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agent 接入我的交易系统以后就是一个巨大的 quant training program, 我从前赚的大部分钱都是高度 delta-netural 的——靠对接流动性的速度赚钱，不需要靠数学赚钱。（正如我说，我们这个领域的流动性是十分低效的） 但其实这世界没那么多完美配对，这一年 agent 向我的系统注入了很多以前我根本没注意到的的 “波动定价” 和 “投注风控” 能力的钱（对于低效的市场依然黄金遍地，因为人迹罕至而价差普遍，所以对于模型的精度要求没那么高）。 当然可能也是因为当年精力有限，没有像现在这种几十上百个 agent 一起干那么游刃有余。 关于投注控制和 ev 实现（主要是凯利公式），由于我很多年来比较了解 poker，我现在最喜欢的一个系统 ev 纠正模块是一个类似 poker tracker 的时间轴 playback 模块，看某段时间内模型自以为的 ev 曲线是否在 pnl 曲线的下方，看定价是保守了还是激进了还是完全错误了。 一旦位于 pnl 曲线上方，对我来说是红色信号，我就会疯狂开始研究到底模型差在哪里。直到板正为止——这个过程结束就像 solve 了一个数学题一样让人着迷。 而且由于过去的职业习惯和构建软件系统的优势，我其实是有充分的市场参与的广度和速度，因此也能拿到充分的 “真实成交信号样本以及执行损耗样本” 来验证模型离真实世界的距离，反过来作用于定价精度。 ——这种结对编码的体验是非常好的。因为你能感觉到你对市场理解是的显著增加的，收益面和手上能掌握的工具箱也是在成倍增加的。 这在 agent 之前你是需要大量的金融和工业场景训练的，没有一个职业的交易团队的熏陶几乎是不可能的。 所以我其实很羡慕当代年轻的工程师们，随着 crypto 和 AI 的持续演进，很多过去极高的市场准入门槛其实是在降低的，这不意味着赚钱变难，反而会是对勤奋者的奖励——因为后面十年绝大多数人还在以传统方式参与市场，或者根本不会成为参与者。

Substantial upgrades just landed in Afaq — Civilizational Atlas 🌍 The timeline now reaches deep into the ancient world: the unification of Egypt, the Great Pyramid, Sargon's first empire, the migration of Prophet Ibrahim عليه السلام. Every one of 200+ civilizations now leaves its mark on the timeline — blue for its founding, purple for its fall — so you can watch 5,500 years of rise and collapse in one sweep. The maps are sharper, the playback smoother, and the whole atlas still tells history through the Islamic civilizational lens it was built around. See where the horizons take you →

Map the content path to clarify your streaming architecture. → Ingest & preparation: Content entry and processing → Storage & availability: Consistent access on demand → Delivery & playback: Player performance AIOZ Stream connects these stages into one media workflow.

Agencies charge $2,000/mo for AI ad creative. Higgsfield + draft mode discipline = $29. The full 32-minute build, chaptered: 0:00 — Intro: the sister-trap premise and the storm-at-sea kill 4:28 — Stage 1: the script Claude actually writes for you 5:24 — Stage 2: the asset factory inside Cinema Studio 10:36 — The naming trick that saves 400 wasted generations 11:25 — Stage 3: the pirate cabin, shot by shot 14:01 — The talking parrot fix that made the scene alive 15:41 — Directing a cannonball through a sea battle 18:01 — The ship blast that transitions into the desert 18:46 — Full pirate scene playback: wet-deck fall into the ocean transition 19:45 — Desert scene: ostrich riders and dust transitions 30:00 — Full jungle sequence playback 31:30 — The twist ending that reframes the whole film The frame this post opens with (agencies at $2,000/mo for AI ad creative, a $29 stack on the other side) is the pitch. What Adil actually shows is one operator building a 32-minute cinematic short across three settings, solo, in Krea Cinema Studio with Claude writing every prompt. The whole build is on screen, timestamp by timestamp. The turn comes at 10:36. He names every asset, tags them the same in Krea Cinema Studio and Claude, and the scene generator auto-matches inputs by those tags. That's why the pirate captain keeps the same face 20 minutes later. Skip this step and you burn 400 generations wondering why the model keeps drifting. At 17:19 he stops typing and draws. He sketches where the cannonball lands and where the crew stands, then feeds the picture to Claude. One drawing beats ten sentences. Every failed batch you avoid is credits back in your pocket. The whole thing runs on draft-first discipline. Batch cheap in low-res, iterate the prompt in Claude, commit to 4K once. That's how one person out-produces the retainer. He did it alone. In Krea. With Claude.

AIOZ Stream brings efficient chunking to adaptive streaming on AIOZ DePIN. What this supports: → Optimized video chunking → M3U8 playlists for dynamic quality selection → Buffering and preloading for smoother playback Built for playback stability and streaming quality.

Struggling with choppy playback or high bandwidth costs for global sports live streams? Our Intelligent End-Side Playback Optimization: · Adaptive bitrate tech for complex network · 8K/144FPS real-time HD transcoding · Save 50%+ bitrate · Top Speed Codec for superior viewing

AIOZ Stream, built on AIOZ DePIN, powers video conversion for scalable streaming. → Video conversion across codecs, resolutions, and bitrates → Adaptive streaming profiles for smoother playback → Transcoding for broader playback compatibility Built for playback quality.

Say hello to Zoom Slides! 🎉 From a meeting, a rough idea, or a few notes AI generates a polished deck, ready to present. ✨ ✅ Generate slides from meetings, docs, or prompts ✅ Co-edit live during meetings ✅ Voice-powered playback, even async ✅ Compatible with PowerPoint & Google Slides And there's a lot more explore everything at 👉 @Zoom is here 🔊 #sales# #marketing# #leadership#

xAI has been shipping Grok Build updates non-stop If you have not been keeping track, here is what xAI has rolled out up to v0.2.11: New commands & core features → Integrated 𝕏 search and much faster web search → Added /export, /login, /usage, and /config-agents → Added an interactive read-file viewer with PowerPoint text extraction → Added Always-approve mode to streamline permissions → Auto-installed shell completions for bash, zsh, and fish Expanded platform support → Added Windows ARM64 and macOS x86_64 support → Improved terminal support across Warp, VTE-based terminals, JetBrains, and legacy Windows Console → Fixed copy/paste issues across Linux Wayland, WSL, and Windows Agent & context improvements → Subagents now share the terminal backend, scheduler, and monitor across sessions → Added proactive system reminders and laziness detectors to keep the model on task → Improved context compaction and memory usage for chat history → Auto-backgrounds long-running bash-mode commands triggered via ! UX, media & UI upgrades → Boosted terminal video playback to 30fps → Added multi-image paste, drag-and-drop, and temporary macOS screenshots → Added instant loading indicators when switching models → Improved clickable markdown links and rendered links inside table cells → Smoother plan-mode controls and absolute line numbers in the edit panel Stability & fixes → Increased default retry budget to ~5 minutes → Increased Unix ulimits to prevent crashes → Hardened background tools to handle timeouts and self-kills → Fixed rendering bugs across UTF-8 output, large monitors, Windows contrast, and more xAI is moving insanely fast Grok Build is going from early CLI to a serious agentic coding environment very quickly