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A Guardian report noted that the Nasdaq Composite index, which has got a lot of tech companies listed, closed down 3.1% on the day R1 was released, with the drop at one point wiping off more than $1trillion in value

via Guardian

The prevailing opinion online and in newsrooms in the days following R1’s release is that DeepSeek’s rise is a clear indication that the US had lost its advantage or pioneering edge in AI. But experts, including executives at leading AI model development companies suggested that various shifts in the technological landscape were taking place. Rather than solely pursuing ever-larger models which demand vast computing power, the focus appeared to be now shifting towards advanced capabilities like reasoning. This shift creates opportunities for smaller, innovative startups like DeepSeek, which haven’t secured massive funding, nor are backed by large Tech behemoths like Google, Amazon, Meta or Microsoft.

But the warnings were there, in September DeepSeek published an image showing it’s model’s achievement on the LMSYS Chatbot Arena Rankings.

It’s probably too early to really have a strong opinion on what this means for the trajectory around infrastructure and Capex,” Mark Zuckerberg said. “There are a bunch of trends that are happening here all at once.”

Zuckerberg was talking to reporters about Meta’s earnings, and went on to say that his company is still studying DeepSeek and the implications of the release, and that eventually they may adopt the best aspects of what is learned. But it’s unlikely to significantly lower costs.

It’s going to be expensive for us to serve all of these people because we are serving a lot of people,” said Zuckerberg. He also said DeepSeek’s emergence is a validation of Meta’s open-source approach to AI.

As things stand, the true price of developing DeepSeek’s R1 is not yet known. Thus, many analysts and industry experts continue to believe that the true cost must have been a lot higher. However, even if it were $40million or $50 million, what would that change, because from everything that’s known at the moment, it’s still a game changer. 

In a June 2024 research paper, DeepSeek disclosed that its earlier model, DeepSeek-V2, was developed on clusters of Nvidia H800 chips, which are less powerful than the A100 Tensor Core GPU chips typically employed by leading US AI companies like OpenAI. However, some AI insiders speculate that DeepSeek might have used the computing power of more than the reported 10,000 Nvidia A100 chips the company said they had access to in developing and training the R1 model. 

The full impact of this story and the unfolding of this narrative are yet to be determined.

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