与「mac」相关的搜索结果

坦白一下，我玩交易一直是赌徒模式😅 无聊时候玩一下，每次只扔 100U，动不动就开 20 倍、50 倍，我只要没亏完就不收手，赚了才卖。 还真是从 200U 到了 800U🤣，玩法倒是摸熟了。 但说实话，全是运气。 所以我打算从头认真学一遍，K 线、指标、仓位、止损，股票也一起学，看 K 线这套东西，股票和币其实差不多。 让 AI 当教练，配着 OKX 的工具学： 1、先复盘我自己 用只读 Key 把 OKX 的 Agent Trade Kit 接进 Claude，让它拉我过去的成交记录和历史仓位。 提示词："你是我的交易教练，看完我最近 30 天的成交记录，找出我最容易亏钱的三个习惯，不要给我任何买卖建议。" 2、在真实 K 线上学指标 Agent Trade Kit 的行情模块不用登录就能用，70 多种指标，均线、RSI、MACD、布林带、ATR 都有。 每天挑一个币，让 AI 对着当天的 K 线讲：这个指标现在在说什么，什么时候它会涨会跌。 3、用模拟盘按规则练 开仓前先写好止损、单笔最多亏多少、杠杆上限，多在 OKX 模拟盘里按这套规则跑，每天让 AI 对照规则复盘。 4、看网格参数是怎么来的 OKX 网格页里的 AI 策略小助手，会按回测给激进、均衡、稳健三套参数，对比着看，能很直观地看到波动和仓位是怎么影响收益的。 学会了这一套，换到股票上也是一样的 K 线和指标。 等我先学出点东西，再来跟大家分享怎么交易，现在我还不配，hhh

Ftx大陆用户kyc 不给提现，现在大家可以9折出售，我试了，速度很快，一天到账，操作很简单。 昨天的删了，很多人担心有kyc泄漏风险，这个网站是 @LouisOrigny 做的，kyc 验证是@sumsub 做的，大家自己评估风险吧，都是X上可以验证的，我觉得这个9折出售还是能帮助一些人。 操作步骤 1.确认邮件，大家都是 这个网站 2.领取确认，就是登陆ftx 网站，截个带名字的截图提交，还有一个赔偿ID号，在ftx账号右上角有，或者按照他那个视频，搜一下过往邮箱。 3.KYC用身份证或者护照都可以，注意要用手机人脸，mac 操作不成功 4.然后邮签一个文件，都是傻瓜式操作 5.确认test 金额，然后就收到款了，全部操作一天搞定 链接

I dramatically underestimated the value of Grok Bot in my Tesla. Can you technically do everything you’re able to do with Grok Bot in the Tesla just by launching the app on your phone and going voice mode? Sure. But the magic isn’t in the raw capability itself, it’s in the combination of raw capability and total seamlessness. I often have fleeting thoughts while driving around. Some of these things aren’t significant enough to make me fumble around with my phone while supervising FSD, but when I literally don’t have to lift a finger and can just “Hey Grok” anything computer related into reality, I find myself taking advantage daily. And the little things add up. I’m on my way to work and remembered that I have a few documents on my home computer that I am going to need for work. So I just asked “Hey Grok, can you grab those 4 pdf files from my Mac downloads folder and move them into X folder on my one drive?” Now they’ll be where I need them to be when I get to my desk, and I won’t have to re-download them on my work machine. I have to work on a presentation today for a talk in a few weeks. “Hey grok, go into my sales enablement folder and have Claude Code build me a deck focused on X product for Y industry.” Claude already has my full job context, styling preferences etc and can build a nearly finished deck with a prompt. Now when I get to my desk, instead of building from scratch, I can review and prompt revisions before beginning to dig through my email backlog. Feels insane.

朋友们 回来了 ​ ​32G + 1t ​ ​除了贵没什么其他特别之处，我买的是翻新的版本 上一台翻新 MacBook Pro 还是 2021 年买的，买了后做了个外包挣了 6 万人民币，​现在送给我老婆用，她每天的工作就是聊聊微信，改下PPT，可以用很久 这一台计划用五年，真正让我感到兴奋了还是七八万Mac Studio Ultra啊 可惜太贵了

🚨 Apple has released an important security update for iOS/iPadOS 26.7.1, addressing CVE-2026-86950, an out-of-bounds write vulnerability that may lead to arbitrary code execution. As we previously reported, this update is highly relevant to the iOS attack activity we have been tracking. Apple confirmed that the vulnerability may have been exploited in highly sophisticated attacks targeting specific individuals on iOS versions before iOS 27. For crypto users, this is especially concerning given the iOS exploitation activity we have observed targeting sensitive wallet data. 🔐 Please: • Update your iPhone, iPad, Mac and other Apple devices to the latest available security updates. • Avoid installing apps from unknown or untrusted sources. • Do not open suspicious links in Safari or in-app browsers. • Treat unexpected files, links and app installation prompts with caution. Stay alert and keep your devices updated. Apple Security Update:

第 3 步️⃣：藏在暗处 🥷 为了不被发现，他们克隆已连接设备之一的 MAC 地址。再做 IP 欺骗，把路由器搞晕，让一切看起来都像正常流量。 更狠的会进路由器后台删日志，一点痕迹都不留。🗑️

我觉得目前 macOS 的多媒体播放器都太难用了。不仅性能差，功能迭代也很慢。 所以我最近两个月一直在开发多媒体播放器 Khua Player，专为现代 macOS 和 Apple 芯片打造。 为了追求极限性能，用 C/C++ 等原生代码优化播放核心，尽可能压低体积、内存和 CPU/GPU 开销，打开快、操作跟手、播放丝滑。 也用上了 macOS 的原生 AI 能力：本地生成字幕、翻译字幕，再加上实时补帧、4K/HDR、Finder 预览 MKV 格式等。损坏或没下载完的视频，也能尽量救回来播放。 已完全开源，网址：

今天晚上 10 点，我的 Claude 老号毫无征兆被封了。 用了大半年，一直为了这个账号小心翼翼供着原生家宽 IP。 并且这个账号过kyc后买来一路从免费版升级： $20 尝鲜 $100 重度主力使用了好几个月 最后开到顶配 $200 结果 $200 还没 $100 用得久，用了不满两个月直接阵亡。 我第一反应先是骂A ÷玄学风控、同时怀疑自己节点是否被标记不干净。 但静下心拉了 Clash 的连接日志，把 Mac 上的路由表、DNS 和后台进程彻底摸了一遍，我服了。 面对AI风控,现在大部分教程都在疯狂教你折腾“纯净住宅 IP”。 其实真正害死账号的，往往是本地网络环境的“精神分裂”。 这里我实践排查出来的 3 个致命硬伤： 1.Claude Code 压根不支持 SOCKS很多人随手配个 socks5 变量，但官方文档写得清清楚楚：只认 HTTP_PROXY 和 HTTPS_PROXY，不支持 SOCKS。配错了对应出口后它根本不认，流量直接裸奔或异常打架。 2.IPv4 和 IPv6 严重割裂IPv4 规规矩矩走了家宽节点，IPv6 却在本地直连或者经由不同的虚拟网卡分流。在服务端眼里，你相当于上一秒在美国，下一秒直接瞬移。 3.终端、桌面端、浏览器出口完全不一致CLI 终端走一套环境变量，桌面端走 TUN，浏览器还带着残留的动态端口后台重启。同一个账号，几个客户端同时挂着完全不同的出口在调用。 所以说原生家宽固然重要。 但本地网络没有对齐，IP 买再贵也是白送。 所以如果你也是AI重度用户，给几个我自己实践用过的排查建议： 明确禁用或阻断 IPv6，确保没有双栈绕过 给 Claude Code 显式配置 HTTP 代理，别依赖 SOCKS 统一所有客户端走同一条出口路径，排查并干掉后台偷跑的僵尸进程(claude codex都要监控) --- 最后祝大家的账号都安好,能够安心使用AI🫰

You can now run Laya Decision models locally on just 4GB RAM! 🔥 Works on CPU, Mac, Windows, Linux and GPU setups. Serve Laya through a Jev-compatible API via Unsloth Desktop. GitHub: Guide:

Higgsfield is the most untold story in tech. $1BN in ARR in 18 months. Faster than everyone other than OpenAI and Anthropic. They spend $4M a month on models. They expect this to be $100K per person per month. They have 150 people working in a content machine. They will breed more millionaires than any other company in Kazakh history. For the first time, @alexmashrabov on the journey to $1BN in ARR. (below) 1. The Power of the Immigrant Founder Coming from Uzbekistan, Alex was pushed into competitive programming at age eight as his single path to reach the United States. For international founders, placing top in global competitions serves as the ultimate social elevator, instilling the relentless work ethic required to build breakout companies. 2. My Biggest Lessons in the Journey to Finding Product-Market Fit @higgsfield burned over $10 million of its $16 million seed round chasing hype and narrative rather than product quality. With under $5 million left, the team pivoted to product-led growth, solving camera control for creative directors, which immediately triggered organic hypergrowth without paid ads. 3. The 150-Person Content Team Powering Higgsfield's Billion in ARR Nearly half of Higgsfield's workforce consists of 150 in-house creative professionals producing tutorials, ads, and cinematic projects. Generating 90 minutes of TV-quality AI video requires 100 hours of raw output, proving human taste and curation remain the primary drivers of distribution. 4. We Spend $4 Million per Month on Models Higgsfield spends $4 million monthly on internal model usage, averaging $10,000 per employee so teams can freely vibe code and test workflows. Uncapped inference compute acts as a force multiplier, allowing top talent to discover breakthroughs at maximum velocity. 5. Why Chasing Benchmarks Is Bullshit and the Corporate Misalignment Occurring Public benchmarks have devolved into corporate psyops where lab researchers overfit test data to secure bonuses before job-hopping. Text-to-video benchmarks ignore real production workflows requiring 3,000-word prompts, proving direct customer iteration beats artificial leaderboards. 6. Why Team Sizes Won't Be Impacted as Much as People Think While AI handles over 60% of basic support requests, complex B2B environments cannot eliminate human teams. High product velocity constantly shifts rules and context, requiring smart, coordinated operators across legal and customer success. 7. Americans Are Way More Promiscuous When It Comes to Leaving Companies Silicon Valley workers routinely jump jobs every two years, prioritizing short-term trends over deep commitment. This transactional market gives international hubs an advantage, where cultural loyalty and team stability build compounding technical moats. (links in comments)