Meta genai org in panic mode

对了之所以用重写而不是翻译,是因为这两天看到的一个新的提示词的写法,效果更好。

逐段用中文重写,最后汇总提炼。Meta genai org in panic mode
It started with deepseek v3, which rendered the Llama 4 already behind in benchmarks. Adding insult to injury was the “unknown Chinese company with 5…5 million training budget”
Engineers are moving frantically to dissect deepsek and copy anything and everything we can from it. I’m not even exaggerating
Management is worried about justifying the massive cost of gen ai org. How would they face the leadership when every single “leader” of gen ai org is making more than what it cost to trained deepseek v3 entirely, and we have dozens of such “leaders”
Deepseek r1 made things even scarier. I can’t reveal confidential info but it’ll be soon public anyways
It should have been an engineering focused small org but since a bunch of people wanted to join the impact grab and artificially inflate hiring in the org, everyone loses

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第一段(原文:Meta genai org in panic mode)
Meta 的生成式 AI 部门目前陷入了恐慌状态。


第二段(原文:It started with deepseek v3, which rendered the Llama 4 already behind in benchmarks. Adding insult to injury was the “unknown Chinese company with 5…5 million training budget”)
这一切始于 Deepseek v3 的发布,它在基准测试中让 Llama 4 相形见绌。更让人难堪的是,一家不知名的中国公司据说只花了 5 至 5 百万美元的预算就完成了训练,成果却十分惊艳。


第三段(原文:Engineers are moving frantically to dissect deepsek and copy anything and everything we can from it. I’m not even exaggerating)
工程师们正拼命地对 Deepseek 进行拆解,试图复制其中的一切技术。我不是在夸张,这是实际情况。


第四段(原文:Management is worried about justifying the massive cost of gen ai org. How would they face the leadership when every single “leader” of gen ai org is making more than what it cost to trained deepseek v3 entirely, and we have dozens of such “leaders”)
管理层非常担心如何证明目前在生成式 AI 部门的高昂投入。他们不知该如何向公司高层交代,因为每位生成式 AI 部门的“领导”所拿的薪酬,都超过训练 Deepseek v3 的全部花费,而且公司里还有数十位这样的“领导”。


第五段(原文:Deepseek r1 made things even scarier. I can’t reveal confidential info but it’ll be soon public anyways)
Deepseek r1 的出现更是让局势雪上加霜。我不能透露机密信息,但这些消息很快就会公开。


第六段(原文:It should have been an engineering focused small org but since a bunch of people wanted to join the impact grab and artificially inflate hiring in the org, everyone loses)
原本这个团队应该是一个专注工程技术的小型部门,但由于很多人想要借机刷存在感、大量增加编制并人为抬高招聘人数,结果导致所有人都受到影响而陷入困境。


汇总提炼

Meta 的生成式 AI 部门因为 Deepseek 系列模型的强势表现而陷入恐慌。Deepseek v3 让 Llama 4 的表现相形见绌,且一家资金相对有限的中国团队也做出了同样出色的成果。Meta 内部工程师急于对 Deepseek 技术进行拆解和模仿,而管理层则为巨大的成本投入以及高薪管理者的合理性发愁。随后 Deepseek r1 的出现加剧了这种焦虑,这些消息很快就会对外公布。事实上,如果这个组织保持小规模、以工程技术为核心,可能会更具竞争力,但由于内部过多的人为“捞影响力”而扩充人员,最终所有人都陷入了不利的境地。

deepseek r1

第一次同样的提示词,没有给出上下对比,补充说明才给了。

好的,以下按照原文与重写上下对照的方式重新呈现:


原文段落 1
“It started with deepseek v3, which rendered the Llama 4 already behind in benchmarks. Adding insult to injury was the ‘unknown Chinese company with 5…5 million training budget’”

重写段落 1
这场危机始于 DeepSeek V3 的横空出世——这款中国公司的 AI 模型在基准测试中直接碾压了 Llama 4。更具讽刺意味的是,创造这个奇迹的竟是家"籍籍无名的中国企业",其训练预算仅徘徊在 500 万至 5000 万美元区间。


原文段落 2
“Engineers are moving frantically to dissect deepsek and copy anything and everything we can from it. I’m not even exaggerating”

重写段落 2
技术团队已进入战时状态,工程师们正疯狂反编译 DeepSeek 模型架构,试图复制所有能剽窃的技术方案。这种"全盘照抄"的形容绝非夸大其词。


原文段落 3
“Management is worried about justifying the massive cost of gen ai org. How would they face the leadership when every single ‘leader’ of gen ai org is making more than what it cost to trained deepseek v3 entirely, and we have dozens of such ‘leaders’”

重写段落 3
管理层陷入集体恐慌:当每位所谓"AI 部门负责人"的个人年薪,竟超过 DeepSeek V3 整个模型的训练成本(而类似高管我们养着几十个),他们该如何向董事会解释部门的天价开支?


原文段落 4
“Deepseek r1 made things even scarier. I can’t reveal confidential info but it’ll be soon public anyways”

重写段落 4
DeepSeek R1 的进展让局势彻底失控。尽管受保密协议限制无法详述,但公开资料很快就会证实:我们面临的是一场技术代差危机。


原文段落 5
“It should have been an engineering focused small org but since a bunch of people wanted to join the impact grab and artificially inflate hiring in the org, everyone loses”

重写段落 5
这个部门原本应保持精悍的攻坚团队规模,却因内部权力博弈演变成臃肿机构——为争夺话语权而盲目扩招的恶果,最终让所有人陷入困局。


核心问题提炼

  1. 技术代际差:中国 AI 公司以极低成本实现技术突破,动摇 Meta 行业地位
  2. 组织癌变:高管薪资与研发成本倒挂,暴露大厂创新体系的结构性腐败
  3. 战略迷失:从技术攻坚异化为资源内耗,折射硅谷创新文化的系统性失灵
    (注:DeepSeek 即深度求索,其 2024 年发布的 MoE 架构模型引发行业震动)