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The $15K reward pool will be shared according to the table above. Here are a few important points shared by @NucleusCodes about the @Acurast campaign: Up to 5 posts per week will be accepted. AI tools are allowed for editing only. Explaining how Acurast works counts as a bonus task. Earning ACU can also increase your multiplier. Keep these details in mind when creating your content.

建议收藏，用到时照着做。做完你能让 DeepSeek 自己决定“要不要调用你写的函数”，并把结果用人话讲回来。 AI 能查天气、查订单，是它自己去查的吗？DeepSeek 官方一句话拆台：模型本身不执行任何函数 这是 DeepSeek 官方 API 文档里 Tool Calls（工具调用）一页。先说结论： 官方原话是，函数要由你自己提供，模型本身不执行具体函数。它只负责说“我想调这个函数、参数是这些”，真正去跑的是你的代码。 先说清词。 工具调用（Tool Calls），是让模型能用外部工具的功能，比如查天气、查数据库。 函数（function），是你自己写好的一段代码，模型只会“点名”它。 tool_call_id（工具调用编号），是模型每次点名时附带的一个号码，你回传结果时要带上它，模型才知道你在回答哪一次。 strict 模式（严格模式，Beta 测试版），是让模型点名时严格按你定义的格式填参数。 一个真实例子：官方示例问“杭州天气怎么样”，模型返回的是 get_weather 这个函数和参数 location 等于杭州，你的代码去查到“24℃”，再交给模型，模型才说“杭州现在 24 度”。 先把话说全： 官方示例用的是非思考模式，请求里加 extra_body 把 thinking 的 type 设成 disabled。 官方写明：从 DeepSeek-V3.2 开始，思考模式下也能用工具调用，细节看官方 Thinking Mode 一页。 官方写明：Chat Completion 接口不支持在对话中间插入不是模型生成的工具调用，要插的话请改用 Anthropic API 或 Responses API。 strict 模式目前是 Beta，要用测试版地址。 一、先看懂整个流程 官方给的执行流程是四步：用户问杭州天气；模型返回要调用 get_weather，参数是杭州；你的代码真的去调用 get_weather，把结果交给模型；模型用自然语言回答“杭州现在 24 度”。 二、照官方示例做一遍 第一步：去 DeepSeek 开放平台拿一个 API key，电脑装好 Python 和 openai 库。 第二步：创建客户端，base_url 写 DeepSeek 官方接口地址（官方文档第一屏就有），api_key 填你的。 第三步：写 tools 清单。每个工具包含 type 等于 function，再写 name（函数名）、description（描述，告诉模型什么时候用）、parameters（参数）。官方示例的函数叫 get_weather，描述是“获取某地天气，用户须先提供地点”，参数 location 是字符串，并且在 required 里。 第四步：发第一次请求，model 官方示例写 deepseek-flash，把 messages 和 tools 一起传，并加上 thinking 关闭的设置。 第五步：从返回里取 tool_calls 的第一项，先把模型这条消息原样追加进 messages。 第六步：你的代码去执行函数，再追加一条 role 是 tool 的消息，带上刚才的 tool_call_id，content 写结果，官方示例写的是 24℃。 第七步：再发一次请求，这次模型就会用自然语言回答。 三、想要更稳：strict 严格模式 第八步：base_url 改成官方文档里写明的 beta 版接口地址（就是原地址后面加 /beta）。 第九步：每个 function 都加上 strict 等于 true。 第十步：服务器会检查你的 JSON Schema（结构说明），格式不合规或用了不支持的类型，会直接返回错误信息。 官方支持的类型是：object、string、number、integer、boolean、array、enum、anyOf，另外 $ref 和 $def 可以复用和做递归。 四、strict 的硬规矩 对象里所有属性都必须写进 required，并且 additionalProperties 必须设成 false。 字符串可以用 pattern（正则）和 format，官方列出的格式有 email、hostname、ipv4、ipv6、uuid，但不支持 minLength 和 maxLength。 数字支持 const、default、minimum、maximum、exclusiveMinimum、exclusiveMaximum、multipleOf。 数组不支持 minItems 和 maxItems。 五、看到什么算成功 第一次返回的是函数点名，不是答案；第二次返回的才是自然语言答案，内容里有你的函数结果。 六、卡住怎么办 strict 报错：先检查是不是漏写 required 或忘了 additionalProperties 设 false，再检查有没有用到 minLength、maxItems 这类官方不支持的写法。 结论：工具调用不是模型替你干活，而是模型“点名”、你的代码“动手”。想让点名更准，就用 strict。把这条复制链接发给他，下次他说 AI 查不到东西，先让他确认函数是不是自己写了。 你卡在第几步？评论区告诉我。同系列前几篇在我主页。 收藏版：5 步速查 一、tools 里写清函数名、描述、参数 二、第一次请求拿到 tool_calls 三、自己执行函数，回传 role 为 tool 的消息并带 tool_call_id 四、第二次请求拿到自然语言答案 五、想更稳就用 beta 地址加 strict 等于 true 常见坑 3 条 一、以为模型会自己执行函数，其实要你的代码去跑。 二、回传结果忘了带 tool_call_id。 三、strict 里漏了 required 或 additionalProperties 设成 false。 复制即用提示词：我想让模型调用一个叫 你的函数名 的函数，它需要这些参数：写参数。请帮我写出符合 DeepSeek Tool Calls 格式的 tools 清单，每个参数都写 description，并改成 strict 模式需要的写法。 S1哥观点：这篇最狠的地方，是官方把话挑明了：模型不执行函数，只负责点名。很多人以为 AI 在后台自己动手，其实动手的永远是你的代码。 真正的信号是：工具调用的难点不在模型，在你把函数描述写得多清楚。就像派活给新人，说明写得含糊，他再聪明也会点错人。 你现在想让 DeepSeek 调用的是什么，查数据还是发消息？评论区告诉我。 今天送：DeepSeek 工具调用速查卡，评论区第一条直接拿。 参考：DeepSeek 官方 API 文档 Tool Calls（S1哥 整理）

We’ve partnered with Fanatics Studios, the joint venture between @Fanatics and @OBB, for a multiyear collaboration that will bring Fanatics Studios’ creative and event production capabilities to NBA All-Star, including in-arena events, competitions and original content, starting with NBA All-Star 2027 in Phoenix.

‼️ CISA Confirms Active Exploitation of Outlook User Interaction 0-Day Vulnerability Details: The U.S. Cybersecurity and Infrastructure Security Agency has confirmed active exploitation of a Microsoft Outlook zero-day vulnerability, CVE-2026-124194, that can expose user authentication data. According to Microsoft’s security advisory, an attacker can send a specially crafted message file and persuade a victim to open it in Outlook. The application may then connect to an attacker-controlled network location without showing its usual warning about external content. Microsoft released security updates for an actively exploited Outlook network-spoofing flaw (CVSS 6.5) that allows unauthenticated attackers to spoof networks. #CybersecurityNews#

Most models are built to generate text, creative content, or reason step-by-step. But not every task needs a written answer. When a workflow or agent just needs to make a quick call, the Decisions API returns calibrated confidence scores (150–250 ms end-to-end) at $0.10 per 1M input tokens, making it nearly 5x more cost-efficient across the shared benchmark suite than Gemini 3.5 Flash-Lite with the Interactions API.

Gaming is all about excitement, timing, and the thrill of every unexpected moment! 🎮🔥 This video captures the energy of online gaming, from spinning the reels and chasing exciting combinations to celebrating impressive wins. Every round brings a new possibility, keeping the experience entertaining and unpredictable. What makes this kind of content engaging is not just the gameplay itself, but also the live atmosphere, real-time reactions, and interaction with the community. Watching the action unfold makes every moment feel more intense. Platforms like @1win bring together entertainment, gaming experiences, and opportunities to enjoy the excitement of different games. Whether you're watching a streamer or exploring the gameplay yourself, responsible play should always come first. The real fun is enjoying the experience, embracing the unexpected, and knowing when to stop. What do you enjoy most: the gameplay, the big moments, or the excitement of live streaming? #1win# #Gaming# #OnlineGaming# #LiveStreaming#

The Moral Collapse of the Chinese Crypto Community To Elon Musk 2022–2023 marked the golden age of Chinese-language Twitter. Back then, there was no creator revenue you offered purely based on traffic. Two main groups of creators came here to share insights: Influencers who migrated over with their followers after their Weibo accounts were banned. Content creators who were already living overseas. These people came with genuine intent to share, and they often uncovered valuable market alpha. Whether it was Bay Area Spaces, inscription research bloggers, or spot and secondary market analysts. Back then, everyone believed the next bull run would be bright. People expected their altcoin spot holdings would deliver at least 5–10x returns. After all, A16Z poured capital into projects left and right, and every so often, stories popped up of Gen Z traders hitting A8 and retiring financially free. Then the tide turned. High-cap tokens pumped immediately upon launch. Instead of bringing fresh liquidity into the market, the ETF event drained what little liquidity remained, driven largely by Trump-related narratives. The crash on October 11 was almost inevitable. Long before that, many had already lost everything on altcoins. That black-swan event merely liquidated whatever leveraged contract positions were left. Starting around 2024–2025, after X rolled out creator ad revenue, a flood of traffic chasers emerged, catering to lowbrow audiences. These people do not trade crypto, nor do they care about any market narratives. They crossed over to this platform just to scrape together that tiny creator payout, as they have little footing in real life. Consequently, we saw the worst tropes from mainland domestic social media spill over: gender polarization, disinformation, and bootlicking culture. While you tweaked the algorithm to curb plagiarism, the platform still fails to incentivize high-quality content. Plenty of boundaryless content farms still rack up views, and accounts that harass others relentlessly often evade effective reporting penalties. Meanwhile, posts from creators I used to follow have vanished from my timeline. I kindly request that you strictly investigate accounts that distribute other users’ private information without consent.

The Moral Collapse of the Chinese Crypto Community To Elon Musk @elonmusk 2022–2023 marked the golden age of Chinese-language Twitter. Back then, there was no creator revenue you offered purely based on traffic. Two main groups of creators came here to share insights: Influencers who migrated over with their followers after their Weibo accounts were banned. Content creators who were already living overseas. These people came with genuine intent to share, and they often uncovered valuable market alpha. Whether it was Bay Area Spaces, inscription research bloggers, or spot and secondary market analysts. Back then, everyone believed the next bull run would be bright. People expected their altcoin spot holdings would deliver at least 5–10x returns. After all, A16Z poured capital into projects left and right, and every so often, stories popped up of Gen Z traders hitting A8 and retiring financially free. Then the tide turned. High-cap tokens pumped immediately upon launch. Instead of bringing fresh liquidity into the market, the ETF event drained what little liquidity remained, driven largely by Trump-related narratives. The crash on October 11 was almost inevitable. Long before that, many had already lost everything on altcoins. That black-swan event merely liquidated whatever leveraged contract positions were left. Starting around 2024–2025, after X rolled out creator ad revenue, a flood of traffic chasers emerged, catering to lowbrow audiences. These people do not trade crypto, nor do they care about any market narratives. They crossed over to this platform just to scrape together that tiny creator payout, as they have little footing in real life. Consequently, we saw the worst tropes from mainland domestic social media spill over: gender polarization, disinformation, and bootlicking culture. While you tweaked the algorithm to curb plagiarism, the platform still fails to incentivize high-quality content. Plenty of boundaryless content farms still rack up views, and accounts that harass others relentlessly often evade effective reporting penalties. Meanwhile, posts from creators I used to follow have vanished from my timeline. I kindly request that you strictly investigate accounts that distribute other users’ private information without consent.

overheard from friends talking about AI in China, and it’s very alarming - AI short films went massive in China market because of how good the video models are now - the first wave of people who mastered using AI to generate short films and comics made quite some money because they could produce a lot more content than traditional workflows - but within just a few months, everybody and their mom could make equally good short films because all the expertise could be written in a markdown file - when everyone’s more productive, no one actually has an advantage and it’s a race to the bottom. very quickly it became impossible to make money, and everyone’s busier than they were without AI - the only one making money now is companies like bytedance who owns user demand and distribution. they sell ads to creators who pay to get traffic, and eventually ad spend became 80% of those creators’ operating expense, while AI tokens is less than 5% so what are the problems here? 1. there’s no moat if you are creating anything with AI if a human is really good at something, and it’s hard to find more humans who can do the same, they can leverage the scarcity of their skill to get paid very well but if AI is good at something, it will be infinitely replicated, so there’s no scarcity hence you can’t really expect a sustainable business by creating anything with AI 2. more creators created more content people actually liked. that’s a good thing but the economical benefit of that all got absorbed by the distribution platforms there’s a famous chinese poem 遍身罗绮者，不是养蚕人 - it basically says people who dress well aren’t the people making dresses. that’s exactly what’s happening here if our society doesn’t figure out a better way to distribute wealth, AI will help billionaires become trillionaires while average people become more exhausted than ever