Emad@EMostaque · 5天前17

anyone hiring witches to save training runs

译有人在雇女巫来拯救训练运行吗？

AYi@AYi_AInotes · 5天前43

Damn，AGI到来之后，品味和审美一定是一个人最核心的竞争力和最强的护城河， Claude Fable 5遇到审美和品味高的，输出质量高到爆炸，这效果真的绝了😭

译天哪，AGI到来之后，品味和审美一定是一个人最核心的竞争力和最强的护城河， Claude Fable 5遇到审美和品味高的，输出质量高到爆炸，这效果真的绝了😭

🚨 AI News | TestingCatalog@testingcatalog · 5天前63

NoimosAI launched an all-in-one autonomous AI marketing team that runs strategy, content, and analysis end-to-end. > It connects to a brand's own apps and websites, blends that with external market data, and acts at the right time on its own. > Outputs land in a Feed for approval and can be routed to Slack, email, or Discord.

译NoimosAI 推出全自主 AI 营销团队，可端到端运行策略、内容创作与分析。它连接品牌自有应用和网站，融合外部市场数据，自主判断执行时机。所有产出汇集到 Feed 供审批，并支持路由至 Slack、Email 或 Discord。功能覆盖 SEO、社交媒体、外联、GEO 等，7×24 小时运行，无需人工干预。

François Chollet@fchollet · 5天前72

Some considerations that many folks seem not to get: 1. It can be a bubble even if the tech works. (For instance, if the tech doesn't have a high-demand use case.) 2. It can be a bubble even if the tech works and has strong product-market fit. (For instance, if the tech cannot be economically viable.) 3. It can be a bubble even if the tech works, has strong product-market fit, and has a path to eventual economic viability. (For instance, if profitability takes too long to achieve or makes margin/competition assumptions that fail to materialize.) 4. It can be a bubble even if the tech works, has strong product-market fit, and is currently highly profitable. (For instance, if demand has a hard ceiling and growth stops once the ceiling is reached.) 5. It can be a bubble even if the tech works, has strong product-market fit, is currently highly profitable, and has unlimited future demand. Literally all it takes for something to be a bubble is for lots of people to over-enthusiastically bet their money on it, and subsequently get panicky. Importantly, bubbles can be attached both to things that are completely hogwash, like the Metaverse, and to world-changing developments like the Internet or railways. Bubbles don't care. They're brought into existence by the thoughts and feelings of investors, not by actual tech or products. "The bubble has burst" doesn't mean "the tech didn't work" or "people stopped using the tech." It only means that people got panicky, investor money dried up, and valuations collapsed. Internet adoption didn't stop in 2000.

译Francois Chollet 指出，许多人误以为只要技术有效、有市场、能盈利甚至需求无限，就不可能是泡沫。实际上，泡沫的定义是投资者过度乐观地押注后恐慌，与技术的实际价值无关。无论技术是像元宇宙那样的噱头，还是像互联网或铁路这样的变革性发明，都可能产生泡沫。泡沫破裂并不意味着技术失败或用户停止使用，只是投资资金枯竭、估值崩溃——就像2000年互联网泡沫并未阻止互联网普及。

elvis@omarsar0 · 5天前42

So the message I am getting is that I can't use Fable to further accelerate AI research and education. No company will decide that for me. Just an absolutely sad day for the research community. As a developer, I already felt ignored, and now this. Damn it!

译所以我得到的信息是，我无法使用Fable来进一步加速AI研究和教育。 没有任何公司能替我做这个决定。 对于研究社区来说，这绝对是个令人悲伤的日子。 作为一个开发者，我已经感到被忽视，现在又这样。 该死！

elvis@omarsar0 · 5天前71

This is awesome! I am spending a lot of time on diffusion LLMs these days, so this is perfect timing. I feel like there are so many underexplored research questions around text diffusion. Weight available in HF.

译太棒了！我最近花了很多时间在研究扩散大语言模型上，所以这个时机恰到好处。我觉得文本扩散领域还有很多未被充分探索的研究问题。权重已在 HuggingFace 上可用。

AK@_akhaliq · 5天前46

ABot-Earth 0.5 Generative 3D Earth Model

译ABot-Earth 0.5 生成式3D地球模型

Rohan Paul@rohanpaul_ai · 5天前56

NoimosAI just launched an autonomous AI marketing team. It connects to a product’s apps, website, and data sources, then plans and runs growth work across SEO, GEO, social, outreach, and conversion. The product is built around a clear bottleneck: AI has made product building faster, but distribution still depends on traffic, leads, content, timing, and repeated testing. So NoimosAI is trying turn that marketing grind into a daily operating loop, where the system studies your business, suggests high-impact work, runs tasks 24/7, and sends finished outputs for approval.

译NoimosAI 推出全合一自主 AI 营销团队。连接产品应用、网站及数据源后，系统自动规划执行 SEO、GEO、社交媒体、外展和转化等增长工作，24/7 运行并将输出结果送交审批。产品基于一个关键洞察：AI 虽加速了产品构建，但分发仍依赖流量、线索、内容和反复测试，因此 NoimosAI 试图将营销流程转化为日常自动运营闭环。

Sundar Pichai@sundarpichai · 5天前75

DiffusionGemma is an open, experimental model that brings our text diffusion research to Gemma 4. It’s a racehorse 🏇achieving up to 4x faster inference by generating entire blocks of text simultaneously vs predicting token-by-token (word-by-word) output!

译DiffusionGemma 是一个开放的实验性模型，它将我们的文本扩散研究引入 Gemma 4。它是一匹赛马 🏇，通过同时生成整块文本（而非逐 token（逐词）预测输出）实现高达 4 倍更快的推理速度！

Epoch AI@EpochAIResearch · 5天前48

How should we think through various proposals for sharing the gains of AGI? According to @pawtrammell and @ansonwhho, the leading proposals for universal redistribution after AGI differ along a primary axis: how much direct control over capital they propose giving citizens. 🧵

译我们应该如何思考各种关于分享AGI收益的提案？ 根据@pawtrammell和@ansonwhho的观点，AGI后普遍再分配的主要提案在一个主要轴线上存在差异：它们提议给予公民多少对资本的直接控制权。🧵

Claude@claudeai · 5天前72

New from Code with Claude Tokyo: scheduled deployments and environment variables in vaults are in public beta in Claude Managed Agents, and dynamic workflows in Claude Code are generally available. Agents now run on a schedule, use your tools securely, and take on bigger jobs.

译Code with Claude Tokyo 新功能：定时部署和保险库中的环境变量已在 Claude Managed Agents 中进入公测，Claude Code 的动态工作流已正式可用。 Agent 现在可以按计划运行，安全使用你的工具，并承担更大的任务。

向阳乔木@vista8 · 5天前32

对比 Fable 5，忽然觉得把大模型变便宜这件事儿真的很重要。 真的要夸下DeepSeek，实在是便宜。 每月用 v4 flash 翻译不少东西，一看账单才花几十块。 把自己的 AI 雷达 Skill 变成网站，支持双语对照翻译和 AI 侧边栏对话。 下周开源，本周先上网站，输入DeepSeek API能用 AI 功能，也能人工点评

译作者对比 Fable 5 后强调，把大模型变便宜至关重要。他称赞 DeepSeek 极低的成本——每月使用 v4 flash 翻译大量内容，账单仅几十元。作者将自己的 AI 雷达 Skill 做成网站，支持双语对照翻译和 AI 侧边栏对话。网站本周先上线（输入 DeepSeek API 即可使用 AI 功能，也可人工点评），下周将开源。

Fei-Fei Li@drfeifei · 5天前20

Scientific research is fundamental to advancing civilization and helping people globally to solve the most critical problems, from medicine to materials, from brain science to physics, and much beyond. This is only possible when scientists have access to the best tools of the time to conduct scientific research, including having access to AI-based tools.

译科学研究是推动文明进步、帮助全球人民解决最关键问题的基础——从医学到材料，从脑科学到物理学，乃至更广泛的领域。这只有在对科学家拥有时代最佳工具（包括基于AI的工具）来进行科学研究时才有可能实现。

Chubby♨️@kimmonismus · 5天前61

Everyone is talking about basic chat apps, but desktop AI agents are completely shifting how we work in 2026. I’ve been testing Tencent WorkBuddy now that it’s finally going global. It dropped in China back in March and instantly hit number one for daily active PC users according to Tencent’s Q1 earnings. @TencentAl_News

译人人都在谈论基础聊天应用，但桌面AI智能体正在完全改变2026年的工作方式。 我已经测试了腾讯工作助手，它终于走向全球。它于3月在中国发布，根据腾讯Q1财报，其PC日活跃用户数立即排名第一。@TencentAl_News

Chubby♨️@kimmonismus · 5天前61

Most "AI marketing" tools are basically Zapier with a chat box. NoimosAI plays in a different league. It plans the strategy, creates the content, ships it across every channel and analyzes what worked, then adjusts on its own. You connect your stack and it starts working in your brand voice the same day. There's a 7-day free trial, so you can watch it run before you commit.

译Kim 介绍 NoimosAI 是不同于普通 Zapier+聊天框的 AI 营销工具：它能自动制定策略、创建内容、跨渠道发布、分析效果并自主调整。用户连接现有工具后当天即可按品牌语调工作，提供 7 天免费试用。引用推文称其为全球首个全自主 AI 营销团队，覆盖 SEO、社交、外展、GEO 等，24/7 无人值守运行。

Google DeepMind@GoogleDeepMind · 5天前72

DiffusionGemma is our new experimental open model with up to 4x faster output on dedicated GPUs. Instead of predicting word-by-word, it generates entire blocks of text simultaneously. This lets the model self-correct and format complex markdown in real time.

译DiffusionGemma 是我们新的实验性开放模型，在专用 GPU 上输出速度最高可提升 4 倍。 它不是逐词预测，而是同时生成整块文本。这让模型能够自我纠正，并实时格式化复杂 Markdown。

🚨 AI News | TestingCatalog@testingcatalog · 5天前40

Meta is working on support for Custom Instructions for Meta AI on the web.

译Meta 正在为网络版 Meta AI 开发自定义指令支持。

Kling AI@Kling_ai · 5天前25

What’s inside this football? ⚽

译这个足球里面有什么？⚽

SiliconFlow@SiliconFlowAI · 5天前58

If you need one model for agents, long context, and multimodal inputs — this is it. Meet @GoogleDeepMind 's Gemma 4 12B on SiliconFlow 🔥 💰Input / Output: $0.1 / $0.3 per 1M tokens on SiliconFlow 🛠️ 262K Context | Built-in Thinking | Native Tool Calling | 140+ Languages ✨ Encoder-free architecture: vision and audio inputs flow directly into the LLM backbone, reducing process latency 🧠 12B Size, 26B Brain: nearing Google's 26B performance, excel at multi-step reasoning and agentic workflows Try it on SiliconFlow ⬇️

译Google DeepMind 的 Gemma 4 12B 已在硅基流动上线，定价输入 $0.1/1M tokens，输出 $0.3/1M tokens。支持 262K 上下文、内置思考、原生工具调用及 140+ 种语言。采用无编码器架构，视觉和音频输入直接注入 LLM 主干，降低处理延迟。12B 参数但配备 26B “大脑”，性能接近 Google 26B 级别，擅长多步推理与智能体工作流。

Chubby♨️@kimmonismus · 5天前58

This is one of the most important parts of the Mythos 5 announcement: Drug design. Anthropic says its internal protein design experts used Mythos 5 to accelerate parts of the drug design process by around 10x. In one example, Mythos 5 used protein design and bioinformatics tools without (!) human assistance and matched or beat skilled human operators. It means the model could run parts of the early drug discovery loop itself: choosing binding sites, selecting tools, running protein design workflows, recovering from failures, and generating promising candidates. And here is what people still dont understand outside of our community: AI is moving from "assistant that explains science" to "agent that can actually execute parts of scientific work." The future of drug discovery may look less like one scientist manually testing ideas one by one, and more like thousands of AI-driven research loops running in parallel, with humans validating, interpreting, and deciding what actually moves forward. I keep thinking about what Demis Hassabis said: we are entering the golden age of science. There is probably no doubt about that anymore. Medicines are being developed faster and more precisely, and previously incurable diseases are becoming treatable.

译Anthropic内部蛋白质设计专家使用Mythos 5将药物设计部分流程加速约10倍。在一例中，Mythos 5无需人类协助即可自主使用蛋白质设计和生物信息学工具，匹配或超越熟练人类操作，能独立完成早期药物发现中的结合位点选择、工具调用、工作流运行、故障恢复和候选生成。在Gemini 3.5 Pro和GPT-5.6临近发布的背景下，Anthropic凭借Mythos/Fable进入新层级，给竞争对手带来压力，其IPO前景也因此提升。

Chubby♨️@kimmonismus · 5天前73

OpenAI appears to be preparing for a possible IPO within the next year, but Sam Altman is keeping the door open. If recursive self-improvement starts looking real, staying private could become the smarter move. At the same time, OpenAI’s enormous compute needs may push it toward public markets sooner, while the company is also preparing a new model, codenamed 5.6, described internally as a meaningful improvement over GPT-5.5. via The Information

译The Information 报道，OpenAI 正筹备未来一年内 IPO，CEO Sam Altman 持开放态度：若递归自我改进趋势显现，私有可能更明智；巨大计算需求也可能推动更早上市。公司同时准备代号 5.6 的新模型，内部描述为对 GPT-5.5 的有意义改进。本周早些时候，Altman 与首席科学家 Jakub Pachocki 已向员工发送备忘录讨论上述事宜。

OpenRouter@OpenRouter · 5天前66

Today we're launching the new Activity explorer on OpenRouter. It's the best way to see how much and your team are spending on every model, along with tokens, cache hit rate, agents, & trends. All updated in real time. See how our team is using Fable and other models 👇

译今天，我们在 OpenRouter 上推出了新的 Activity explorer。 这是查看你和团队在每个模型上花费了多少的最佳方式，还包括 token、缓存命中率、智能体以及趋势。所有数据实时更新。 看看我们的团队如何使用 Fable 和其他模型 👇

ChatGPT@ChatGPTapp · 5天前69

Go #MessiMode Upload a photo of yourself and try this prompt: “Make my hair the colors of my country flag but keep it natural-looking. If no country or image is provided, ask."

译Go #MessiMode 上传一张你的照片并尝试这个提示词：“将我的头发变成本国国旗的颜色，但要看起来自然。如果没有提供国家或图片，请询问。”

AYi@AYi_AInotes · 5天前71

怎么让Claude Fable 5做一个关于他自己的网站？ 这个提示词结构很顶，完全可以拿去让Fable做一个个人网站啊，效果真的很炸🤯 Prompt: 生成一个关于你自己的登录页面：Claude Fable 5， 你完全自由，但要确保它视觉吸引人，简洁，互动性强，带有动态动态效果，彩蛋， 搜索并使用2026设计趋势。

译推文分享了一个让 Claude Fable 5 生成关于自身登录页面的提示词结构。提示词要求完全自由，视觉吸引人、简洁、互动性强、包含动态效果和彩蛋，并搜索使用 2026 设计趋势。引用推文显示结果令人惊艳。作者认为该提示词结构同样适用于创建个人网站。

OpenAI Developers@OpenAIDevs · 5天前40

For musician and composer @sound4movement, Codex works like a studio assistant. He asks for a piano track in 3/4, sets the tempo and harmony, then describes how the performance should build. Codex handles the setup in Ableton Live. Michael stays focused on the creative work.

译对于音乐人和作曲家 @sound4movement，Codex 就像一个工作室助手。他要求一个 3/4 拍的钢琴轨道，设置速度和和声，然后描述表演应该如何构建。Codex 在 Ableton Live 中处理设置。Michael 则专注于创作工作。

DogeDesigner@cb_doge · 5天前22

The future of AI is multiplanetary.

译AI的未来是多行星的。

🚨 AI News | TestingCatalog@testingcatalog · 5天前45

ANTHROPIC 🔥: Voice Mode on Claude will soon include a model selector. > Earlier, a language selector was added as well. > Currently, it says that Claude Haiku 4.5 is being used, regardless of the selected model. This may mean we have hope for a non-TTS voice mode, too, as it seems Anthropic is preparing a major upgrade. Fingers crossed 👀

译ANTHROPIC 🔥：Claude 的语音模式即将包含模型选择器。 > 此前，语言选择器也已添加。 > 目前，无论选择哪个模型，系统都显示正在使用 Claude Haiku 4.5。 这可能意味着我们也有望获得非 TTS 的语音模式，因为 Anthropic 似乎正在准备一次重大升级。 期待 👀

SemiAnalysis@SemiAnalysis_ · 5天前62

AI market beat 2025 expectations by massive margins. But here's what's wild about the composition of this beat.

译AI市场以巨大幅度击败了2025年的预期。但关于这次超预期的构成，疯狂之处在于——

elvis@omarsar0 · 5天前52

This is why frontier open models are crucial. This is extremely sad for the research community.

译这就是前沿开源模型至关重要原因。 这对研究社区来说极为可悲。 mythos 会在 AI “前沿大语言模型研究”任务上故意表现差，这对研究社区来说非常非常可悲。 而且这种故意行为对用户不可见，太疯狂了。

向阳乔木@vista8 · 5天前36

忙活一天，还没顾上体验 Claude Fable 5，打开Happycapy试试。 让它开发一个在线RSS阅读器，待会看结果。 看了不少海外分享，都建议把最有雄心的项目交给它做。 咱普通人又不搞科研，几乎没啥特别有挑战的项目。 就写作任务来说，大家反馈Fable 5还不如Claude 4.6... 问有更好的吗？卡神说：4.5

译用户打算用 Claude Fable 5 开发一个在线 RSS 阅读器，但尚未正式体验。海外多数分享建议用 Fable 5 处理最具雄心的项目。不过写作任务方面，反馈称 Fable 5 不如 Claude 4.6；当询问更优版本时，有用户（卡神）推荐 Claude 4.5。

AYi@AYi_AInotes · 5天前61

我尼玛，Claude Fable 5今天把整个软件行业的底层逻辑给击穿了！ 以前做软件要几个月，现在只要15分钟，Claude Fable 5把产品经理和程序员的中间环节，直接干掉了。 也就是说，15分钟的销售电话打完， AI当场做出了客户要的可运行软件原型，喵个咪，这谁受得了啊🤯 Todd Saunders，Dalton Mills AI 的 CEO，做的是 trades 行业的垂直 SaaS——建筑、家政、暖通这些。 他用刚发布的 Claude Fable 5， 在跟一个客户的销售电话里， 让 AI 在后台实时转录通话， 同时自主构建客户刚刚提到的软件功能。 通话结束，他当场演示了一个完全可运行的原型，精确匹配客户 15 分钟前描述的需求。 一个语音报价系统：AI 实时听服务电话，自动匹配价目表，识别 upsell 机会，生成 Good/Better/Best 三档方案，自动发提案短信。整个过程近乎零人工干预。 不是 简单的AI 辅助开发，直接对话即构建，damn！ 平复下激动的心情，这个案例最让我震惊的不只是AI 写代码快，AI 真的能听懂人话了啊啊啊， 然后一个长达几十年的产品开发范式，就这么被直接击穿了，holy sh*t！ 想一想过去几十年我们怎么干活的，客户跟你说工人在现场太乱经常算错钱，你记下来，回去消化，以为懂了， 画原型，约评审，排期，开发，几周后拿出来， 客户摇头说不对不是这么回事， 你一肚子委屈，说我每个字都记了，他说你记的是我说的话，不是我脑子里的东西。 这个循环叫理解-翻译-验证，短则几周长则几个月，整个行业就吃这碗饭的，我们管它叫专业服务。 但是今天，Fable 5 把这个循环干掉了，不是压缩啊兄弟们，直接彻底干掉了， 客户说，AI 听，AI 当场做出来，客户当场看对不对， 没有 PRD，没有你在内部群里发那个需求我回去评估一下，没有一切中间件， 从客户嘴里说出来的那一刻，一个能跑的东西就在屏幕上等着他。 这才是真正要命的地方，这哪是提效啊，简直把整个底层逻辑都改变了。 但我们也必须立刻面对一个最尖锐的问题，就是那客户为什么还需要你？这不就 15 分钟的事吗？ 这个问题必须正面面对，确实是客观存在的， 如果你对自己的定位只是把客户需求翻译成代码的那个人，那你完全可以被这 15 分钟取代，因为 AI 现在翻译得比你快，还不用开评审会。 但如果你做完项目就知道，原型和系统，中间隔着的不是几行代码，还有权限体系里那几十个你不知道为什么会存在的字段， 是客户二十年前的财务系统里藏着的那个没人敢动的数据表，是工人在负二层没信号的地方操作时该怎么缓存，也是某个老小区因为水压问题装不上你方案里那个完美的配件， 又或者是当地监管对报价条款里的某个措辞有特殊要求，这些东西，Fable 5 不知道，你问它它也不知道，它甚至不知道它不知道。 它的原型是乐高模型，系统是能住人的楼，之间的差距，专业术语叫工程判断，也可以叫领域责任，更可以叫为长期可用性兜底。 所以这个案例真正揭示的，不是谁会被替代，是什么在剧烈地变稀缺。 第一样，把 AI 的生成能力锚定在真实世界的复杂约束里， 这一下子就筛掉两种人：只会做原型不会做系统的人，和只会做系统但不懂行业的人。 留下的是那种，你问他这个需求能不能做，他会先问你那边现场平均信号几格、工人习惯左手拿手机还是右手、他们现在用的那个老系统数据库编码是 UTF-8 还是 GBK 的人。 第二样，领域知识， 我说的不是行业报告里那些漂亮话，是那些只有在这个行业干了十年才知道的脏东西。 AI 能生成完美的三档报价界面，但它不知道某个配件的供应商在雨季会涨价 30%，不知道某个话术在北方好使在南方会让客户挂电话，不知道这个工种的师傅脾气大你不能在流程里多加一步确认否则他宁愿不干，这些脏知识才是真正的护城河。 第三样，也是最被低估的一样：把原型变成可信赖系统的治理能力。 评估框架你怎么建，AI 改了这一处你怎么知道没把另一处改坏。 记忆持久化你怎么做，客户上次改的需求下次对话能不能记住。 错误恢复你怎么设计，流程跑到一半 AI 崩了用户看到什么。 多代理协作你怎么编排，一个 Agent 听电话提取意图，一个匹配价目表，一个检查合规，一个生成界面，人类在哪个节点介入裁决。 这些东西不酷，开会聊这些会让人想抽烟，但就是从酷到能用的最后那一公里。 Fable 5 和后续更强的模型，把生成这件事的成本和速度打到了一个新的量级。 这个量级意味着，做出一个看起来能用的东西，以后不再是任何人的竞争力。竞争的分水岭是，谁能把 AI 吐出来的东西，变成一个别人敢在上面跑业务、能长期依赖、出了问题找得到人负责的系统。 扯了这么多，最后一句话给大家共勉： 从今天起，把 80% 的精力，从怎么让 AI 生成得更快，转移到怎么为 AI 生成的东西负责，说白了，酷是给外人看的，稳是给我们自己续命的。

译SaaS公司CEO Todd Saunders使用新发布的Claude Fable 5，在客户销售电话中实时转录通话，AI自主构建客户描述的功能。通话结束即展示完全可运行的原型——语音报价系统，自动匹配价目表、识别upsell机会、生成三档方案并发送提案，全程零人工干预。这直接跳过了PRD、评审、开发排期，实现“对话即构建”。但将原型落地为可信赖系统仍需工程判断、领域脏数据和治理能力，这些才是真正的稀缺价值。

向阳乔木@vista8 · 5天前47

文章提到DeepSeek目前满足于落后美国公司约 6 个月...... 这有点扯吧。 中国每家大模型公司都受限于显卡和技术，不是不想追啊，谁想落后，谁安于落后。

译@NikoMcCarty 探访DeepSeek总部称，这家300人、2023年由梁文锋创立的公司脱胎于幻方，位于杭州无标识大楼，2025年1月发布R1模型，团队年轻，目前满足于落后美国约6个月，保持低调。Vista反驳：中国大模型公司并非安于落后，而是受限于显卡和技术条件。

向阳乔木@vista8 · 5天前74

演示视频中的书籍解读口播脚本 Skill 开源了 https://github.com/joeseesun/qiaomu-book-script 安装指令：npx skills add joeseesun/qiaomu-book-script 只需要说：解读《被讨厌的勇气》 Skill 会调用多个Subagent从不同角度写脚本，最后主LLM整理成终稿。

译Vista 开源的 qiaomu-book-script Skill 可通过 `npx skills add joeseesun/qiaomu-book-script` 安装。用户说“解读《被讨厌的勇气》”即可触发，多个 Subagent 分别撰写脚本，最后由主 LLM 整理成终稿。此前 Vista 已用该 Skill 生成口播脚本并完成录制。

Nathan Lambert@natolambert · 5天前56

Many AI leaders in the US accused Chinese LLMs of subtle manipulation of the user (without proof, but it's hard to prove). But then the leading American lab documented manipulation of their users. Can't make this up.

译许多美国 AI 领袖指责中国大语言模型对用户进行微妙操纵（没有证据，但很难证明）。但随后，领先的美国实验室记录了对他们用户的操纵。真是编都编不出来。

DogeDesigner@cb_doge · 5天前41

SpaceX achieved all of this without any use of AI

译SpaceX 在没有使用任何 AI 的情况下实现了所有这一切。

fofr@fofrAI · 5天前47

I asked Fable to invent a new color, and I got my first "chat paused". It did however decide to pursue a strategy of shining lasers in your eyes to trigger otherwise impossible cone activations 🤯

译我让 Fable 发明一种新颜色，然后我收到了第一次“聊天暂停”。 不过它决定采用一种策略：把激光射到你的眼睛里，触发原本不可能的视锥细胞激活 🤯

Berryxia.AI@berryxia · 5天前10

按照这个架势，Codex 不得立马要Reset一下啊！ GPT-5.6摩拳擦掌该抛出来了啊，奥特曼~👊🏻

Berryxia.AI@berryxia · 5天前48

Fable 5 VS Opus 4.8 VS Gemini 3.1 Pro VS GPT 5.5 只有Google 还拿着去年的模型在玩儿~

Kling AI@Kling_ai · 5天前54

In June 2024, a group of creators began creating with Kling AI. Besides "this is amazing," we heard one phrase more than anything else: "If only." If only characters felt more alive. If only movement felt more real. If only she could speak. For two years, we heard this over and over again. And with every iteration of our product, we listened. From Kling 1.0 to 3.0, every breakthrough began with a creator saying: "If only it could be better." In June 2026, Kling AI has reached over 100 million users worldwide. As we celebrate our Anniversary II, we want to say thank you to every creator. Kling has grown with you, every step of the way.

译2024年6月，创作者开始使用可灵Kling AI。用户反复提出“如果角色更生动”“如果动作更真实”“如果她能说话”等需求。从Kling 1.0到3.0，每次迭代都基于创作者反馈改进。2026年6月，可灵Kling AI全球用户突破1亿。官方在二周年之际向所有创作者致谢。

Rohan Paul@rohanpaul_ai · 5天前71

Reuters: India’s biggest private employer TCS's Chairman ‌ AI agents could become as numerous as TCS employees. The Chairman said: "Some of the work being done will go to AI agents. That will be the ​nature of the transition that we have to go through ​not only ⁠as a company, as an industry, and as a country" . TCS has already announced 12K job cuts, reported $2.3B in annualised AI revenue, and has an OpenAI data-centre agreement, so this is not just talk from management. TCS has about 600K workers, so Natarajan Chandrasekaran’s claim points to a future where software tasks are handled by hundreds of thousands of digital agents rather than only human engineers. The company expects hiring to fall as AI takes over more coding, testing, support, maintenance, and back-office work, although Chandrasekaran also said new AI-related roles will appear. This hits India’s $315B IT services model hard because firms like TCS and Infosys grew by supplying large teams of lower-cost engineers to global companies. AI weakens that model because one agent can perform repeatable software work at scale, reducing the need to keep expanding human headcount for every new contract. --- IMO, India’s whole $315B tech-services industry was built on sending work to lower-cost human teams, and even recent outsourcing guides still describe offshore BPO as attractive mainly because staff costs are lower than in Europe and the US. If AI agents can do that same repeatable coding, testing, IT support, finance processing, or customer-service work, the buyer no longer needs India as the labor location, because the “worker” can run inside a US or European cloud stack, under local data rules, closer to the company’s own systems. That means the BPO threat is not only job loss at TCS; it is a possible collapse of the old outsourcing bargain, where cost savings came from moving work to cheaper people, while the new bargain may come from replacing the location advantage with software automation, especially when TCS itself says AI agents could match its human workforce --- reuters .com/world/india/indias-tcs-chairman-expects-ai-agents-equal-employee-count-2026-06-09/

译印度最大私营雇主TCS董事长Chandrasekaran称，未来AI agent数量可能达到公司员工数（约60万）。TCS已宣布裁员1.2万人，AI业务年化收入达23亿美元，并与OpenAI签署数据中心协议。他指出AI将接管编码、测试、支持、维护等重复性工作，尽管也会创造新AI岗位。这一趋势直接冲击印度3150亿美元的IT服务外包模式——传统上依赖低成本人力团队的优势将被AI agent取代，因“工人”可在美欧云堆栈中运行，无需转移劳动力。分析认为，这可能导致旧外包模式（靠低成本人力差获利）崩塌。