跳到正文
8月25日周二
  1. dex47

    Dex Horthy分享其生产级大型功能的AI驱动开发流程:先产出研究与产品大纲文档,让AI智能体通宵实现、审查与争论,再通过循环反馈打磨。随后与智能体协作将2万+行实现拆分为3-9个独立PR,逐个(1k-3k行)进行反馈、打磨与代码审查。引用@jlongster观点:AI将大任务拆成可独立落地的小型堆叠PR,快速构建大功能后逐项精修至生产就绪,此前拆分工作极为繁重。

    引用James Long@jlongster

    man I love telling ai to take a large piece of work and break it up into small stacked PRs that you can land individually it lets you build something big quick but then you can do a final pass to make it production ready by focusing on individual pieces in order breaking it up was so much work before

  2. Qwen33

    通义千问Qwen3.8-27B在Code Arena: WebDev中以1595分位列总榜第9,是前十名中唯一同尺寸级别模型,并重塑了帕累托前沿。该模型仅比更大的Qwen3.8-Max低6个名次,而4月发布的Gemma 4-31B仅排第80位。

    引用Arena.ai@arena

    Exciting news: Qwen3.8-27B by @Alibaba_Qwen just landed in Code Arena: WebDev at #9 overall with 1595 pts. It is the only model in its size class in the top 10, and also reshapes the Pareto Frontier! It is only 6 ranks behind the much larger Qwen3.8-Max. For scale: Gemma 4-31B which was released back in April sits at #80. Congrats to @Alibaba_Qwen on the release! See thread for more highlights on Qwen3.8-27B.

  3. Elon Musk26

    用户仅用自然语言指令,让 Grok Bot 在几分钟内完成原本需数天的工作:找到并转录 38 个相关视频,精选 13 个最佳片段,剪辑合并为一个 19:35 的视频,并生成包含各片段科学要点及原始时间戳的 Markdown 文件。整个过程无需编写任何脚本或代码。

    引用KanekoaTheGreat@KanekoaTheGreat

    Grok Bot is insane. I asked it to find every video where Dr. Roger Seheult discusses sunlight, red light, infrared light, and mitochondria, including MedCram videos and interviews with Andrew Huberman, Eric Berg, Steven Bartlett, and others. A few minutes later it had: • Found and transcribed 38 videos into one Word document • Picked the 13 best clips explaining the science • Cut and combined them into one 19:35 video I can watch straight through • Created a markdown file summarizing each clip, the science it covers, and the exact timestamp in the original video No scripts. No code. I just told it what I wanted in plain English, and it turned days of work into minutes. As a non-coder, this is the first AI agent that actually feels like a superpower.

  4. Elon Musk25

    Grok Voice 2 很棒 [引用 @SpaceXAI]:Grok Voice Think Fast 2.0 现已在 Artificial Analysis 语音到语音指数中排名第一。 该指数衡量语音智能体能否对所听到的语音进行推理、解决真实客户问题,并使用智能体工具正确完成任务。

    引用SpaceXAI@SpaceXAI

    Grok Voice Think Fast 2.0 is now #1 on the Artificial Analysis Speech-to-Speech Index. This index measures whether voice agents can reason over the speech it hears, resolve real customer issues, and correctly complete tasks using agent tools.

  5. Rohan Paul31

    Rohan Paul 分享 @atomic_chat_hq 的测试:更高量化精度并不自动带来更好结果,Qwen 3.8 27B 的 Q8 版在体素任务上有时被 Q4 版追平或超越。

    引用atomic.chat@atomic_chat_hq

    Qwen 3.8 27B Q4 quant destroyed Q8 at voxel island creation ⛏️ We gave our Atomic Dynamic Q4, Q5, Q6 and Q8 quants the same voxel island tasks: - Cliffside Hamlet - Autumn Road - Winter Cabin - Jurassic Volcano Isle - Pirate Cove Sunset - Overgrown Ruins - Steampunk Sky Island Q8 wasn’t always the best, with Q4 often times producing a comparable or better result, which shows that lower quants are also a viable and more accessible option. AD-Q5_K_M is our top-pick, it fits on a 32GB MacBook Air with 32K content and picks the same next token as the BF16 original 97.3% of the time

8月24日周一
  1. Elon Musk30

    前苹果工程师让 Grok 4.6 在 Cursor 中执行两项任务后睡觉,次日直播验收成果,全程无需人工干预。SpaceXAI 围绕长时运行智能体任务构建 Grok 4.6,测试其能否在无人监督下持续工作,并对比了 Grok 4.6 与 Opus 5 的表现。

    引用Morlex@0xMorlex

    ex-Apple engineer gave Grok 4.6 two jobs inside Cursor, went to sleep, and opened the results live the next morning: no babysitting, no checking every generation, just a model left running on real work for hours. • 00:42 - reveal the website Grok redesigned overnight • 23:21 - go from a voice prompt to a full software stack • 45:43 - inspect the generated code + architecture • 01:21:26 - Grok 4.6 vs Opus 5 • 01:46:31 - live PR + Cloud Agent workflow Most coding demos test an AI for 5 minutes. This tests the thing that matters for agents: can the model keep working when you stop watching it? SpaceXAI built Grok 4.6 specifically around longer-running agent tasks, coding and more ambitious visual work. The endgame isn’t prompting faster. It’s giving an agent a job at night and reviewing finished work in the morning. Worth watching before you choose which model runs your overnight agent loops.

8月23日周日
  1. Ethan Mollick36

    Ethan Mollick 实测神秘模型 Ox Alpha,认为其表现尚可但未达开源权重模型的前沿水平。在其新哥特城市 twigl shader 测试中,Ox Alpha 逊于引用推文中同样开源的 Kimi K3,后者被评价为“非常好的模型”。Mollick 表示仍在继续测试。

    引用Ethan Mollick@emollick

    Kimi K3 on my shader test: "create a visually interesting shader that can run in twigl-dot-app make it like an infinite city of neo-gothic towers partially drowned in a stormy ocean with large waves." "Make it better" Very good model, not Sol Max or Fable, but great open weights

  2. Elon Musk31

    Elon Musk 转发用户实测:Grok Bot 通过带语音的屏幕录像学会用户整理桌面的方式与原因,并自动压缩大视频文件以便观看。该智能体还能就如何录制第二部分给出改进反馈,并主动提问验证理解程度。用户称这将是许多人接触 AI 智能体的入口,并已为妻子开通使用。

    引用Dillon Loomis@DillonLoomis

    Alright, it happened. After a slow start with Grok Bot I just had my mind blown. Twice I did a screen recording with audio of me cleaning up my desktop after a week that resulted in hundreds of random files that all needed particular sorting It's a monotonous task I've always wanted to outsource but didn't really trust other platforms to give that level of access But the mind blowing part was how my Chief of Staff LEARNED not just what I do but HOW and WHY I do things From a screen recording with my voice giving instructions...and because the video file was large my CoS automatically compressed the file under the limit to watch it It then gave me feedback on what to change for how I record part two so it can learn even better And there's more. I planted a quick question in my video recording to see how closely it was watching and listening. You can see my CoS asking me the question in the second screenshot, it's the last chat bubble Soon enough I'll have this painful task automated away. And undoubtedly many, many others in time as well. Thank you @bot This really will be the entry point for many and the beginning of a true paradigm shift. I also got my wife set up with Grok Bot today. This platform is easily accessible by anyone and everyone

8月22日周六
  1. Ethan Mollick44

    Ethan Mollick 认为 LLM 应充当跨领域“通用翻译器”,比起笼统的“简化解释”,更应要求“基于我已懂的知识来讲解”。他引用 Anthropic 员工 @trq212 的推文:Anthropic 内部近期常用 ELI5 技能,通过 `/eli5 <主题>` 指令,以“大图少字”的 HTML artifact 向零基础者解释。

    引用Thariq@trq212

    a skill people at Anthropic have been using a lot recently: ELI5 /eli5 <what you want explained> "explain like I'm someone who knows nothing about this topic, using a HTML artifact with big pictures and few words"

  2. Elon Musk28

    马斯克转发称,用 Grok 机器人“就这么简单”。引用推文展示了 24 小时实战:给 Grok Bot 分配 3 项任务,让它扫描 X 与网页数据、筛选信号并生成简报,用户只需定义目标、授予工具,AI 即可自主执行,工作流从“提示→回答→复制”转向“分配→执行→验证”。

    引用Lummox@Lummox_eth

    I launched Grok Bot for 24 hours, gave it 3 jobs, and stopped treating AI like a chatbot. I had it scan live X + web data for emerging AI products, research what people were actually saying about them, filter the obvious engagement bait, compare sources and turn the strongest signals into a structured brief. At the same time, I could have separate research paths looking at competitors, code or market opportunities instead of forcing everything through one conversation. That’s the difference I underestimated. I don’t want to sit inside a chat writing another prompt every 5 minutes. I want to define the objective, give the agent access to the right tools and data, let it execute, then step back in when judgment or approval is actually needed. The old workflow was prompt → answer → copy → repeat. The workflow I’m moving toward is assign → execute → verify. Once AI stops waiting for your next message, it stops feeling like software you use and starts feeling like work you delegated.

  3. Sherwin Wu29

    太棒了,现在就给我来 14 个 [引用 @kedia_naman]:我最近在 @ChatGPT 上最喜欢玩的一个交互:长按 + 号,拖到最近的照片上,松手即可瞬间附加 你甚至可以在照片还在飞出来的时候选中一张,它会直接变形进入输入框 大家觉得怎么样!

    引用Naman Kedia@kedia_naman

    one of my favorite interactions i’ve been playing with lately on @ChatGPT: long press the +, drag to a recent photo, and let go to attach it instantly you can even select one while the photos are still flying out and and it'll morph right into the composer lmk what y'all think!

  4. Elon Musk34

    Grok Voice Think Fast 2.0 在 Artificial Analysis 新推出的 Speech Agent Arena 中任务成功率排名第一。该基准由真人跨实际场景与隐藏语音智能体对话,衡量 AI 理解请求、调用工具并完成任务的能力,而非仅语音自然度。

    引用X Freeze@XFreeze

    Grok Voice Think Fast 2.0 just ranked #1 on Artificial Analysis’ new Speech Agent Arena for highest Task Success Rate This benchmark actually measures what matters Real people talk to hidden voice agents across practical scenarios. Task Success Rate tracks whether the AI understands the request, calls the correct tools, and successfully completes the job It’s not just about sounding natural. It’s about whether the voice agent can actually get things done Grok finished #1

  5. Elon Musk38

    马斯克转发VulcanBench排行榜,Grok 4.5 High在Eval Suite 3中得分最高,Fable 5 Low紧随其后。VulcanBench是唯一跨推理努力级别评测、且100%真实工程任务的基准。评测者指出,Max effort并非总能提升准确性,反而消耗更多token和时间。

    引用Morgan@morganlinton

    I am going to start to share the leaderboard at VulcanBench more regularly. VulcanBench is the only benchmark I know that benchmarks across effort levels, on an eval suite of 100% real engineering tasks. Getting ready to sunset eval suite 3 and eval suite 4 is almost ready to go. Here's the current leaderboard for Eval Suite 3, Grok 4.5 High is the highest scoring model still with Fable 5 Low, yes Low, right behind it. What I've been able to uncover with VulcanBench is that way too many people are running models at Max effort, thinking that buys them more accuracy, when really it just costs more and uses more tokens so takes more time. If you're still in the mode of, tell my agent to do something then go get coffee, you're probably still living in the past. You can move faster, with higher accuracy, the key is not thinking you need Max effort all the time.

  6. Elon Musk36

    马斯克转发Greg Eisenberg观点,称Grok Bot可能是首个让非技术人员通过AI代理团队运营整个业务的工具。Eisenberg分享其朋友Billy用Grok Bot代理运营整个newsletter业务,并预测将出现超10万家类似企业。他给出最佳实践:每套配置聚焦单一任务、先建Chief of Staff代理、用约束保持专注、决策权在人而非代理。

    引用GREG ISENBERG@gregisenberg

    Grok Bot might be the first tool that lets one non-technical person run an entire business with a team of AI agents. My friend Billy runs his whole newsletter business on Grok Bot agents, and I think we're about to see 100,000+ businesses like his. BEST PRACTICES: 1. The agents run on a shared cloud computer, so running your newsletter, your X, and your receipts all in one place creates context bloat and burns tokens fast. One mission per setup. 2. Start with a Chief of Staff. Give it access to your existing docs (Notion, Slack, Gmail), have it audit the business, then tell you the top three agents to build first to drive revenue. 3. Perfect a task with the Chief of Staff before spinning up a new agent. Have it do the outbound sales once, review it, and only then say "now build a bot that does exactly that." You earn each new hire by proving the task works first. 4. Constraints are the feature. You get a limited number of agents, one thread per bot, like DMs with a teammate. It forces you to stay mission-oriented instead of spinning up a bot for every random idea. 5. You make the decisions, not the agent. Billy's team spent three weeks unable to pick where content should live. At some point you say "we're doing Notion, no more tinkering" and move on. 6. Run week one with no new agents. Build the team, learn to fly the plane, just execute. Week three is when you find the real gaps and expand, someone to man the inbox, someone for the Shopify shop. 7. Then add routines so it works while you sleep. Ask your Chief of Staff what recurring jobs would move the business forward overnight, and it builds the automations that run without you. Thanks to @billyjhowell for sharing the sauce on @startupideaspod (follow for more). Grokbot is really cool. Watch below: http://youtu.be/qQluNEfSVHk?si=3L2cAB71NQSuqxWU

  7. Elon Musk38

    Grok 4.6 在 CursorBench 3.2 上以 70.8% 得分登顶,单任务成本仅 $2.81,比 Fable 5 Max(70.5%,$17.32/任务)便宜约 6 倍,比 Opus 5 Max(70.0%,$8.23/任务)便宜近 3 倍。Elon Musk 推荐通过 Grok Build 或 Cursor 应用使用 Grok 4.6 以获得最佳效果。

    引用Tesla Owners Silicon Valley@teslaownersSV

    BREAKING: Grok 4.6 just took the #1 spot on CursorBench 3.2 — while delivering a massive efficiency advantage. ⚡💻 • Grok 4.6 Extra High — 70.8% | $2.81/task • Fable 5 Max — 70.5% | $17.32/task • Opus 5 Max — 70.0% | $8.23/task • GPT-5.6 Sol Max — 67.2% | $5.69/task Grok achieved the highest score while costing roughly 6× less than Fable 5 Max and nearly 3× less than Opus 5 Max per task. For AI agents, raw intelligence is only part of the equation. The ability to maintain high performance across long coding tasks without burning massive amounts of compute could be a major advantage. Grok’s agentic coding efficiency is becoming seriously impressive. 🚀 Source: CursorBench 3.2

  8. Elon Musk16

    我给我的 Grok Bot 最好的东西之一…… 就是它自己的邮箱地址。 现在它可以: → 发送邮件 → 接收回复 → 验证账户 → 注册网站 → 在自己的工作流中使用邮件 只需 2 分钟…… 现在它可以在没有我的情况下做更多事了。

    引用Liam@liam_fallen

    One of the best things I gave my Grok Bot... Was its own email address. Now it can: → Send emails → Receive replies → Verify accounts → Sign up for websites → Use email inside its own workflows Takes 2 minutes... Now it can do a LOT more without me.

  9. Elon Musk27

    Grok 4.6 在 Extra High 思考模式下以 70.8% 得分登顶 CursorBench 3.2,单任务成本仅 $2.81。相比 Fable 5 Max(70.5%,$17.32/任务)和 Opus 5 Max(70.0%,$8.23/任务),Grok 得分最高且单任务成本分别低约 6 倍和近 3 倍,凸显其智能体编码效率优势。

    引用X Freeze@XFreeze

    Grok 4.6 just took the #1 spot on CursorBench 3.2.....and the efficiency is insane Here's the cost comparison: • Grok 4.6 Extra High — 70.8% | $2.81/task • Fable 5 Max — 70.5% | $17.32/task • Opus 5 Max — 70.0% | $8.23/task • GPT-5.6 Sol Max — 67.2% | $5.69/task Grok achieved the highest score while costing roughly 6X less than Fable 5 Max and nearly 3X less than Opus 5 Max per task That’s what makes Grok so powerful for agents Top-tier intelligence is great.....but top-tier intelligence that can keep working across long coding tasks without burning ridiculous amounts of compute is even better Grok’s agentic coding efficiency is insane

8月21日周五
  1. 🚨 AI News | TestingCatalog31

    NVIDIA 通用编程智能体 AVO 在 ARC-AGI-3 交互推理基准上取得 100% 满分,完成全部 25 个公开环境中的 183 个关卡。AVO 无需指令、显式规则或既定目标即可自主行动,通过持续检查、规划、执行与评估,利用记忆、工具和反馈逐步构建学习能力。

    引用NVIDIA AI@NVIDIAAI

    Our general-purpose coding agent just scored 100% on the ARC-AGI-3 interactive reasoning benchmark. NVIDIA AVO completed all 183 levels across all 25 public environments, figuring out what to do with no instructions, explicit rules, or stated goals.