DeepSeek CEO explains how he has transformed the chip shortage into his strategic alibi

One of the many battles that China and the United States are fighting is technological, specifically one related to artificial intelligence. US business spending on AI It’s astronomicalbut in China the ambition is no less and the Government wants it to be one of the pillars for the country to be the first world power in the short term.

One of the conversations surrounding Chinese AI compared to American AI has to do with efficiency. Very capable models, higher in some cases to the Americans, but with a much lower price and, above all, trained in record time. There are controversies about it, such as theft accusations by giants like Anthropic and OpenAI, but the reality is that if you don’t want to use the AI ​​of an American company, they are there alternatives like DeepSeekKimi or those from Zhipu AI.

But, speaking of Deepseek, the company’s CEO is clear that there is a Huge difference between Chinese AI Big Tech and American counterparts: computing capacity. He gives a fact to illustrate it: four Huawei chips are equivalent to one from Nvidia, and that opens the door for the US to have even more arguments to continue putting pressure on the Chinese technology industry.

The bottleneck is power, nothing more

Liang Wenfeng He is the CEO of DeepSeek and, like so many in his position in recent weeks, he has had the presentation before investors. These types of events are very interesting because they allow us to learn more about both the companies and their plans, and in this case it has been revealing to listen to the head of one of the most relevant AI companies today.

They are not official statements, since they are the leak of the almost four-hour meeting published by Tencent Tech, but among its many phrases, we can extract very interesting ideas. The first is what we mentioned: for the boss, the main gap is money and resources. “There is no gap in personnel, since it is basically the same group of people. Talent is not the bottleneck: resources are the biggest bottleneck,” says Liang.

The CEO continued to point out evidence, stating that “more cards are always better” and that, at a reasonable price, they buy as many as they can because “converting money into Nvidia cards is definitely better than leaving that money in the bank.” And the Nvidia cards stand out for a fact that is also very interesting: how many Huawei cards are equivalent to one Nvidia card.

Assures that the relationship is four to one, or what is the same: if they wanted to train a model with 800,000 million active parameters like the main American AI models, they would need 50,000 Nvidia GB300 cards or 200,000 Huawei 950 cards.

That It doesn’t seem to leave Huawei in a very good place.which are those that the Chinese industry and the Government itself is trying to promotebut Liang affirms that Nvidia is digging its own grave in the Chinese market, that the CUDA ecosystem is eroding quickly and that Huawei supernode 950 It can completely replace Nvidia’s GB200 and GB300 in both performance and price.

Although the 4:1 ratio between the chips seems alarming for the domestic company, Liang did not specify the workload or whether it measures raw performance, training performance or inference.

The US looks closely

One detail that Liang points out is that this computing power gap will end up closing as Huawei launches solutions and that, although he does not dare to guess when it will happen, it is something that will end up arriving. But of course, when the competition between the US and China is, in part, in that power of AI, the United States is not in the least interested in closing the gap.

In recent months we have seen how pressure has continued to prevent Chinese companies from accessing Western hardware that is key to the development of the semiconductor industry. ASML Extreme Lithography Machines are an exampleand more recently the White House accused Chinese startup Moonshot AI from acquiring servers equipped with Nvidia chips that they should not be able to access.

The case of Moonshot AI has been quite popular because a few days ago we told you about that amazing Kimi K3 model that, according to the Americans, would have been trained in Thailand with Nvidia GB300 chips to avoid United States export regulations. And they go further, arguing that Kimi K3 had ‘drunk‘the model Anthropic Fable.

Deepseek Strategy

Beyond politics, and returning to Liang, although right now it seems that China is not on par in terms of computing power, DeepSeek has a long-term strategy that has less to do with having the most powerful model currently. As we read in SCMPLiang commented that they are setting prices “to make only a reasonable profit, not to maximize revenue.”

And that is the key that the company apparently pursues, since they are keeping prices low for users with the aim of their service being increasingly used in the hope of increasing the possibility of achieving artificial general intelligence.

So while other companies prioritize immediate profits and capturing market share, Liang is focusing on “increasing the probability of achieving AGI“because it will be that AI that will have great commercial value. And that is what they do seek to exploit.

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