In the field of AI, DeepSeek has undoubtedly become the focus of this year. As many companies have devoted themselves to its application practice, a consensus has gradually reached in the industry: the popularity of DeepSeek is not only a victory for AI large model technology, but also a key turning point for the AI industry from technological innovation to commercial application.

The core of this transformation lies in the fact that AI technology must not only achieve breakthroughs, but also have the ability to be commercialized, so that AI technology can go out of the laboratory and become a practical tool to promote the development of social productivity. The cooperative practice of silicon-based flow and ascension provides a strong proof of this.

At the Ascend AI Partner Summit, Jian Hu, co-founder and chief product officer of Silicon Flow, shared his journey with Ascend to promote DeepSeek's business practices. He mentioned that the triple superposition of technology, cost and scale is the key factor to promote the application of large model inference.

Hu Jian's views coincide with the core issues of the current AI industry. The combination of high-performance models such as DeepSeek and the computing power support of Ascend, coupled with the engineering capabilities of silicon-based flow, jointly promote the process of enterprise application of large models and accelerate the popularization and application of AI technology.

However, although DeepSeek has quickly become popular due to its low cost and high performance, there is no linear relationship between model capability and industrial value. Strong model capability does not mean that the industrial value must be high.

Hu Jian pointed out that when deploying AI models, enterprises still face multiple challenges, such as difficult hardware adaptation, data security, slow computing power efficiency, and lack of ecology. How to improve the inference speed of large models in a restricted environment and make it truly an intelligence in the application is a pain point faced by enterprises.

但挑戰往往伴隨著機遇。春節期間，矽基流動與昇騰迅速上線了DeepSeek的“滿血版”模型推理服務，取得了顯著的市場反饋。平臺流量激增，日訪問量突破百萬，註冊用戶超過500萬，矽基流動也因此登頂AI產品增速榜。

This successful case shows that the digital and intelligent transformation of enterprises is urgent. The popularity of DeepSeek has made enterprises see the potential of applying AI large models, but how to implement them has become a difficult problem. The cooperation between Silicon-based Flow and Ascend not only provides enterprises with a path for efficient application, but also verifies the standard paradigm of inclusive development of the AI industry - the synergy of model capabilities, computing power and cloud services.

With only DeepSeek's model capabilities and the support of computing power and cloud services, its phenomenal popularity may be difficult to sustain, and it is even more difficult to quickly transform into industrial value. The practice of silicon-based flow and ascension has fully proved that the key to achieving high performance of large AI models is to maximize optimization on different hardware for different models.

In this process, the local AI industry ecosystem has sorted out a relatively complete process to undertake the huge traffic brought by DeepSeek. With its technological advantages, silicon-based flow has gained a cost advantage in a short period of time, and then won a larger scale. The combination of technology, cost and scale makes it stand out in the fierce market competition.

A lot of optimization work has been done on silicon-based flow and ascension to adapt to the underlying architecture of DeepSeek, including operator fusion and scheduling optimization, and deep adaptation of the underlying framework architecture design. These technical optimizations have greatly enhanced the core competitiveness of silicon-based flow in the AI industry, and also provided a stable and reliable foundation for enterprise applications to deploy DeepSeek.

For the application deployment of large AI models, enterprises need a comprehensive solution covering model adaptation, computing power support, and application acceleration. DeepSeek provides top-level model performance, Ascend provides high-performance computing resources and adaptation capabilities as the computing base, and Silicon-based Flow provides one-stop MaaS cloud services, large model inference engines and other engineering capabilities to accelerate the development of the AI industry.

As more and more companies find that domestic solutions can not only evolve co-evolution, but also compete with international giants in terms of performance, and provide services that meet local needs, the market's attitude towards domestic technology systems is gradually changing. The popularity of DeepSeek is not only the success of a large AI model, but also an inflection point in the co-evolution of domestic technology systems.