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AI won't replace people. People using AI will replace people who don't. 真正拉开差距的，非 AI 本身，而是每天都在用 AI 的人。 #AI# #ChatGPT# #AIAutomation# #AITools# #Productivity# #FutureOfWork# #WorkSmart# #Automation# #DigitalSkills# #PersonalGrowth# #BuildInPublic# #OnlineBusiness# #CreatorEconomy# #TechTrends# #Web3# #Cryptocurrency#

AI Practical Use #3#: Let AI help you with Excel data analysis. AI 实用玩法第 3 个： 让 AI 帮你做 Excel 数据分析。 Here is a very common office situation: You have an Excel file with sales data, costs, profit, regions, products, and dates. Normally, you may spend 2 hours writing formulas, checking data, making summaries, and building charts. But with AI, you can finish the first draft in about 10 minutes. 一个很常见的办公场景： 你手里有一份 Excel 数据， 里面有销售额、成本、利润、区域、产品、日期。 以前你可能要花 2 小时： 写公式、查数据、做汇总、看趋势、做图表。 现在可以先交给 AI， 10 分钟生成初步分析结果。 You don’t need to manually type every complex formula. Let AI help you: Build formulas Summarize key findings Find abnormal data Compare trends Suggest chart formats Create a report structure 你不需要自己一个个输入复杂函数。 可以让 AI 帮你： 生成公式 总结关键结论 找出异常数据 对比趋势变化 建议图表形式 生成汇报框架 Here is a simple prompt: 这里有一个简单提示词： Please analyze this Excel data. Help me build the right formulas, summarize the key findings, find possible errors or abnormal values, and suggest the best chart or report format. I will review and verify the final results. 中文版本： 请分析这份 Excel 数据。 帮我生成合适的公式，总结关键结论，找出可能的错误或异常值，并建议最适合的图表或汇报格式。 最终结果由我来审核确认。 The key idea is simple: AI does the heavy first draft. You review the logic and final result. 核心思路很简单： AI 负责先把复杂工作做出来， 你负责审核逻辑和最终结果。 Before: 2 hours manually writing formulas. After: 10 minutes with AI assistance. 以前： 手动写公式、做分析，可能要 2 小时。 现在： 借助 AI，10 分钟先完成初稿。 AI is not here to replace your judgment. It helps you save time on repetitive work, so you can focus on checking, thinking, and making better decisions. AI 不是替代你的判断力。 它是帮你节省重复劳动的时间， 让你把精力放在审核、思考和决策上。 Let AI write the formulas. You review the results. 让 AI 写公式， 你负责审核结果。 That is a smarter way to work. 这才是更聪明的办公方式。 #ChatGPT# #AI# #AITools# #Excel# #ExcelTips# #DataAnalysis# #Productivity# #WorkSmarter# #OfficeWork# #BusinessTools# #Automation# #DigitalTools# #TechTips# #FutureOfWork# #PromptEngineering#

正好最近我也在筹备，所以做过计算。 主要的 GPU 是 RTX PRO 6000 Blackwell Max-Q 96GB X 4 用 Max-Q 版本主要是因为功耗是 300 瓦，而标准的 RTX PRO 6000 Blackwell Workstation Edition 是 600W 。虽然 Max-Q 的峰值性能会稍微低一些，官方数据是 3511 AI TOPS 对 4000 AI TOPS，大概少了 12%，但两者都是 96GB GDDR7 ECC 显存，1792GB/s 显存带宽，对于 AI 视频生成来说，最重要的就是显存容量。 而且一旦用到四张 GPU，功耗差距就非常明显。4 张 Max-Q 满载是 1200W，4 张标准版单 GPU 理论功耗加起来就是 2400W。 这就意味着标准版已经很难按照普通工作站的方式长期运行。而前者仍然是可以家庭化办公使用。 对于 AI网剧，我个人也更看重并行产能。一个剧集最后可能有几百个镜头，与其让一张 600W 的卡把一个镜头生成得快一些，肯定不如四张 96GB 的 GPU 可以同时跑四个不同镜头。一张负责正式镜头，一张跑失败镜头重做，一张跑人物或者场景相关任务，一张继续处理下一批镜头，机器可以全天保持任务队列。 这样一台机器最终就是 4×96GB，一共 384GB 的物理显存资源。 当然对于新手来说，没有必要上来就拉满 4 块 GPU ，所以我自己的思路是先把工作站（主机）按照最终 4 卡规格买好，初期只装 1 至 2 张 RTX PRO 6000 Max-Q，等用工熟练并且能把生成队列跑满以后，再逐渐增加到 3 张、4 张。 如果最终做到 4× RTX PRO 6000 Max-Q 96GB，我现在估算整台高配工作站的硬件投入大约在 13 万到 15 万新币，大概就是 70 万到 80 万人民币。 其中最大投入就是 GPU 了，现在新加坡一张 RTX PRO 6000 Blackwell Max-Q 96GB 的公开价格大约是 24,550 新币。光 GPU 就已经接近十万新币。 另外就是软件部分，我大概列一下： 1. 核心生成平台：ComfyUI 2. 静态图阶段：Qwen Image 系列 3. 视频核心：Wan 2.2 4. 人物一致性和控制工具：LoRA，ControlNet / OpenPose 以及 IPAdapter / Reference 类工作流。 5. 后期软件：DaVinci Resolve 6. 声音部分：TTS / AI 配音 或 Character Voice Bible 我现在已经开始尝试做简单的内容了。当然主要是 AI 做，我负责打酱油。

🚨 BREAKING: Apple filed for a PRELIMINARY INJUNCTION against OpenAI AND asked a federal judge to put them under forensic supervision "Apple respectfully moves the Court for a preliminary injunction to stop THE THEFT OF ITS TRADE SECRETS" Apple filed NINE sworn declarations, a 28-page memorandum and a concurrent motion for expedited discovery What Apple now says, under oath: Chang Liu: 8 years at Apple, now OpenAI "Member of Technical Staff" exploited an authentication bug to steal Apple trade secrets "on AT LEAST FIVE SEPARATE OCCASIONS" from February to April 2026, WHILE working for OpenAI Liu downloaded "THOUSANDS OF PAGES of Apple's most sensitive trade secrets" The stolen files, NAMED: >DisplayNotes.key — "several hundred pages" on Apple's custom display power development program >Architecture analyses. Fabrication decisions. Testing results >Engineering data for an UNANNOUNCED Apple product: 'touch, display, and power systems" >Final.key + V2.key — compilations of two undisclosed Apple R&D projects >and those are "only four of the dozens of proprietary documents Mr. Liu stole" Liu fed OpenAI "a steady stream of Apple proprietary information that he actively concealed" Liu also "coached Yu-Ting "Alyssa" Peng, then still INSIDE Apple, how to access and copy files from Apple workstations "to avoid trouble with the security team" and directed her to communicate with him on the encrypted LINE app "to avoid detection" Tang Yew Tan: 24-year Apple VP, now OpenAI's Chief Hardware Officer, "used an Apple internal project codename for an unannounced product to elicit still more trade secrets from job candidates." Tan's own messages, quoted in the motion: >"Just like last time, bring some parts you worked on" >"mlb, battery, shields type of stuff is interesting" OpenAI recruiter, quoted: "No, you won't sign anything at the exit interview. If they do ask you to sign anything, let me know asap." APPLE TOLD FEDERAL JUDGE: >"OpenAI knows its misappropriation is wrong and has tried to conceal it." >"This is not a case of 'mere hiring'... it is a case of repeated instances of deliberate theft." Apple says OpenAI went after its SUPPLIERS: >OpenAI "directed a trusted Apple partner [name redacted] to perform [Apple's proprietary metal finishing] process for them, knowing it was proprietary to Apple... because they were involved in this partnership while at Apple." Apple put its own Surface Finishing Manager, Jackie Hughes, under oath to prove it. Apple named ELEVEN MORE former Apple employees at OpenAI — beyond Liu, Tan, and Peng — Fourteen people total. Apple also filed a concurrent motion for EXPEDITED DISCOVERY demanding depositions: - Liu. Tan. Peng. - A fourth unnamed OpenAI employee - Plus OpenAI itself, under oath, through Rule 30(b)(6) Apple has asked a federal judge to put OpenAI under forensic supervision RIGHT NOW: >Forensic inspection of ALL OpenAI devices >ALL cloud storage, Slack, email >Including anything that "previously contained" Apple data — deleted included Demanding the "first available hearing date," citing "imminent threat" to its trade secrets. APPLE: > "The harm is happening now — every day that passes without an injunction allows OpenAI to embed their knowledge of Apple's stolen information into its hardware development efforts." Hearing: October 1, 2026. Judge Edward J. Davila. ITS HAPPENING

Meet Qwen3.8-Max. Your always-on workmate for • Coding • Reasoning • Research • Writing • AI Agents You live your life. It does the work. Try it & API on • Model Studio: • Qwen Cloud: #BuildWithQwen# #AlibabaCloud# #QwenCloud# #ModelStudio#

Our robot intern just reached another milestone. Earlier this year, Xiaomi's humanoid robot began its internship at Xiaomi EV Factory. After one quarter, its dual-side task success rate at the self-piercing nut workstation reached 98%—just 1 percentage point shy of the success rate achieved by experienced human operators. Now it's taking on two new factory roles: • Center console side-cover sorting • Returnable box folding Both have already achieved over 90% task success. Every new task is another step toward real-world deployment. #HumanoidRobots# #Manufacturing# #EmbodiedAI# #Robotics# #Xiaomi#

Linux RAM requirements are wild 🤯 • 🟠 Ubuntu - 6 GB • 🎮 SteamOS - 4 GB • 🚀 Pop!_OS - 4 GB • 🔵 Fedora - 2 GB • 🎩 Red Hat Enterprise Linux - 2 GB • 🦎 openSUSE - 2 GB • 🍃 Linux Mint - 2 GB • 🪟 Zorin OS - 2 GB • 🛡️ Kali Linux - 2 GB • 🏔️ Manjaro - 2 GB • 🏔️ Rocky Linux - 2 GB • 🎯 CentOS Stream - 2 GB • 🕊️ Lubuntu - 1 GB • 📦 Debian - 512 MB • 🐧 Arch Linux - 512 MB • 🪶 Puppy Linux - 256 MB • 💿 Tiny Core Linux - 64 MB Linux can run on everything from a potato to a workstation. Which distro are you using right now? 👀

Huge: NVIDIA just put a gaming PC, an AI workstation, and a GPU server into a laptop thin enough to disappear in your bag 😳 For 30 years, the PC has been the same thing: Intel or AMD inside, GPU on the side, and hope it doesn't crash. At Computex, Jensen Huang showed off RTX Spark: an ARM-based AI PC chip built around a Blackwell RTX GPU, a 20-core Grace CPU, and 128GB of unified memory. And it fits inside a 14mm laptop 🤯 On stage, it ran Forza Horizon 6 and 007 First Light at 100 FPS in 1440p. On battery. On Windows. Without throttling. The crazy part? It can run 120 billion parameter AI models on-device. No cloud. No API. No subscription. That means your AI agent no longer has to live in someone else’s data center. It can live on your machine. Always available. Private by default. Yours alone. This is the shift NVIDIA is really betting on: the laptop stops being a thin client for cloud AI and becomes a personal AI workstation. For developers, founders, analysts, designers, and finance teams, that could change the entire workflow. The PC used to be a screen with a keyboard. Now it is becoming the place where your AI actually lives.