DeepSeek的AI培訓背後的十億美元現實

DeepSeek一直在新聞中，這是有充分理由的。有爭議的說法是，中國初創公司在兩個月內僅使用600萬美元來建立AI模型，這震驚了全球的開發商。

DeepSeek, a Chinese startup, has been making headlines for its impressive feat in building a large AI model with a relatively small budget.

中國初創公司DeepSeek一直因其在預算相對較小的大型AI模型方面的令人印象深刻的壯舉而成為頭條新聞。

While initial reports claimed that the model cost just $6 million to train, new information suggests that the actual expenses are significantly higher.

雖然初始報告聲稱該模型的培訓僅為600萬美元，但新信息表明，實際費用明顯更高。

David Sacks, White House AI and Crypto Czar, took to X to share an update with his 1.2 million followers.

白宮AI和Crypto Czar的David Sacks參加了X，與他的120萬追隨者分享了更新。

In his post, Sacks highlighted a report by Dylan Patel, a semiconductor analyst at SemiAnalysis.

薩克斯在他的帖子中強調了半導體分析師迪倫·帕特爾（Dylan Patel）的一份報告。

According to Patel's analysis, DeepSeek might have spent over $1 billion on its compute cluster, which is hundreds of millions more than the widely reported figure of $6 million.

根據Patel的分析，DeepSeek可能在其計算集群上花費了超過10億美元，這比廣泛報導的600萬美元的數字多了數億美元。

Sacks further explained that the $6 million figure only pertains to the final training run and does not include critical aspects of DeepSeek's major expenditure.

薩克斯進一步解釋說，這筆600萬美元的數字僅與最終培訓有關，不包括DeepSeek的主要支出的關鍵方面。

Some notable expenses excluded from the reported amount are capital expenditure (the cost of buying and setting up the hardware for DeepSeek) and Research and Development (R&D) costs.

報告的金額中排除的一些顯著費用是資本支出（購買和設置DeepSeek的硬件成本）和研發（R＆D）成本。

All expenses related to researching the AI model, developing it, and optimizing DeepSeek were not factored into the $6 million calculation.

與研究AI模型，開發和優化DeepSeek有關的所有費用均未納入600萬美元的計算中。

Based on this information, Sacks implies that the cost of building DeepSeek's AI model falls within the billion-dollar range.

基於這些信息，Sacks意味著建立DeepSeek的AI模型的成本屬於十億美元的範圍。

Moreover, he dismissed the $6 million reports as untrue and misleading, possibly intended to just score points.

此外，他駁斥了600萬美元的報告是不真實和誤導的，可能只打算得分。

Interestingly, SemiAnalysis provided a more detailed breakdown of DeepSeek's alleged misleading claims.

有趣的是，半分析提供了DeepSeek所謂的誤導性主張的更詳細的細分。

It insisted that the $6 million only accounts for the Graphics Processing Unit (GPU) pre-training.

它堅持認為600萬美元僅考慮圖形處理單元（GPU）預培訓。

It pegs the actual total infrastructure cost and R&D and server capital expenditure at around $1.3 billion.

它將實際的總基礎設施成本和研發和服務器資本支出固定在13億美元左右。

Another notable claim it debunked relates to the chips. SemiAnalysis noted that while DeepSeek operates 50,000 Hopper GPUs, they are not all top-tier H100s.

另一個值得注意的聲稱它揭穿了籌碼。半分析指出，雖然DeepSeek經營50,000個Hopper GPU，但並非全部H100。

Rather, it is a mix of H100s, H800s and H20s. The H20s are China's version due to the U.S export restriction.

相反，它是H100，H800和H20的混合物。由於美國出口限制，H20是中國的版本。

However, SemiAnalysis also highlighted U.S. export restrictions as a potential hurdle to DeepSeek's expansion ambitions.

但是，半分析還強調了美國的出口限制，這是對DeepSeek擴張野心的潛在障礙。

Despite the varying figures and differing opinions on the true cost of DeepSeek's AI model training, analysts believe that the development could have a significant impact on the crypto sector.

儘管對DeepSeek AI模型培訓的真實成本的數字有不同的數字和不同的看法，但分析師認為，該開發項目可能會對加密貨幣部門產生重大影響。

As it suggests more can be achieved for less, blockchains and different crypto projects will likely demand greater efficiency and value for money from developers.

正如它認為可以更少的情況下實現更多的，區塊鍊和不同的加密項目可能需要從開發人員那裡獲得更高的效率和價值。

This might lead to new upgrades in the crypto space that aim for scalability and efficiency.

這可能會導致加密空間中的新升級，以提高可擴展性和效率。

Following the update, AI tokens went on a rebound streak. Internet Computer jumped 2.80% to $9.9336, Injective rallied 1.82% to $20.40, with Near Protocol jumping 2.2% to $4.616.

更新後，AI令牌進行了籃板連勝。 Internet計算機躍升了2.80％至9.9336美元，注入式註入1.82％至20.40美元，接近協議躍升了2.2％至$ 4.616。