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I am actually disgusted by the timing of this drop. And this will get a bit more technical. Let’s do a real technical teardown of this "1,385-sigma Blackwell weight fingerprint" report that OpenAI and Anthropic are breathlessly promoting today, because banking on nobody reading past the headline is how DC narratives get manufactured. ​First, look at the actual CUDA maths: when PyTorch initialises model weights (torch.nn.init) with a fixed PRNG seed, curand/Philox parallelises random number generation across the GPU’s Streaming Multiprocessors (SMs). Because Hopper has 132 SMs and Blackwell has 148 or 152 SMs, the exact same seed lays out initial weights in a different spatial pattern depending on the GPU’s SM count. In huge MoE models, certain low-gradient null-spaces or unrouted slices preserve faint directional traces of those step-0 weights even after training. ​So yes, brute-forcing the seed and SM grid can show that a model’s step_0 weight initialisation script ran on a 148/152-SM Blackwell GPU. Now read what the summary explicitly admits in the fine print: 1. Initialisation is not full training: The report literally states that these signatures show how the weights were created, and "support (but do not prove) the inference that Blackwell also participated in model training". Initialising a model checkpoint takes seconds on a single rented dev node before loading the safetensors onto a standard Hopper cluster. The "2,000 to 3,000 Blackwell GPUs" and "$500 million" cluster numbers do not come from the weight fingerprint and Depue admits in his own thread that he simply "estimated" cluster sizes from release schedules and model details. ​2. Zero geolocation and zero proof of smuggling: The final sentence of the executive summary explicitly admits that the findings "do not establish the physical location of the chips, how they were acquired, or whether export control regulations were violated". Depue himself rented a cloud GB200 instance just to run his verification test. Commercial labs that are not on the Entity List renting bare-metal Blackwell nodes in offshore clouds (Singapore, Japan, or the Middle East) is completely legal under BIS rules and leaves the exact same SM fingerprint. Now ask yourself why a former OpenAI researcher dropped this on November 12, the exact day Jensen Huang was pushed out, with OpenAI and Anthropic immediately stepping in to "independently verify" it. US closed-source labs are watching their paid API moats get eaten alive by free Chinese open-weights models. Conflating a step-0 PRNG initialisation seed with a "$500M smuggled Blackwell cluster" hands DC hawks the exact pretext OpenAI and Anthropic want to regulate global cloud compute and kneecap open-source AI.

有没有币圈优质大哥 这个群里的老妹儿想让我帮忙介绍一个 情绪价值绝对拉满 想怎么玩儿就怎么玩儿 身高167 体重100 洛阳人 06年 可接受轻度SM 需要实力大哥老妹儿让我帮忙挑一个 刚大学毕业 绝对不调皮不捣蛋 会提供情绪价值 会来事 知进退

哈哈哈，刚听了一个出轨故事！ 有个已婚女人开房玩SM，主人把她捆绑吊起来后出门买东西了，由于挂的时间太长出现不适大喊大叫惊扰了其他住客，叫声过于惨烈服务员报了警，警察到后敲门，出轨女说别进来我没穿衣服叫我男朋友回来，警察好心查了女人登记信息，开房只登记了女人信息所以警察根据已知信息通知了女人老公，老公推开酒店房门后说自己看到了只蚂蚱挂在蜘蛛网上🤣🤣🤣

华语网黄 Top 10 先声明一下：以下排名纯属个人主观审美，不分先后，也不代表任何权威榜单。就是我想到谁就写谁，看到哪位老师想起来了就顺手点评两句。😂 1. 奶咪 @Anaimiya 奶咪是真的卷。更新勤奋程度在这个圈子里都属于劳模级别，而且当年还在抖音带起过一阵模仿热潮。能长期保持曝光和热度，本身就说明她非常懂流量。 2. 噗噗 @waifupupu 噗噗老师属于那种第一次看确实会有点惊艳的类型。表情、身材、镜头表现力都非常有辨识度，反差感拉满。只不过看久了之后，个人感觉表情和内容套路会稍微有一点审美疲劳。 3. 玩偶姐姐 @hongkongdoll 这个不用多说。华语区巅峰级人物。口罩、氛围感、镜头语言，甚至整个IP的塑造，都属于后来者很难完全复刻的类型。而且她还是Crypto相关内容的参与者。 她是我和几个同学第一次在 OnlyFans 上消费的华语创作者。尤其是那个“陪玩”系列……只能说：太他妈经典了。给我看哭了😭 4. 困困狗 @kunkunkun188 困困狗属于比较有个人风格的那一类。尤其是她的一些偏SM审美的内容，确实很容易让人记住。 只能说：苦练绝技，只为模仿。 5. 刘玥 @SpicygumL 刘玥老师，属于这个圈子的老教师了。算是我的启蒙老师之一 6. 饼干姐姐 @FortuneCutie00 饼干姐姐最大的特点之一：腿是真的长。又细又长，视觉辨识度非常高。身材条件又非常突出。 7. kitty @kitty2002102 kitty老师的身材确实不错。属于那种不需要太复杂的人设，单纯靠身材条件和镜头表现力就能把辨识度拉起来的类型。 8. 阿朱 @azhua1997 有时候一个人的辨识度，不一定来自五官或者身材，而是来自一个固定的神态。 9. 台北娜娜 @Nana_taipei 台北娜娜老师必须提名。尤其是那个经典的：“二郎腿战神。”这个称号不是我乱封的，是真的有画面感。 10. 桥本香菜 @qiobnxingcai 最后一个留给桥本香菜老师。我只能说：这个眼神，真的很有东西。丝袜、美腿、反差感，再加上那个标志性的眼神，辨识度非常高。 眸子里面都含水呀。 总之，以上纯属个人审美 + 个人记忆 + 个人胡说八道。

忍不住甩奶骚叫求爸爸进来 被爸爸扇耳光骂母猪宝宝怎么骚成这样 奶头硬了逼水还流一地 让狗狗自己掰着大腿含着手指拱逼讨好爸爸 #女喘# #kp# #手冲实录# #sm# #调教# #骚货#

来大理找k线教主了 @Paris13Jeanne 这次主要是为了和她学习交易策略，并不是为了和她玩儿sm，望君知。 为了好好体验一下 @protocol_fx @FX100Perp 的测试网产品，过来找她取取经。 师夷长技以制夷，准备学好交易知识，好在fx上面狠狠厮杀。 为后续去丙察察的经费，做好充足准备 Fighting