与「aerti」相关的搜索结果

“𝘛𝘩𝘦𝘺 𝘴𝘦𝘦𝘮 𝘵𝘰 𝘣𝘦 𝘷𝘦𝘳𝘺 𝘨𝘰𝘰𝘥𝘴 𝘧𝘳𝘪𝘦𝘯𝘥𝘴...” Have you considered Tifa and Aerith as girlfriends? 👀✨ Well, me and my flower girl @alcololic did! 🌸 Do you like our take? #cosplay# #FF7R# #TifaLockhart# #AerithGainsborough# #aerti#

Grok 4.6 wins again. 👑 Grok 4.6 takes the #1# spot on GPQA Diamond with a score of 94.9%, beating GPT-5.6, Gemini 3.1 Pro, Claude Opus 5, and every other model tested by Artificial Analysis.

DeepSeek V4 Pro 的 0831 版本不太对劲，他们是不是又把模型给撤了？ 现在的情况非常奇怪： API 确实是有的，在 API 的模型和价格这部分写的是 0813，但是更新日志页面完全没有提到 0813 的更新。 官网上面原本关于“DeepSeek V4 Pro 更新正式版”的横幅也被撤掉了。 模型的文档里写的是 0813，更新日志里却没有。 因为我们没办法直接知道他们到底更没更新，只能通过官方公告来确认，但他们现在既没有发正式的公众号文章，也没有发布任何公告。 Artificial Analysis 测出来的得分也很怪，V4 Pro 正式版只比 V4 Flash 高了一分，两者的得分几乎是一样的。 他们现在什么也不说，测出来的得分又不对。这不让昨天熬夜测试的人都成小丑了吗？我去

I used Grok 4.6 to build a 2D agent simulation of The Office. Here are notes and observations on 4.6: It is a huge step up from 4.5 - both in the quality of visual outputs and in the breadth of work: personality, features, and finding usable assets for this project. The editorial content and writing were good - I like the "feel" of this model. One of the biggest wins for 4.6 is speed. The throughput (~80 tok/s) and latency are so good that it feels Composer-adjacent - something @ericzakariasson called out in his writeup. That speed + cost + performance makes for a true "workhorse" model that's practical for both personal and work use. My goal was to simulate The Office through "agents" that behaved like the characters - including all of the neuroticism and idiosyncrasies that made the show so funny. I knew what I wanted artistically - I've built similar 2D apps with pixel art. I asked Grok 4.6 to research psychological modeling, pull character descriptions, find references for the cast, and assemble 2D sprites with the Universal LPC sprite sheet generator and some RPG tilesets I grabbed online. I rattled a brief into the @cursor_ai mobile app late one night at the Cursor office and woke up to an MVP. Then I spent a day or so spamming cloud agents until the simulation worked how I liked. The cool part is that Grok did the simulation, art, and research on its own: - Every couple of minutes, each person scores a few possible actions and picks one. They pathfind around desks, work, grab coffee, talk at the cooler, hide in the annex, or end up in a meeting. - Click someone and you can inspect traits, needs, mood, relationships, and whatever they're doing right now. You can also speed time up, force Michael to call a meeting, or roll a random office event. - Each character has Big Five scores that bias what they tend to do. Needs like work, social, caffeine, status, and comfort rise over time and fall when they do something about them. - Grok reconstructed the layout from Dunderpedia (Office Wiki) and online sources - Michael's office and the conference room on the north glass, Pam at reception, sales and accounting in the bullpen, the annex to the east, restrooms and the warehouse down the stairs. - Grok helped me find a few sprite sheet packs to implement. I was surprised at how accurate some of the character sprites were - from hair color to clothing. The combination of a performant model, cloud workspaces, and high throughput made for a really fun devex - the amazing folks at @cursor_ai and @SpaceXAI make my job easier everyday. A huge shout-out to @_Brian_Zhang, whose Notion hackathon project inspired this exploration.