旦评估协议被证明有效且稳健,正式化可能会很快跟进,这意味着前沿模型必须通过该协议才能在美国市场部署。实验室还将与标准机构合作,解决任何关键的发布后漏洞。 模型评估应包括对网络安全、生物威胁和其他高风险领域能力的严格科学评估。特定的代理AI测试可以查找试图绕过安全护栏或欺骗行为的迹象,并确保采用最佳实践,例如对AI生成的图像进行数字水印,以及生成人类可读的输出标记以理解模型推理。 这些评估将定期更新,可能起初是每季度一次,淘汰过时的或饱和的基准并用新的取而代之。最初,它们将与前沿实验室协商制定,但最终该标准机构应建立起独立于实验室创建其自己的保留测试的技术能力,以防止过拟合。与美国政府合作,它可以促进一个第三方审计师的生态系统,以协助评估和开发新的基准和评估方法。 这种方法的优势在于它将专注于技术,同时支持创新并激励负责任的行为。它旨在跟上该领域的加速步伐,并适应被识别出的最大风险,如果事态的严重性需要,甚至可以升级措施,包括在必要时协调前沿实验室放慢开发速度。被指定为前沿实验室将享有极高的声望,任何通过构建符合基准标准的模型的组织都可以开放申请。该框架可适用于无论原产国是哪里、无论是开源还是闭源的前沿级模型,但任何非前沿模型,例如来自初创公司或学术界的模型,都将豁免于此流程。 这项由美国发起的努力将为制定关于前沿AI的共同国际标准提供一个强有力的起点。由于这项技术将影响整个地球,理想情况下,该框架将推动国际社会就如何管理最严重的风险达成共识,同时确保每个人都能获得AI带来的机会并从中受益。 ## 未来尚未书写 AGI有潜力成为推进科学和医学的终极工具,并推动巨大的生产力提高和经济增长。但为了实现这一点,我们需要通过围绕一个共同的全球框架进行协调,使用最严谨的科学方法,并召集最优秀的人才共同解决我们面临的挑战,从而打好技术基础。 即使我们解决了这些艰巨的技术挑战,仍有更复杂的经济和哲学问题需要解决:在稀缺后的世界里,需要什么样的新经济模型来帮助每个人繁荣发展?我们要秉持什么样的价值观,意义和目的将是什么,甚至人类的生存状态本身可能会如何改变?显然不能也不应该仅由技术人员来解决这些问题。它需要社会的各个部分聚集在一起,共同帮助定义这一新篇章。 人们对AI既感到巨大的兴奋,又感到不确定,这两种情绪都是合理的。但未来尚未书写,我们必须利用AGI到来之前这宝贵的窗口期,为了全人类的利益来塑造这项技术。我们现在集体所做的一切将决定文明下一阶段的展开方式。通过将AGI安全地引入世界,我们可以进入科学发现和进步的新黄金时代, usher in 一个人类实现惊人繁荣的光明未来。 ## 相关链接 - [Demis Hassabis](https://x.com/demishassabis) - [@demishassabis](https://x.com/demishassabis) - [6.4M](https://x.com/demishassabis/status/2076957440109625718/analytics) - [Upgrade to Premium](https://x.com/i/premium_sign_up) - [5:10 PM · Jul 14, 2026](https://x.com/demishassabis/status/2076957440109625718) - [6.4M Views](https://x.com/demishassabis/status/2076957440109625718/analytics) - [View quotes](https://x.com/demishassabis/status/2076957440109625718/quotes) --- *导出时间: 2026/7/15 12:28:53*
《 《前沿人工智能框架与新时代的曙光》雄文解析 文章解析了关于通用人工智能(AGI)的前沿框架,将其比作电与火的“文明级重启”。文章探讨了AGI带来的风险与机遇,提出了建立类似FINRA的标准机构来监管前沿模型的方案,强调了在技术竞速中保持审慎和国际合作的重要性。 技术 › LLM ✍ KK.aWSB🕐 2026-07-15 AGI人工智能安全监管前沿模型技术伦理国际合作标准机构风险控制
A AGI 前夜:智力进入接口、成本表和工作流 文章分析了 AGI(通用人工智能)临近时的现实特征,指出其冲击力不在于机器像人,而在于智力成为一种可复制、可计价的基础设施。文章探讨了 OpenAI、DeepMind、Anthropic 等巨头对 AGI 的定义与路径,强调 AGI 首先是劳动力供给的冲击。同时,文章从任务链路、接口、稳定性、成本四个维度定义了 AGI 的现实门槛,并揭示了算力战争背后的能源与地缘政治博弈。 技术 › LLM ✍ Russell🕐 2026-05-01 AGI人工智能OpenAIDeepMindAnthropicAgent算力技术趋势职场变革Karpathy
1 100 小时深入基米:揭秘 Moonshot AI 的极客文化与生存法则 本文通过100小时的内部观察,深入剖析了Moonshot AI(Kimi)独特的企业文化与生存状态。文章记录了公司如何在DeepSeek崛起的压力下调整战略,强调了“模型能力”至上的原则。作者揭示了该公司偏爱具有“概括能力”和“品味”的天才型员工,实行无KPI、无层级的扁平化管理,并详细描述了年轻员工在高强度跨领域工作中的成长与焦虑。这不仅是一家初创公司的生存侧写,也是对AI时代人才组织模式的深刻探讨。 技术 › LLM ✍ Rui Ma🕐 2026-04-01 Moonshot AIKimi公司文化DeepSeek人工智能职场AGI访谈创业模型训练
硅 硅谷7000人失眠夜:AGI与自我进化的临界点 文章描述了2026年初硅谷因AI爆发性进展而产生的集体焦虑。从Matt Shumer关于“判断力”AI的描述,到OpenAI利用模型自我构建的事实,指出“智能爆炸”已进入正反馈循环。文章引用投资人王利杰的观点,分析了免费版与付费版AI的认知差,并给出了行动建议。作者认为,算力成本限制了AGI的无限进化,人类应关注决策层优势,将AI视为工具而非威胁。 技术 › LLM ✍ kvc.eth🕐 2026-02-16 人工智能AGI智能爆炸AI投资硅谷技术哲学ClaudeOpenAI
中 中国风投生态运作机制 文章分析了中国风险投资生态的独特性,指出尽管中国在开源AI、生物技术和机器人领域具有优势,但其资本市场对创始人更为严苛。文章解释了为何中国初创公司倾向于IPO而非被收购,并详细介绍了人民币基金、美元基金和外资基金这三种资本池的特点与差异。 投资 › 宏观经济 ✍ Bohan🕐 2026-07-29 中国风投IPO资本生态人工智能机器人生物科技
对 对话姚颂:不想 boring,那就继续开心地 suffering 本文专访了正行创新创始人姚颂,回顾了他从清华本科毕业创立深鉴科技,到3亿美元卖掉公司,再到投身商业航天和物理 AI 的十年创业历程。姚颂分享了对技术创业、战略取舍、人生状态以及硬科技发展的深刻思考。 职场 › 职业发展 ✍ 晚点 LatePost🕐 2026-07-24 姚颂创业深鉴科技人工智能职业发展清华商业航天访谈
2 2026年普通人都能上车的AI风口:DeepSeek 创始人梁文锋3小时演讲精华提炼 文章提炼了DeepSeek创始人梁文锋关于AI未来的演讲精华,强调“克制”的重要性。梁文锋指出,想拿得多的人会被想拿得少的人打败。他为AI发展制定了清晰的路径,并建议普通人不要盲目追逐风口,而应注重提升“把话说清楚”和“长期沉淀”的能力,通过行业深耕和AI应用找到属于自己的机会。 技术 › LLM ✍ Gloria🕐 2026-07-24 DeepSeek梁文锋人工智能职业发展创业思维链智能体Coding AgentAI应用克制
梁 梁文锋投资人会议语录 本文记录了梁文锋在投资人会议上的核心观点,涵盖AGI发展路线、开源与商业化策略、团队管理及愿景驱动等方面。他强调产品是AGI的副产物,现阶段的重点是Coding Agent和持续学习能力,开源与克制是长期战略,目标是实现AGI而非追求短期利益。 技术 › LLM ✍ Orange AI🕐 2026-07-23 AGI开源Agent持续学习商业模式愿景驱动克制大模型技术路线团队管理
M Making a Billion Intelligent Machines 文章介绍了Applied Intuition公司如何通过提供仿真、数据和操作系统工具,从自动驾驶领域的非主流选择发展为物理AI应用平台,并成功拓展到国防、建筑等多个行业。 技术 › Agent ✍ Marc Andreessen🕐 2026-07-22 物理AI自动驾驶仿真技术Applied Intuition操作系统国防工业应用技术平台人工智能转型
I Inside Kimi: 100 Hours of Observation 本文讲述了作者深入 AI 独角兽 Moonshot AI(Kimi 母公司)内部进行 100 小时的观察记录。文章回顾了公司从早期的营销挣扎到面对竞争对手 DeepSeek 突围时的战略调整,展现了这家年轻、高估值且充满内向天才员工的神秘企业文化。 技术 › LLM ✍ Liu Mo🕐 2026-07-22 KimiDeepSeekLLM人物企业文化创业人工智能月之暗面观察报道
F FDE:年薪百万的AI前沿部署工程师详解 文章介绍了科技领域最热门的角色 Forward Deployed Engineer (FDE),其年薪可达15万至100万美元。FDE 负责在企业内部部署 AI,连接业务流程与模型。文章提供了30天行动计划,涵盖流程理解、判断、构建部署及人际应对,强调实战经验的重要性。 职场 › 职业发展 ✍ The Startup Ideas Podcast (SIP)🕐 2026-07-21 AI工程师职业规划部署职场人工智能技术FDE工作流技能
A A Conversation with Yang Zhilin of Kimi: Advancing Toward the Endless, Unknown Snow Mountains 本文是对月之暗面创始人杨植麟的专访,回顾了他从硅谷回国创业、专注AGI的历程。文章探讨了基础模型公司面临的资本、人才竞争压力,以及Kimi在商业化与理想主义之间的平衡。 技术 › LLM ✍ 张小珺 Xiaojun Zhang🕐 2026-07-19 杨植麟Kimi月之暗面AGI访谈创业基础模型商业化资本技术理想主义