DeepSeek is a Chinese AI company that has shaken up the industry with its efficiency claims. The company claims training their V3 model, the predecessor of the R1 model that everyone is using, costs just $5.576 million to train.
Since the release of the R1 model, DeepSeek has achieved widespread adoption all over the world and now Arm CEO predicts that the US government could soon ban the Chinese AI company. National security? Let’s explore what could be the reason.
According to a previous report, NASA has already blocked DeepSeek from its systems, and the U.S. Navy has warned personnel against using the AI service.
DeepSeek is reportedly 50-75% more efficient than its competitors. Despite requiring less power and compute, it has outperformed the OpenAI’s o1 model in different tests. Additionally, it’s free and open source, meaning anyone can build their AI application on top of it.
Privacy? One can download the model and run it locally on their own system. The 7b or 8b parameter model (both are less than 5GB in size) can be installed and operated on a consumer grade device.
A possible reason behind the prediction
DeepSeek has achieved a widespread adoption throughout the world (including the US) and triggered a major selloff in AI-related stocks, with Nvidia losing $600 billion in market value over fears that lower-cost AI models could reduce the demand for expensive AI chips.
It not only achieved the top position in Apple’s app store but also convinced US-based giants like Microsoft to adopt it—companies that would have otherwise stuck with OpenAI for its AI needs. Perplexity has also integrated DeepSeek R1 for better reasoning capabilities and overall smarter responses, which they are running on their servers.
We will need to see if the prediction turns out to be true and how the US companies that are already using or working on it navigate the situation.
Not to mention a lot of the Chinese smartphone makers such as Huawei, Honor, Oppo, and ZTE have also introduced the collaboration with DeepSeek and are working on distilled versions of the R1 model for their on-device AI needs.
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