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2140 条 · 共 131

7月26日7月26日周日

星期日 · 1 条
21:50
IT之家(RSS)精选
AI 评分 71/100
OpenAI、Anthropic 游说美国限制中国开源模型,黄仁勋与马斯克公开反对

OpenAI 与 Anthropic 正游说美国监管机构限制中国开源 AI 模型,认为开放开发过于危险。英伟达 CEO 黄仁勋、微软 CEO 纳德拉、马斯克及扎克伯格等人公开支持开源,签署联名信反对限制。近 200 家硅谷创业公司也敦促特朗普政府不要限制获取中国开源模型,美国官员倾向于将此事作为国家安全问题单独处理。


推荐理由:OpenAI 和 Anthropic 推动限制中国开源模型的游说曝光,加上黄仁勋、马斯克等公开反对,把 AI 开源与闭源之争推向了国家级博弈,这事会直接影响未来中美 AI 生态的走向。

7月25日7月25日周六

星期六 · 1 条
03:24
Hacker News 热门(buzzing.cc 中文翻译)精选
AI 评分 77/100
英伟达、微软和Meta联合警告:应避免对开放权重模型过度监管

英伟达、微软和Meta联合签署公开信,警告对开放权重AI模型的过度监管将削弱美国在AI领域的竞争力。信中指出,开放权重模型能促进创新、降低准入门槛,并支持学术研究。OpenAI和Anthropic未签署该信函。


推荐理由:我觉得这份联名信信号明确,开源模型已成巨头护城河,监管收紧只会让中国模型更占优势,开发者要密切关注后续政策。

7月24日7月24日周五

星期五 · 2 条
07:49
IT之家(RSS)精选
AI 评分 77/100
佛州男子因相信 ChatGPT 拒绝就医而险些丧命,起诉 OpenAI 及 CEO 奥尔特曼

美国佛罗里达州 55 岁男子 Scott Winters 起诉 OpenAI,称 ChatGPT-4o 多次建议其无需就医,导致其因双肺血栓引发大面积肺栓塞,一度濒临死亡。诉状指控 OpenAI 存在疏忽和“无证行医”行为,要求经济赔偿并暂停 ChatGPT Health 服务。OpenAI 回应称 ChatGPT 不是医生,不应替代专业医疗护理。


推荐理由:这不是第一个起诉AI公司的案例,但「AI医生」角色的法律定性将成为行业分水岭,敢不敢让AI给健康建议的团队都该看看。

7月23日7月23日周四

星期四 · 1 条
13:20
公众号:数字生命卡兹克精选
AI 评分 66/100
北京发布智能体新政,首次将Harness Engineering、Token经济、OPC等写入政策

北京市发布《关于加快智能体引领发展的若干措施》,共十条,首次将Harness Engineering(驾驭层工程)、Token经济、OPC(一人公司)等前沿概念写入正式政策。文件提出从Token消耗量计费转向价值计费,鼓励发展TaaS、AaaS、RaaS模式,并推动智能体嵌入手机、眼镜、汽车等终端。


推荐理由:这份政策把 Agent 时代的核心概念全部写进了红头文件,Harness Engineering、Token 经济、OPC 等首次在官方文件中出现,意味着智能体正式进入政策加速期,每个 AI 从业者都该读一遍。

7月21日7月21日周二

星期二 · 4 条
23:52
TechCrunch:AI(RSS)精选
AI 评分 74/100
美国威胁因知识产权盗窃对中国AI模型实施制裁

美国财政部长Scott Bessent周二表示,美方将审查中国开源模型是否存在知识产权盗窃行为,若证实将对中国AI公司实施制裁。Bessent称政府支持开源模型但不支持IP盗窃,并称有能力对盗窃美国公司技术的外国模型进行制裁。此举正值中国模型(如Moonshot AI的Kimi K3)能力与受欢迎度持续提升,威胁OpenAI、Anthropic等美国头部AI企业的商业模式。


推荐理由:美国财政部首次明确威胁制裁中国AI模型,将知识产权争议武器化,从芯片限制直接转向模型本身,AI冷战的边界正在被重新划定。
10:49
The Decoder:AI News(RSS)精选
AI 评分 86/100
Anthropic 因盗版书籍支付 15 亿美元和解金,创下集体诉讼版权赔偿纪录

Anthropic 向图书作者支付 15 亿美元版权和解金,联邦法院已批准。约 482460 部作品中 91.3% 被索赔,每部约获 3000 美元。法官此前裁定,在合法获取的书籍上训练 AI 属于“变革性”合理使用,但大规模抓取网络内容是否合法仍悬而未决。


推荐理由:15亿美元的天价和解只针对盗版获取行为,法官此前已裁决合法图书训练AI属合理使用,这起案件反而成了AI实验室至今最大的法律背书。
10:49
Hacker News 热门(buzzing.cc 中文翻译)精选
AI 评分 79/100
法官批准Anthropic就盗版书籍训练Claude一案达成15亿美元和解协议

美国联邦法官批准Anthropic支付15亿美元,和解其使用盗版书籍训练Claude聊天机器人的集体诉讼。约91%的48.2万本涉案书籍已被作者或出版商认领,每本书赔偿约3000美元。原告律师称这是“历史上已知最大的版权追偿”,Anthropic则强调法院此前已裁定AI训练书籍属于合理使用。


推荐理由:这是 AI 训练数据版权案中第一个重大和解,每个作者赔三千,看似不多但总额达 15 亿,给仍在诉讼中的 OpenAI、Meta 等案打了个样,做版权内容的该认真看看。
01:49
Gary Marcus:The Road to AI We Can Trust(RSS)精选
AI 评分 61/100
中国AI几乎追平美国,Kimi K3开源模型引发市场震荡

中国公司月之暗面(Moonshot.AI)发布Kimi K3模型,性能与最佳美国模型相当,且为开源权重模型,用户可免费下载本地运行。受此消息影响,美国股市上周五下跌,OpenAI和Anthropic的商业模式及IPO前景受到严重质疑。美国在AI软件领域的护城河已不如预期,AI竞赛正演变为工业系统竞争。


推荐理由:加里·马库斯把中美AI竞赛的现实摊开来说,指出美国押注大语言模型是一场战略失误,最值得看的是他提出的七种选项,尤其是把AI变成全球公共产品的方向,对政策制定者和行业人都有冲击。

7月18日7月18日周六

星期六 · 1 条
13:14
TechCrunch:AI(RSS)精选
AI 评分 70/100
Index Ventures 联合创始人 Neil Rimer 认为 AI 财富将面临"再分配"

Index Ventures 联合创始人 Neil Rimer 表示,围绕 AI 积累的巨额财富将面临“某种形式的再分配”,无论是自愿还是强制。他呼吁科技领袖在推动自愿再分配中发挥主导作用。与此同时,美国慈善捐赠总额虽创新高,但捐赠人数持续下降,而加州正考虑对亿万富翁征收 5% 的一次性财富税。


推荐理由:Neil Rimer 这个采访值得点开,不是因为他又在预测,而是他把 AI 财富再分配这个敏感话题摊开了——从慈善的消退到可能的强制征税,跟历史轨迹直接对上了。做 AI 的、投资的都得听听。

7月16日7月16日周四

星期四 · 3 条
22:43
IT之家(RSS)精选
AI 评分 75/100
世界人工智能合作组织协定签署仪式在上海举行,总部设中国上海

7月16日,成立世界人工智能合作组织协定签署仪式在上海举行,中共中央政治局委员、外交部长王毅代表中国政府签署协定。该组织是独立的政府间国际组织,总部设在中国上海,旨在促进人工智能国际合作与全球治理。哈萨克斯坦、老挝、巴基斯坦等29个国家代表签署协定成为创始成员国。


推荐理由:全球AI治理从倡议走向落地,29国签署的政府间组织把总部放在上海,这对中国AI企业的出海合规和参与国际规则制定是长期利好。
21:43
TechCrunch:AI(RSS)精选
AI 评分 77/100
Apple Intelligence 获准在华上线,将集成阿里 Qwen 与百度 AI 能力

中国网信办已批准 Apple Intelligence 在华上线,苹果将把阿里 Qwen 模型集成至 iOS、iPadOS、macOS 及 visionOS 系统。百度也确认正与苹果合作开发面向中国用户的 Apple Intelligence 功能。此前因未获监管批准,Apple Intelligence 自 2024 年推出后在中国市场一直延迟。


推荐理由:Apple 智能服务在华获批,意味着全球最大的 AI 消费市场正式对 iPhone 内置 AI 开放。对国内 AI 开发者来说,Qwen 集成是信号:大厂联盟已定,创业公司窗口在收窄。
20:10
The Verge:AI(RSS)精选
AI 评分 78/100
欧盟裁定 Google 必须向竞争对手开放 Android 和 Search,影响 Gemini 等 AI 服务

欧盟依据《数字市场法案》(DMA)裁定 Google 必须向竞争对手开放 Android 和 Google Search 的关键部分,包括允许第三方 AI 助手和搜索引擎获得更大访问权限。这两项决定可能削弱 Google 对两大核心平台的控制,并为其 AI 工具 Gemini 的未来格局带来深远影响,同时为竞争对手创造新的发展机会。


推荐理由:欧盟这两项裁决直接撬开了谷歌安卓和搜索的围墙,对Gemini等AI助手的地位是实质冲击,做AI应用和搜索的创业者值得盯着后续执行细节。

7月15日7月15日周三

星期三 · 3 条
11:59
Hacker News 热门(buzzing.cc 中文翻译)精选
AI 评分 72/100
数据中心已使美国公众电费增加230亿美元,回收成本困难重重

数据中心对电力的需求已导致美国公众电费增加230亿美元,这一涨价将持续至2028年底。由于电价由州公用事业委员会根据复杂的成本分摊规则设定,数据中心可利用其用电灵活性(如避开系统峰值负荷)规避部分成本分摊,而普通居民难以效仿。监管机构正面临如何公平分配电网基础设施投资成本的挑战。


推荐理由:文章拆开了美国电力市场成本分配的规则漏洞,原来数据中心能靠预测高峰期降载来逃掉电费,普通住户根本没法复制,最后账单还是落在我们头上。
02:35
TechCrunch:AI(RSS)精选
AI 评分 70/100
Google 因 AI 训练再遭出版商集体诉讼

包括 Hachette、Cengage、Elsevier 及作家 Scott Turow 在内的出版商与作者团体对 Google 提起集体诉讼,指控其未经授权使用受版权保护的作品训练 Gemini 模型,并故意移除或篡改版权信息以掩盖这一行为。原告称 Google 将原本仅用于 Google Books 搜索片段展示的书籍副本,以及 Google Play 商店上传的图书,非法用于 AI 训练。诉讼援引 Google 内部文件,其中指出此举可能带来“100 亿至 1000 亿美元的潜在罚款”。该案在纽约南区联邦地区法院提起。


推荐理由:出版商集体诉讼谷歌,这次带上了内部文件警告‘可能面临千亿美元罚款’的弹药,是版权方对AI训练最有力的一次反击,值得关注后续发展。

7月14日7月14日周二

星期二 · 2 条
23:34
TechCrunch:AI(RSS)精选
AI 评分 71/100
纽约州暂停所有新建大型数据中心项目

纽约州成为全美首个暂停数据中心建设的州。州长Kathy Hochul签署行政令,暂时禁止州政府批准50兆瓦及以上大型数据中心的新建许可,可能影响十余个项目。Hochul表示数据中心不应带来更高的电费、水资源消耗或噪音污染,且不能豁免地方区划和审批。禁令将在州政府完成数据中心环境审查流程后解除,预计耗时约一年。Hochul还考虑要求数据中心为州电网提供资金支持,并阻止超大规模数据中心享受税收优惠。此举正值纽约州立法机构推进更严格措施之际,上月一项法案已推进暂停20兆瓦以上数据中心建设一年。


推荐理由:纽约州开了第一枪,暂停所有大型数据中心审批,这可能是AI狂飙时代开始遇到物理世界的硬约束,做基础设施的得重新掂量选址风险了。
17:32
Demis Hassabis@demishassabis精选
AI 评分 68/100
Demis Hassabis:AGI 数年可至,影响达工业革命10倍http://x.com/i/article/2076946210397552640A Framework for Frontier AI and the Dawning of a New AgeThis 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 FrontierAI 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 BodyThe 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 WrittenAGI 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.Google DeepMind 联合创始人 Demis Hassabis 发文称,AGI 可能仅需数年即可实现,其影响将达工业革命的10倍且速度更快。他指出,前沿模型在网络安全、核与生物风险方面已构成挑战,未来需对日益智能体化、递归自我改进的系统建立稳健防护。Hassabis 呼吁美国率先建立类似 FINRA 的前沿AI标准机构,采用联邦监督下的公私合作或自律组织模式,由独立技术专家和开源代表组成董事会,资金主要来自行业以吸引顶尖人才和算力。他强调,当前商业与地缘竞赛导致技术进步快于理解,需以谨慎乐观态度推进公共政策,兼顾创新与安全。
推荐理由:Demis Hassabis 亲自下场提出一个具体的 AGI 监管框架,用 FINRA 模式构建标准组织,这比泛泛呼吁更有行动感,政策讨论里少见的可操作方案。

7月12日7月12日周日

星期日 · 1 条
11:33
IT之家(RSS)精选
AI 评分 70/100
苹果起诉OpenAI挖角窃密,分析师称即使指控未证实也可能重创其硬件计划

苹果在美国起诉OpenAI,指控其挖角400名员工、窃取工程机和机密文件。分析师Paolo Pescatore认为,即使指控最终无法证实,OpenAI的硬件计划仍可能受拖累,双方本就脆弱的合作关系将进一步削弱。斯坦福大学教授Mark Lemley指出,若前苹果员工确实带走机密文件并在OpenAI使用,问题将变得严重。该案涉及消费级硬件产品,预计未来将有更多信息曝光。


推荐理由:苹果的诉讼即使最终不成立,也已经动摇了OpenAI绕开iPhone做硬件的算盘,所有盯着消费硬件的AI公司都该琢磨一下这个先例。

7月10日7月10日周五

星期五 · 1 条
00:40
Anthropic:Newsroom(网页)精选
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Anthropic长期利益信托任命本·伯南克为受托人

Anthropic的长期利益信托(LTBT)任命前美联储主席、2022年诺贝尔经济学奖得主本·伯南克为最新受托人。他将与另外三位受托人共同监督公司以对社会长期有益的方式负责任开发先进AI的使命。LTBT独立于管理团队和投资者,受托人不持股、不分红,仅按服务时间获酬。该信托有权向Anthropic董事会任命成员,并就AI风险与社会影响等关键决策提供建议。伯南克将参与公司的经济研究,帮助理解AI对全球劳动力与经济的影响。


推荐理由:请前美联储主席进入长期利益信托,Anthropic 在治理上下了重注。这不止是人事新闻,更透露了公司对 AI 经济影响的预判——他们正在为系统性风险做准备。