How do always-on, proactive agents like @Bot work? Watch my lecture at Stanford CS146S: 2:35 How we got here 6:13 What changed in the models 10:06 Inside an always-on agent 18:07 The harness 27:26 Context engineering 34:26 Where this is going
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no vc's, no insiders, no lockups, no vesting, fully circulating....
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如果你在人工智能领域,你还有时间转回加密货币。
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🔥太疯狂了,现在你甚至可以直播围观一个 535B 大模型是怎么被训练出来的。 斯坦福教授兼 @simile_ai 创始人 @percyliang 刚刚宣布,他们的新模型 Marin 535B-A23B 本周正式开训,而且整个训练过程公开。 Marin 共有 535B 总参数,其中 23B 激活参数。 为此Percy他们一共准备了18.75T tokens的数据,动用了 11 套 GB200 NVL72,约 792 张 GB200显卡。 预计连续训练 3 个月,总训练计算量约 2.7e24 FLOPs。 训完还会继续做 post-training。 请注意,Marin 真的全部开源了整个训练过程。 正式开跑前,他们先训练了一套 4 级 Scaling Ladder,从 1.6B-A61M 一路跑到 27.7B-A1.2B,用小模型提前预测这次 535B 主模型的 loss 和训练状态。 现在主模型正式开跑,所有人都可以直接围观实时训练曲线,后面的数据、实验记录、工程问题也会持续公开。 类似的事情以前有人做过。 2022 年 BigScience 训练 176B 的 BLOOM 时,就公开过训练进度和 TensorBoard。 但 Marin 这次直接把公开训练的规模推到了 535B。 目前来看,这应该是人类公开围观过的最大规模大模型训练之一。 接下来三个月应该会很好看。 模型最后能不能打是一回事,我更想看的是一个 500B+ 模型的MoE到底会怎么训、怎么调,以及中间到底会炸几次。 这种机会太少见了,等于把一场原本只有顶级 AI Lab 内部才能看到、成本可能高达数千万美元的训练实验,直接摊在全世界面前。
🚢 Marin 535B-A23B started training this week! As usual, the whole process is open. Voyage plan: pretraining (80%) + midtraining (20%) on 18.75T tokens on 11 x GB200 NVL72 for ~3 months (2.7e24 FLOPs). Post-training will follow. Before kicking off the run, we trained a 4-rung scaling ladder from 1.6B-A61M (48B tokens) to 27.7B-A1.2B (926B tokens) to debug issues, and to make a forecast of our hero run. This is by far our biggest run, so definitely expecting the unexpected.
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Crazy to think that we will soon have a “memecoin” worth >$500 B Few are prepared for this.
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全球水电账单可以交易的网站?不少人KYC的地址证明就是从这里搞的。 1poa.org 提醒一句:别拿去搞违法的事。
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trading is the greatest mmorpg on the internet, & on-chain is one of the only places you can spin up generational wealth from a very small starting balance pair this with ai accelerating how easy it is for talented developers to build & it's easy to see where this trend is going
[The next retail mania won’t be forex, it’ll be crypto social trading] “Social trading is gonna get a lot more popular.” “You can hit 100x’s and 1000x’s in crypto. You cannot do that in forex.” “The real money comes from being early.” @blknoiz06 compared today’s crypto market to the forex boom during COVID. Back then, people paid for trading groups hoping to find alpha. Forex never offered the kind of upside they were chasing. Crypto is different. The biggest winners catch new narratives before everyone else. That’s why he sees social trading becoming a core part of the next cycle, where finding the right people matters as much as finding the right trade.
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Now the Chinese just need to make cheap RAM to fit it
Kimi K3 is 2.8T params according to their playstore app
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iPhone 用户又多一个省心选择,不用越狱也无需签名安装,就能直接在设备上跑 iOS 应用,这个叫 LiveContainer 的工具完全开源。 以往装个软件要折腾证书、反复签名,它把这些冗余步骤全给绕过去了。未来能不能成为主流不好预测,但这套设计思路确实替使用者想得足够周到。 🔗 github.com/LiveContainer/Liv…
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In a few years, between hardware and algorithmic improvements, this will all look as laughable as governments restricting encryption to 40-bits.
CHINA CONSIDERS RESTRICTING OVERSEAS ACCESS TO CUTTING-EDGE AI MODELS China’s Ministry of Commerce has led meetings over the past month with major AI companies, including Alibaba, ByteDance, and Z.ai, to discuss measures that would restrict overseas access to cutting-edge AI models, including models that have not yet been released. The discussions reportedly include not only closed-source models but also open-weight models. However, the scope of application is still under debate, and the rules may ultimately apply only to future frontier models. Officials have also discussed designating the leakage or theft of proprietary AI technologies as a national security crime, with stronger penalties, as well as restricting the types of foreign capital that can invest in Chinese AI startups. The backdrop is the U.S. move to strengthen export controls on AI models, along with national security concerns over cutting-edge models that could possess advanced cyberattack capabilities. Chinese authorities are reportedly concerned that advanced U.S. cybersecurity AI models could be used to exploit vulnerabilities in Chinese software. Since the beginning of this year, China has continued to tighten measures to prevent AI technology from being transferred overseas. Authorities have investigated whether Chinese AI startups that relocated abroad violated export control laws, while also strengthening oversight of overseas transactions involving Chinese investors, technology, data, and national security concerns. Future regulations could take the form of a tiered framework based on technological capability. Basic open-source AI models may be managed through a filing system, high-performance models may be subject to security reviews, and the most sensitive frontier models may be banned from public release or restricted to use within China.
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Since Bitcoin, a major open problem in distributed systems was whether proof-of-work consensus can be implemented on top of real-world computation rather than useless random hashing. This challenge of PoUW was repeatedly conjectured impossible by researchers and thought leaders. They were wrong.
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苹果把 App Store 锁得死死的—— 换区要重新绑定支付、旧版本下不了、想备份个 IPA 简直是噩梦。 程序员 @Lakr233 忍不了,写了个工具: AssppWeb 不用装 App、不用越狱、不用侧载证书—— 打开浏览器,搞定一切。 它能干嘛: • 跨区搜 App,全球商店随便切 • 多 Apple ID 管理,它自动匹配区域 • 官方 CDN 直下 IPA,签名永久有效 • 历史版本随意挑,1.0 都给你挖出来 • 一键生成安装链接,手机点一下就装完 最硬核的是安全设计: 零信任架构。 你输密码的时候,服务器根本看不到—— 密码在浏览器里用 WebAssembly 加密,服务器只是个"跑腿的",数据包经过它,但它解不开。 相当于:服务器是个聋哑快递员,送的是加了锁的箱子。 要不要用? 自己搭一个 Docker,或者用 Cloudflare Workers 部署 千万别用别人的公共实例,前端代码被改了你就完了。 项目地址:github.com/Lakr233/AssppWeb 一句话总结: 它把 App Store 的控制权还给了你—— 不是破解,是正当地拿回你本该有的权利。
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I can't believe how many people believe Anthropic's propaganda about distillation attacks. You can read how GLM-5 was trained in the paper. Maybe Claude was distilled from Chinese models? I haven't seen a paper from Anthropic, and accusations are often confessions.
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Introducing Claude Fable 5: a Mythos-class model that we’ve made safe for general use. Its capabilities exceed those of any model we’ve ever made generally available.
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Vercel 搞了一个网页终端模拟器 wterm。核心用 Zig 写,编译成大约 12 KB 的 WASM 包,性能跟原生差不太多。 跟一般用 Canvas 画的终端不同,它直接渲染到 DOM 上,所以文本选择、复制粘贴、搜索、屏幕阅读器这些都是浏览器自带的,不用额外折腾。 github.com/vercel-labs/wterm
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