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从太子集团的陈志到硬件钱包Coldcard，全部都因为随机数导致私钥被破解，那随机数和私钥有什么关系？为什么他们的随机数会出问题？ 首先比特币私钥本身就是一个256位的随机数，而这也是比特币最安全的核心保障，因为这个数字的组合总共有10的77次方，远远大于地球上沙子的数量，大约等于整个可观测宇宙中的原子总数，这种天文数字即使动用地球上所有的计算资源都不可能暴力穷举出来。 那既然规模如此之大，陈志和Coldcard又是怎么被盗的？ 核心就是在于，私钥安全的前提是因为它是个随机数，而如果你的私钥生成的过程根本不随机，那根本用不到什么量子计算机，随便一台电脑跑几个小时就能把你的私钥算出来。 随机数分为两种，伪随机数和真随机数，简单来说凡是通过一定的数学公式使用代码生成的都是伪随机数，而通过物理现象产生的随机数才是真随机数。 比如你使用Python的random()函数生成一个随机数是214，你以为真的是电脑给你随机选了一个数字，实际上这个数字是通过一个数学公式生成出来的，比如下一个数字=当前数字*7+3-5，那么你只要知道计算的公式就可以穷举出来这个公式能生成出的所有结果。 这时候问题来了，你会奇怪那为什么计算机不真的给我一个随机数呢？因为对于软件来说，任何结果都不可能平白无故的直接产生，你得有输入信息，并且配合程序运算，才可以有输出结果。 所以真正的随机来自于不需要软件和数学公式的物理世界，比如你投出的一个骰子，或者下一个雨滴掉落的位置。 所以对于私钥来说，想产生安全的随机数，只有软件不够，必须要配合硬件，比如提取CPU的电子噪音来作为完全无法被预测的输入信息，现在成熟的手机和电脑本身已经提供了硬件层面的安全随机接口可以调用，所以你用OKX、币安和Metamask生成的钱包都大概率使用了硬件噪音产生真随机数，主流硬件钱包自己本身也会读取硬件数据获得随机数。 陈志的钱包被盗是因为雇的程序员水平太差，直接用了最初级的随机数代码，估计是从哪个野鸡学校绑过去了一个刚毕业的大学生，抽了几鞭子就开始干活了。 Coldcard本身其实已经使用了硬件层面的随机数，但因为一个版本出现漏洞导致没有调用到硬件信息，而是采用了纯软件生成。 所以现在的问题是，你的钱包生成随机数的过程，到底随机不随机，完全是个黑盒，你压根不知道。 最有效安全的方式，就是你自己拿个骰子扔100次，记录下来每次的数字，然后把它转换成256位的二进制编码，再使用BIP39算法转换成24个英文单词，也就是你的助记词。

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!

扎克伯格又掀桌子！ 他们发了一个新的模型 Muse Spark 1.2 和 Muse Code 编程 Agent。 这玩意价钱便宜得相当于白送，前提是你同意他们的数据收集要求。 当然，你要想用 Meta 的模型，比用 Anthropic 的模型都麻烦。 我根本无法访问它，它直接不让你访问它的网站，别说能不能登录了。 简单来说，你只要允许它用你的数据进行模型训练，相当于给了你 12 倍的折扣，价格跟DeepSeek-Flash 差不多。 在 DeepSeek 即将涨价的时候，小扎跟上了，AI 圈价格战开始了。

🚨 BREAKING: Apple filed for a PRELIMINARY INJUNCTION against OpenAI AND asked a federal judge to put them under forensic supervision "Apple respectfully moves the Court for a preliminary injunction to stop THE THEFT OF ITS TRADE SECRETS" Apple filed NINE sworn declarations, a 28-page memorandum and a concurrent motion for expedited discovery What Apple now says, under oath: Chang Liu: 8 years at Apple, now OpenAI "Member of Technical Staff" exploited an authentication bug to steal Apple trade secrets "on AT LEAST FIVE SEPARATE OCCASIONS" from February to April 2026, WHILE working for OpenAI Liu downloaded "THOUSANDS OF PAGES of Apple's most sensitive trade secrets" The stolen files, NAMED: >DisplayNotes.key — "several hundred pages" on Apple's custom display power development program >Architecture analyses. Fabrication decisions. Testing results >Engineering data for an UNANNOUNCED Apple product: 'touch, display, and power systems" >Final.key + V2.key — compilations of two undisclosed Apple R&D projects >and those are "only four of the dozens of proprietary documents Mr. Liu stole" Liu fed OpenAI "a steady stream of Apple proprietary information that he actively concealed" Liu also "coached Yu-Ting "Alyssa" Peng, then still INSIDE Apple, how to access and copy files from Apple workstations "to avoid trouble with the security team" and directed her to communicate with him on the encrypted LINE app "to avoid detection" Tang Yew Tan: 24-year Apple VP, now OpenAI's Chief Hardware Officer, "used an Apple internal project codename for an unannounced product to elicit still more trade secrets from job candidates." Tan's own messages, quoted in the motion: >"Just like last time, bring some parts you worked on" >"mlb, battery, shields type of stuff is interesting" OpenAI recruiter, quoted: "No, you won't sign anything at the exit interview. If they do ask you to sign anything, let me know asap." APPLE TOLD FEDERAL JUDGE: >"OpenAI knows its misappropriation is wrong and has tried to conceal it." >"This is not a case of 'mere hiring'... it is a case of repeated instances of deliberate theft." Apple says OpenAI went after its SUPPLIERS: >OpenAI "directed a trusted Apple partner [name redacted] to perform [Apple's proprietary metal finishing] process for them, knowing it was proprietary to Apple... because they were involved in this partnership while at Apple." Apple put its own Surface Finishing Manager, Jackie Hughes, under oath to prove it. Apple named ELEVEN MORE former Apple employees at OpenAI — beyond Liu, Tan, and Peng — Fourteen people total. Apple also filed a concurrent motion for EXPEDITED DISCOVERY demanding depositions: - Liu. Tan. Peng. - A fourth unnamed OpenAI employee - Plus OpenAI itself, under oath, through Rule 30(b)(6) Apple has asked a federal judge to put OpenAI under forensic supervision RIGHT NOW: >Forensic inspection of ALL OpenAI devices >ALL cloud storage, Slack, email >Including anything that "previously contained" Apple data — deleted included Demanding the "first available hearing date," citing "imminent threat" to its trade secrets. APPLE: > "The harm is happening now — every day that passes without an injunction allows OpenAI to embed their knowledge of Apple's stolen information into its hardware development efforts." Hearing: October 1, 2026. Judge Edward J. Davila. ITS HAPPENING

用几秒钟复制任何人的声音，然后直接卖钱。 Meta 开源了 Voicebox，一个本地音声 AI。 录音 → 几秒生成 → 配音销售。YouTube 量产、广告配音、教材贩售都能加速。ASMR、同人语音也都能整。 开源地址：