与「PROM」相关的搜索结果

🎮 Steam accueille bientôt un simulateur de… grattage de testicules 😭 Ball Scratch Simulator est un jeu d'infiltration complètement absurde dont l'objectif est simple : se gratter discrètement les testicules dans des lieux publics sans se faire repérer. Plus les témoins sont nombreux, plus le défi est difficile. Il faut attendre que les gens détournent le regard, choisir le bon moment… et éviter que votre niveau de suspicion n'explose. Le développeur promet six environnements différents, des objets à débloquer, un système de score avec classements mondiaux et même un mode VR, où il faudra reproduire le geste en réalité virtuelle. Le jeu est annoncé pour ce mois-ci sur Steam.

兄弟们刷到一个 GPT-Image2 提示词库，我第一反应是： 这玩意涨 Star 是不是开挂了。 刚开源没几天，GitHub 直接干到 9000 Star。 在 GitHub 上见过不少项目起飞，但这种速度，真不多见。 它其实就干两件事。 但这两件事，刚好把我之前出图最痛苦的部分给拆了。 第一，一套工业级提示词引擎。 不是那种“高清、电影感、细节丰富”硬堆词的 prompt。 是真有结构、有逻辑、能复用的一套系统。 第二，一个一直在更新的模板库。 你今天刚想做某个风格，可能明天里面就多了一套现成模板。 这就很离谱。 以前出图最烦的是什么？ 反复试参数。 反复改词。 反复生成。 然后盯着结果骂一句：怎么还是这鸟样。 用这种现成结构去套，稳定性真的会高很多。 我自己翻了几天，感觉至少把以前浪费在瞎试上的时间，省回来一大截。 更狠的是，后面还跟了一套 GPT images 2 提示词合集。 这批提示词跑出来的图，质感和细节确实有点东西。 光影、材质、构图，全都不是随便糊弄的那种。 很多玩法你自己硬想，真不一定想得到。 整包 3.9GB。 基本都是市面上热度很高的那批，打开就能直接用，不用再到处东拼西凑。 提示词引擎本体在这： 3.9GB 爆款素材包在这： 说白了，做 AI 图的人已经分层了。 一种还在苦哈哈炼丹，试错，熬夜调 prompt。 另一种已经把提示词引擎和模板库当外挂用了。 效率不是差一点。 是别人还在搓木棍，你已经掏电钻了。 很多人看到的是“又一个开源项目”。 我看完只觉得，后面还靠纯手搓 prompt 出图的人，真的要被卷麻了。

我靠？？？ 我真的以为这是哪个韩剧的切片来着... 拆解了这个几万人关注的seedance 2.5 demo @doctorwasif 真实感太TM强了！！！！ 表达方式竟然是自然语言！ 虽然prompt 很长，但是有结构 有手就会的公式模板 直接copy👇

我靠!!!! 这个视频，我真的以为是哪个朋友圈的vlog @BubbleBrain 拆解了一下这个近200K播放，被1000个人收藏的 seedance 2.5 demo 评价只有一个字 真！prompt 很长，但是有结构，表达方式还是时间戳 公式直接拿走👇

We tried using Meta's new Muse Code agent, but it has a bug that doesn't let it sign in from a docker container. So we did a fun experiment: Meta claims Muse Spark 1.2 was co-trained with their Muse agent harness. So we extracted instructions from their system prompt and added them to the Cline harness. TL;DR of this special prompting: - Trust source code over the user prompt, so read every call site and existing tests before starting the task - Weigh edge and error cases as heavily as the happy path - Always reproduce the bug before fixing - Don't trust the first passing test suite, and verify suspicious looking half-baked tests - Never stop at just editing, keep working until the change is verified complete. We then asked this modified harness to fix a real bug from our repo, and compared the results to the original Cline agent harness. Results: - Used 2.7x fewer tokens (19.7M → 7.2M) - Finished 2x faster (49min → 24min) - Cost 2.4x less ($7.69 → $3.25) Same Muse Spark 1.2 model, same task, only the prompting changed. Incredible how much of a performance gain Meta was able to achieve training it on these special instructions!

The future of AI will be built by you. 🫵 Introducing #BuildWithYou# Chapter One: Finance Prompts Share the finance prompts you use to learn, research, invest, and trade. 20 standout prompts will split a 2,000 USDC prize pool. How to join: 👉 Follow @Binance and repost this 👉 Reply or quote repost with your prompt 👉 Complete the survey → Entries close: 15 Aug 2026, 23:59 UTC. Join us, and let's build the future together. 🫡 P.S. Finally, a good reason to check your ChatGPT history. Disclaimer: This is not an offer or solicitation to trade any financial product. Not available to users in jurisdictions including: US, UK, EEA, Hong Kong, Singapore, and the jurisdictions on Binance's prohibited list (see for details)

Today we are releasing Cloudflare OS, a chatbot with connectors, just like every other tech company is doing. Except actually, it's different. This is a remake of Sandstorm[.]io, my startup from 10 years ago, except this time built on Cloudflare Workers (the platform I've spent the last 9 years building) and deeply leveraging AI. This is more or less the culmination of my secret 10-year master plan. This is a full-on personal app vibe coding platform, in which the sandbox is so secure that you can pretty much go wild -- the AI cannot introduce a significant security bug. We believe a company's security team can feel comfortable giving non-technical users permission to vibe code and then sleep soundly at night. How is that possible? It's the Sandstorm security model, revisited. A "Gadget" is the same thing as a Sandstorm "Grain": a fine-grained app instance. For example, if you have a document editor app, each document runs as a separate instance of the app, in a separate sandbox (one "Gadget"). This means two things, both of which I think are Big Deals: 1. The platform can manage all access control, by controlling who can access the Gadget at all. There is no way the Gadget can accidentally leak itself to an attacker -- even an attacker who has access to other Gadgets based on the same app. 2. Since everyone is running their own copy of the code, everyone can freely *modify* their copy of the code. Think about #2# a bit more. What if, when you wanted a new feature in the software you are using, you could just prompt your agent to add it? This doesn't work in the cloud Software-as-a-Service model, because you are not running your own copy of the app. Sandstorm tried to change that 10 years ago, but the world wasn't ready, because not enough people had the skills or patience to actually modify their software. AI has changed that. Now you just ask the agent -- the same agent that you are using to help you interact with the Gadget can also modify the code of the Gadget. And it is so fun.

mattpocock/skills v1.2 is out! We're now the 19th most-starred repo of all time. 13.5m downloads on skills​.sh. Thanks for your support! Here's what's new: - Docs: the community's biggest ask. Every skill documented, with explanations of the main flows + troubleshooting - Claude Plugin: install via Claude's official marketplace - Codex Support: full Codex support via agents/openai.yaml files Updated Skills: - /grilling now asks you questions in rounds, not one-by-one - /prototype now uses HTML instead of a TUI for building logic prototypes - easier to share and far richer - /writing-for-agents renamed from /writing-great-skills, use it for ANYTHING your agents read (AGENTS.md, system prompts, docs) New Skills: - /wizard: tired of provisioning infra? Get your agent to build you a TUI to walk you through it - /to-questionnaire: hit a grilling question you can't answer? Turn the session into a doc you can walk through on a call with a colleague - /wait-what: no idea what the model said? Refocus it in your domain language and simplify with ASD-STE100 Full changelog + docs below. Video soon!