Name: DeepSeek R1--震驚整個行業的中國人工智能 "副業"！ (DeepSeek R1 - The Chinese AI "Side Project" That Shocked the Entire Industry!)
Uploaded: 2025-01-27T19:10:04.000Z
Duration: 16 min 45 s

基礎被動語態

DeepSeek R1 was released just a few days ago and it has sent shockwaves through the AI industry.

DeepSeek R1 發佈僅幾天，就在人工智能行業引起了震動。

程度副詞

R1 is an AI model that has the ability to think just like OpenAI's cutting-edge, state-of-the-art O1 and O3 models.

R1 是一種人工智能模型，具有與 OpenAI 最先進的 O1 和 O3 模型一樣的思維能力。

But here's the thing, it's completely open source and open weights.

但問題是，它是完全開源和開放權重的。

DeepSeek, a small Chinese company, gave all of it away for free and they even detailed how to reproduce it.

DeepSeek 是一家中國小公司，他們免費提供了所有這些資訊，甚至詳細介紹瞭如何複製這些資訊。

It was trained for just $5 million, as compared to the tens and hundreds of millions of dollars that most people in the AI industry thought was required to train a model of this caliber.

它的訓練費用僅為 500 萬美元，而人工智能行業的大多數人都認為訓練這樣一個模型需要數千萬甚至數億美元。

And it has sent everyone in the AI industry scrambling to understand the ramifications.

這讓人工智能行業的每個人都爭先恐後地瞭解其影響。

DeepSeek has been called everything from the downfall of major US tech companies like OpenAI and Meta, to the greatest gift to humanity, to a Chinese psyop meant to shake the US to its core.

DeepSeek 被稱為美國大型科技公司（如 OpenAI 和 Meta）的垮臺、人類最偉大的禮物，以及中國旨在動搖美國核心的心理戰。

這個故事很瘋狂，請繫好安全帶。

So just about a week ago, President Trump, Sam Altman, the founder and CEO of OpenAI, the founder of Oracle, and many others got together to make the announcement about Project Stargate.

就在一週前，美國總統特朗普、OpenAI 創始人兼首席執行官山姆-奧特曼、甲骨文公司創始人以及其他許多人聚在一起，宣佈了 "星際之門計劃"。

That is a $500 billion investment in AI infrastructure built in the US.

這相當於在美國投資 5000 億美元建設人工智能基礎設施。

That is on top of the billions and potentially trillions that have already been spent on GPUs, mostly coming from NVIDIA.

除此之外，英偉達™（NVIDIA®）公司已經在 GPU 上投入了數十億甚至數萬億的資金，其中大部分來自英偉達™（NVIDIA®）公司。

Then, right after that, Mark Zuckerberg doubled down on how much his company, Meta, is going to spend on AI infrastructure.

緊接著，馬克-扎克伯格又加倍強調了他的公司 Meta 在人工智能基礎設施上的投入。

Also stating that they are going to continue to spend many billions of dollars building out energy infrastructure and AI infrastructure.

同時還表示，他們將繼續斥資數十億美元建設能源基礎設施和人工智能基礎設施。

So the theme amongst the biggest tech companies in the world is spend as much as we can to win at AI.

是以，世界上最大的科技公司的主題就是盡我們所能，在人工智能領域取得勝利。

On January 20th, 2025, a small Chinese research firm called DeepSeek released DeepSeek R1, a completely open source, open weights, AI model that has the ability to think, also known as test time compute, that is directly competitive, if not slightly better than the O1 model by OpenAI that cost hundreds of millions of dollars to train.

2025 年 1 月 20 日，中國一家名為 DeepSeek 的小型研究公司發佈了 DeepSeek R1，這是一個完全開源、開放權重的人工智能模型，它具有思考能力，也稱為測試時間計算能力，與花費數億美元訓練的 OpenAI 的 O1 模型相比，即使不略勝一籌，也有直接競爭力。

And just like that, the AI world was flipped upside down.

就這樣，人工智能世界發生了翻天覆地的變化。

All of a sudden, we had this completely open source version of a state-of-the-art model that we didn't think we were going to have so soon, let alone to be absolutely open source and essentially free.

突然之間，我們擁有了一個完全開源版本的最先進模型，我們沒想到會這麼快擁有它，更沒想到它是絕對開源的，而且基本上是免費的。

The initial reaction was extremely strong.

I'll drop them down in the description below.

我會在下面的描述中一一列出。

The biggest names in the AI industry realized we now had a completely open source, state-of-the-art model.

人工智能行業的大佬們意識到，我們現在有了一個完全開源、最先進的模型。

And as everybody was taking this in and super excited that we can play around with it, reproduce it, suddenly the tone shifted.

就在大家都沉浸其中，為我們能玩轉它、複製它而興奮不已時，基調突然發生了變化。

In the technical paper that was released alongside DeepSeek, it was noted that that model was trained for just $5 million.

與 DeepSeek 同時發佈的技術論文指出，該模型的訓練費用僅為 500 萬美元。

That is a fraction of the cost of what every other state-of-the-art model costs to train.

這只是其他先進模型訓練成本的一小部分。

Meta, Microsoft, OpenAI, and all of the magnificent seven, basically the biggest seven tech companies in the world, have been investing trillions of dollars building out AI infrastructure.

Meta、微軟、OpenAI，以及所有七大巨頭，基本上是世界上最大的七家科技公司，一直在投資數萬億美元建設人工智能基礎設施。

And then all of a sudden, this little Chinese company comes along, open sources a model that's comparable to the best models out there.

然後突然間，這家中國小公司出現了，開源了一款可與最好機型媲美的機型。

And not only did they make it completely free, but they said it only costs $5 million.

他們不僅完全免費，還說只需 500 萬美元。

And then all of a sudden, a lot of analysts are looking at these big companies spending billions of dollars per year and thinking, do we really need that?

突然之間，很多分析師看到這些大公司每年花費數十億美元，心想，我們真的需要這樣嗎？

And a lot of people are pointing at these big companies saying, you guys are about to  You've invested so much money and it wasn't even necessary.

很多人指著這些大公司說，你們就要投資這麼多錢了，但這根本沒必要。

Now I will tell you, I do not agree with that whatsoever.

現在我要告訴你們，我完全不同意這種說法。

But that is a theme going on right now in the AI industry.

但這正是目前人工智能行業的一個主題。

And then somebody on Twitter asked, how is DeepSeek going to make money?

推特上有人問，DeepSeek 如何賺錢？

How are they actually going to make money?

And the API endpoint to actually run the model is really, really cheap.

而實際運行模型的 API 端點非常非常便宜。

你可以在自己的硬件上運行它。

DeepSeek's holding, and this is the Chinese company's name, is a quant company, meaning They are mathematicians tasked with building trading algorithms simply to make money.

DeepSeek 的控股公司，也就是這家中國公司的名字，是一家量化公司，這意味著他們是數學家，任務是建立交易算法，只是為了賺錢。

Many years already, super smart guys with top math background happen to own a lot of GPU for trading mining purposes.

多年來，擁有頂尖數學背景的超級聰明人碰巧擁有大量 GPU，用於交易挖礦。

And DeepSeek is their side project for squeezing those GPUs.

而 DeepSeek 是他們的副業，用於壓榨這些 GPU。

Essentially, this is not even the main function of the company.

從根本上說，這甚至不是公司的主要職能。

So a handful of smart people got together, figured out how to make a state of the art model, incredibly cheap, append the entire AI industry, and it was their side project.

於是，幾個聰明人聚在一起，想出瞭如何製作一個最先進的模型，以難以置信的低廉價格為整個人工智能行業提供附加服務，這就是他們的副業。

Let me show you a few of the reactions from people in the industry.

讓我向你們展示一些業內人士的反應。

Sam spent more on this, referencing this incredible automobile, which I know is multiple millions of dollars, and that Sam Altman driving it, than DeepSeek did to train the model that killed OpenAI.

山姆花在這上面的錢比 DeepSeek 花在訓練殺死 OpenAI 的模型上的錢還多，他提到了這輛令人難以置信的汽車，我知道這輛汽車價值數百萬美元，而且是山姆-奧特曼駕駛的。

現在，我再次重申，我並不真的相信這一點。

I will explain what I think is going on in a little bit.

Here we have Neil Khosla, son of Vinod Khosla, saying, DeepSeek is a CCP state psyop, plus economic warfare to make American AI unprofitable.

維諾德-科斯拉（Vinod Khosla）的兒子尼爾-科斯拉（Neil Khosla）在這裡說，DeepSeek 是中共的國家迷魂陣，外加經濟戰，目的是讓美國的人工智能無利可圖。

They are faking the cost was low to justify setting price low and hoping everyone switches to it to damage AI competitiveness in the US.

他們偽造成本低的假象，以證明把價格定得低是合理的，並希望所有人都改用它，從而損害人工智能在美國的競爭力。

Now, there was a community note saying there's zero evidence of this.

現在，有一份社區說明稱，沒有任何證據證明這一點。

In Davos, Alexander Wang, the CEO of ScaleAI, basically called out DeepSeek saying, no, they actually have many more GPUs than they're telling us, simply because there is an export ban on China from the US that we cannot export our cutting edge chips to them at scale.

在達沃斯論壇上，ScaleAI 首席執行官亞歷山大-王（Alexander Wang）基本上是在指責 DeepSeek，他說："不，他們實際上擁有的 GPU 比他們告訴我們的要多得多，原因很簡單，因為美國對中國有出口禁令，我們無法向他們大規模出口我們的尖端芯片。

And so in the research paper, if they admitted that they had a bunch of GPUs, obviously, the US would be pretty pissed.

是以，在研究論文中，如果他們承認自己有一堆 GPU，顯然美國會非常生氣。

And in this clip, Alexander Wang talks about how DeepSeek probably has 50,000 H100s, which are NVIDIA's top of the line GPUs.

在這個片段中，亞歷山大-王談到 DeepSeek 可能擁有 50,000 個 H100，這是英偉達公司的頂級 GPU。

And the fact that they can't talk about it because it goes against the export controls that the US has in place.

事實上，他們不能談論這件事，因為這違反了美國的出口管制。

And maybe that's true, although, again, remember, everything is open sourced and they really went into deep detail, they being DeepSeek, into how they actually produced this model for so cheap.

也許這是真的，不過，請記住，所有東西都是開源的，而且作為 DeepSeek，他們真的深入細緻地研究瞭如何以如此低廉的價格製作出這個模型。

And the company hugging face is reproducing it right now.

而公司抱團取暖的面孔正在重現。

Now let me show you some posts from Emad, who is the founder of Stability AI, who basically ran the numbers and figured out, yeah, it's actually legit what they're saying.

現在，讓我給你們看看埃馬德的一些文章，他是 Stability AI 的創始人，他基本上是通過數字計算得出的結論，是的，他們所說的其實是合法的。

DeepSeek 在運行成本方面沒有造假。

It's pretty much in line with what you'd expect, given the data structure, active parameters and other elements and other models trained by other people.

考慮到數據結構、活動參數和其他元素以及其他人訓練的其他模型，這與你的預期基本一致。

You can run it independently at the same cost.

這是一個努力工作的優秀實驗室。

He didn't put any numbers, but of course, he followed up and did.

他沒有提供任何數字，但當然，他隨後又提供了。

So he basically says, for those who want the numbers here, it is optimized.

是以，他基本上是說，對於那些想要這裡的數字的人來說，它已經優化了。

H100 could do it in less than 2.5 million.

實際上，他以前也是這麼想的。

And again, now all of the focus is back to the major tech companies, Anthropic, Meta, Open AI, Microsoft, who have raised and spent billions and billions of dollars to build out AI infrastructure only to have the rug pulled out from under them from this tiny Chinese company.

再說一遍，現在所有的焦點又回到了那些大型科技公司身上，Anthropic、Meta、Open AI、微軟，它們已經籌集並花費了數十億美元來建設人工智能基礎設施，卻被這家中國小公司搶走了風頭。

DeepSeek goes mega viral and they can handle the demand on their two Chromebooks they have to use for inference.

DeepSeek 引發了巨大的病毒式傳播，他們必須使用兩臺 Chromebook 進行推理，才能滿足需求。

Meanwhile, Anthropic cannot handle the load of their paying customers with billions in funding.

與此同時，Anthropic 無法承受數十億資金的付費客戶的負擔。

And that seems to be the sentiment across the board.

I've made over 200,000 requests to the DeepSeek API in the last few hours, zero rate limiting and the whole thing cost me like 50 cents.

在過去幾個小時裡，我向 DeepSeek API 提出了 20 多萬個請求，沒有任何費率限制，整個過程只花了我 50 美分。

We've been talking on this channel a lot about test time compute.

我們在這個頻道上經常談到測試時間計算。

A lot of the scaling that's happening in AI right now is not at pre-training, not that $5 million that it costs to actually build out the model.

目前，人工智能領域的很多擴展都不是在預訓練階段，而不是花費 500 萬美元來真正建立模型。

But since these models can now think and the more thinking they do, the better the results, that thinking is actually just compute.

但是，由於這些模型現在可以思考，而且思考得越多，結果就越好，是以這種思考實際上只是計算。

And so what's interesting about this is that even at test time, so they're hitting the API 200,000 times, zero rate limiting and extremely inexpensive, unless they are just losing tons of money and have a bunch of GPUs that we don't know about, they've figured out something about efficiency that the U.S. companies have not.

是以，有趣的是，即使在測試階段，他們也要對 API 進行 20 萬次攻擊，速度限制為零，而且成本極低，除非他們虧損嚴重，擁有大量我們不知道的 GPU，否則他們已經找到了美國公司沒有找到的提高效率的方法。

Alexander Wang follows up with a post, DeepSeek is a wake up call for America, but it doesn't change the strategy.

亞歷山大-王（Alexander Wang）跟進發表了一篇文章：DeepSeek 為美國敲響了警鐘，但並沒有改變戰略。

USA must out innovate and race faster, as we have done in the entire history of AI and tighten export controls on chips so that we can maintain future leads.

美國必須加快創新和競賽速度，就像我們在整個人工智能發展史上所做的那樣，並加強對芯片的出口管制，這樣我們才能保持未來的領先地位。

Every major breakthrough in AI has been American.

人工智能領域的每一次重大突破都是美國人取得的。

And continuing, China's DeepSeek could represent the biggest threat to U.S. equity markets as the company seems to have built a groundbreaking AI model at an extremely low price and without having access to cutting edge chips, calling into question the utility of the hundreds of billions of dollars worth of capex being poured into the industry.

此外，中國的 DeepSeek 公司可能是美國股市的最大威脅，因為該公司似乎以極低的價格建立了一個開創性的人工智能模型，但卻無法獲得最先進的芯片，這讓人們對投入該行業的數千億美元資本支出的效用產生了懷疑。

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DeepSeek R1--震驚整個行業的中國人工智能 "副業"！ (DeepSeek R1 - The Chinese AI "Side Project" That Shocked the Entire Industry!)

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