DeepSeek的AI培训背后的十亿美元现实

DeepSeek一直在新闻中，这是有充分理由的。有争议的说法是，中国初创公司在两个月内仅使用600万美元来建立AI模型，这震惊了全球的开发商。

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

中国初创公司DeepSeek一直因其在预算相对较小的大型AI模型方面的令人印象深刻的壮举而成为头条新闻。

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

虽然初始报告声称该模型的培训仅为600万美元，但新信息表明，实际费用明显更高。

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

白宫AI和Crypto Czar的David Sacks参加了X，与他的120万追随者分享了更新。

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

萨克斯在他的帖子中强调了半导体分析师迪伦·帕特尔（Dylan Patel）的一份报告。

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.

根据Patel的分析，DeepSeek可能在其计算集群上花费了超过10亿美元，这比广泛报道的600万美元的数字多了数亿美元。

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.

萨克斯进一步解释说，这笔600万美元的数字仅与最终培训有关，不包括DeepSeek的主要支出的关键方面。

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.

报告的金额中排除的一些显着费用是资本支出（购买和设置DeepSeek的硬件成本）和研发（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.

与研究AI模型，开发和优化DeepSeek有关的所有费用均未纳入600万美元的计算中。

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

基于这些信息，Sacks意味着建立DeepSeek的AI模型的成本属于十亿美元的范围。

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

此外，他驳斥了600万美元的报告是不真实和误导的，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所谓的误导性主张的更详细的细分。

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

它坚持认为600万美元仅考虑图形处理单元（GPU）预培训。

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

它将实际的总基础设施成本和研发和服务器资本支出固定在13亿美元左右。

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.

另一个值得注意的声称它揭穿了筹码。半分析指出，虽然DeepSeek经营50,000个Hopper GPU，但并非全部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。由于美国出口限制，H20是中国的版本。

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

但是，半分析还强调了美国的出口限制，这是对DeepSeek扩张野心的潜在障碍。

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.

尽管对DeepSeek AI模型培训的真实成本的数字有不同的数字和不同的看法，但分析师认为，该开发项目可能会对加密货币部门产生重大影响。

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.

正如它认为可以更少的情况下实现更多的，区块链和不同的加密项目可能需要从开发人员那里获得更高的效率和价值。

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

这可能会导致加密空间中的新升级，以提高可扩展性和效率。

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.

更新后，AI令牌进行了篮板连胜。 Internet计算机跃升了2.80％至9.9336美元，注入式注入1.82％至20.40美元，接近协议跃升了2.2％至$ 4.616。