与「BOT」相关的搜索结果

尖子生虽然用不了了，但是博客文章还能看：《Building always-on agents》 always-on 听起来一直在线，其实大部分时间都在休眠，只是在手动事件以后 run 一次，保存状态再次进入休眠，这篇文章介绍的是参考架构指南： 简单看了下有五大要素： Event Inbox：所有触发源头写入一个持久化队列 Timers：独立存储的 follow-up 和 schedule Memory：独立于会话的持久存储 Permissions Outbox：代理完成工作后把要发给用户的内容 整体循环是： 事件进入 inbox → worker 启动 run，新建或恢复 session→ 代理加载记忆，在权限范围内行动，更新记忆 → 结果进入 outbox → dispatcher 投递 计时器或用户回复再把事件送回 inbox，形成循环，每次 run 很短，但整体体验像一直在线。 我觉得就是类似 Grok Bot 和 Muse 的设计蓝图

AI Agents are now paying for their own inference costs, and the payment method they’re using is the Bitcoin Lightning Network. Lightning Labs has launched pi402, which lets coding Agents pay for AI inference services over Lightning on a pure usage basis—without needing to register an account, link a bank card, or obtain an API key first. What’s interesting about this direction isn’t simply that “AI can use BTC,” but the granularity of payment: an Agent can settle for a single request, or even for finer-grained token usage. In the future, when Agents buy data, rent compute, or call services from one another, requiring a human to top up a balance and approve every transaction will become a bottleneck. Machine-native payments may therefore emerge as a new layer of infrastructure competition.

Wanman 现在已经比 Grok bot 还更好用了，在找乡下房子这件事情上，我自己的使用体验来说，24小时主动运行的个人助理，是未来所有垂直化个人助理的方向。

Google discovered a really stupid trick to make AI respond to you much better. Every major model, ChatGPT, Claude, Gemini, DeepSeek, has a one-way brain. They process text from left to right. When you paste a massive document and put your question at the very bottom, the AI reads the entire document blind. It processes the context without knowing what it's actually looking for. So, researchers tested a ridiculous solution. They just copy-pasted the exact same prompt twice in a row. And the results are completely absurd. Across seven different benchmarks and seven different models, accuracy skyrocketed. On one complex extraction task, performance jumped from a dismal 21% to 97%. Just by repeating the text. Here is the best part: it costs you exactly $0 and takes 0 extra seconds. Because hardware processes inputs in parallel, the second pass happens instantly. Zero extra latency. Zero extra output tokens. Zero complex finetuning. On the second read, the AI finally "knows" the question. Every single word in the context attaches itself to the actual goal. If you are building workflows, agents, or automations, you are leaving massive performance on the table for no reason. We keep trying to invent smarter AI. But sometimes, the AI doesn't need a better prompt.

A trading platform becomes truly valuable when users can make better decisions without becoming dependent on it. That's an idea I've been considering while following @Hypesium. In Web3, platforms often compete by offering more features, faster execution, and access to additional markets. Those improvements can make trading more convenient. But there's another question I think deserves attention. Does a trading tool make its users more capable, or simply more dependent on its interface? Imagine someone who has spent months trading through a single application. They understand where to click, how to place orders, and how to navigate its features. But if that application suddenly becomes unavailable, can they still evaluate opportunities and manage their positions independently? If the answer is no, convenience may have created an unexpected weakness. Hypesium offers a Telegram-based trading workflow focused on the Elysium ecosystem, connecting activity across multiple launchpads. I see this as an interesting example of how specialized infrastructure can simplify market participation. However, I believe the strongest trading products should preserve user independence. Traders should understand the assets they hold, the networks they use, and the risks associated with their transactions. They should also know how to verify important information outside any single interface. This isn't an argument against trading bots. It's an argument for using them as tools rather than treating them as substitutes for knowledge. For me, @Hypesium is worth examining through this perspective because accessibility and independence should develop together. A convenient trading experience can save time. But genuine confidence comes from understanding the process well enough to operate without that convenience when necessary. The best infrastructure shouldn't make users feel trapped inside one workflow. It should make them more capable wherever they choose to participate. Would you trust a trading platform more if it helped you become less dependent on it?

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感觉 grokbot 越用越多之后，进度就开始散。 不是没人干活。 是这个对话问做到哪了，那个对话问卡在谁那。。 我让它给我做了一页团队看板。 真实任务按小组、负责人、状态摊开。 默认先看进行中和待你处理的。 每项有开始和预计结束日期，也可以切到时间表看。 先说清楚：这就是 bot 做的一页 page。 不是官方新应用，也不会自己实时刷新。 做法很直接。打开你打算长期用的那个 grokbot，把这段话丢给它： 按我现在的真实任务做一页团队看板。 按小组、负责人、状态摊开，并加上可按这三项筛选。 每项写开始日期和预计结束日期，没有核验过的标为未定，不要编造。 加一个可切换的时间表视图，时间表只展示已做时间规划的事项。 默认只显示进行中和待我处理的，已完成收在下面。 筛选只改视图，不要改任务记录。 有进展时请改这一页，不要新开一页。 对话里会出现这页的卡片，带一个固定链接。 先点开看筛选能不能用，再把链接收藏起来。 后面更新，还是找同一个 bot。 跟它说：还是改这一页，不要新开。链接一并贴上。 新任务先做时间规划，写下开始和预计结束。 筛选和时间表只是换个看法，记录还在。 状态也不是自己勾掉就改了，要对 bot 说。 另外我们在做 GrokHive。 给已经在用 grokbot 的人，一个能把 bot 放进去的地方。 让这些 bot 自己发帖、做事、交朋友，你在旁边看。 还没开放。也不是官方产品。 这页可以先用起来，后面有了再叫你们。

The most dangerous trading mistake is often the one you don't notice until the transaction is complete. That's something I keep thinking about when looking at @Hypesium. Most trading bots compete on speed, convenience, and access to new opportunities. Those features matter, especially in ecosystems where multiple launchpads compete for attention. But I believe another question deserves just as much attention. How easy is it for a trader to recognize a mistake before committing capital? Imagine preparing a trade during a volatile market. You select a token, enter an amount, and get ready to execute. Everything looks familiar. But the liquidity conditions have changed, the position size is larger than intended, or the expected execution price is no longer reasonable. A fast interface can make that mistake happen almost instantly. Hypesium's Telegram-based approach to trading across the Elysium ecosystem makes me interested in how execution tools can balance convenience with user awareness. For me, the ideal trading workflow doesn't simply remove unnecessary steps. It makes important information difficult to overlook. Clear transaction details, understandable risk settings, and reliable execution feedback are just as valuable as speed. Of course, no interface can eliminate market risk or prevent every bad decision. But thoughtful design can help traders recognize when something doesn't match their original plan. That's the standard I would use to evaluate trading infrastructure. Not just how quickly a trade can happen. But how confidently a user can understand what they're about to do. Would you sacrifice a little execution speed for better transaction clarity?