AI and Crypto Assets: An Unexpected Competition

Recently, the development of AI and the Crypto Assets field has shown an unexpected trend. This competition is not advancing evenly as people expected, but rather presenting a situation of mutual rise and fall. Breakthrough advances in AI technology seem to be having a significant impact on traditional capital markets and the Crypto Assets market.

On January 27, China's AI large model DeepSeek emerged as a strong contender, with its download volume surpassing ChatGPT for the first time, taking the top spot on the US App Store. This event has garnered widespread attention and discussion in the global technology, investment, and media circles.

This breakthrough not only sparked thoughts on the possible reshaping of the technology landscape between China and the United States but also triggered a brief panic in the US capital markets. As a result, several tech giants saw significant declines in their stock prices, with Nvidia down 5.3%, ARM down 5.5%, Broadcom down 4.9%, and TSMC down 4.5%. Other companies such as Micron, AMD, and Intel also experienced varying degrees of decline in their stock prices. The Nasdaq 100 futures even dropped to -400 points, potentially setting the record for the largest single-day drop in recent times. It is estimated that the market value of the US stock market may have evaporated by more than $1 trillion during the day's trading, equivalent to one-third of the total value of the entire crypto assets market.

Following the trends of the US stock market, the Crypto Assets market has also faced severe selling pressure. The price of Bitcoin fell below $100,500, with a 24-hour decline of 4.48%; Ethereum dropped below $3,200, with a 24-hour decline of 3.83%. Many investors are confused by this sudden plunge, with some speculating that it may be related to lowered expectations of interest rate cuts by the Federal Reserve or other macroeconomic factors.

The rise of DeepSeek is surprising not only for its technical strength but also for its efficient use of resources. Compared to the billions of dollars invested by other AI giants, DeepSeek achieved such accomplishments in less than two years with 200 employees and a development cost of less than 10 million dollars. This high efficiency has sparked reflections within the industry on the existing AI development model.

A vice president of a certain product commented on social media that the success of DeepSeek is a typical case of disruptive innovation. They did not simply optimize existing processes, but fundamentally rethought the approach to AI development. "What if we do this smarter, rather than just throwing more hardware at it?" This mindset has led to remarkable results.

Through innovative technological methods, DeepSeek has reduced the cost of traditional AI model training from 100 million dollars to 5 million dollars, the GPU demand from 100,000 to 2,000, and the API costs by 95%. More importantly, their models can run on standard gaming GPUs without the need for expensive data center hardware. This is not magic, but extremely clever engineering design.

The success of DeepSeek challenges many traditional notions, including the perception of China's technological innovation capabilities, Silicon Valley's leading position in the AI field, the moats of large AI companies, and the assumption of high costs in AI development. Although these views have not been completely overturned, they have been significantly shaken.

A well-known equity investment institution pointed out in its briefing that the success of DeepSeek represents a victory for the open-source model over the closed-source model. Contributions from the open-source community will quickly translate into prosperity for the entire industry. However, they also believe that closed-source models like OpenAI still have the potential for new breakthroughs through continued investment.

DeepSeek's innovation reduces enterprises' reliance on expensive APIs, providing greater development space for downstream applications. In the next year or two, we may see more diversified inference chip products and a more prosperous ecosystem of large language model applications.

Although DeepSeek has improved the efficiency of AI models, this does not mean that the demand for computing power will decrease. Historical experience shows that improvements in technological efficiency often lead to broader applications and greater market demand, just like how the increase in the efficiency of steam engines during the Industrial Revolution actually increased the total consumption of coal.

This major breakthrough in AI technology will undoubtedly have a profound impact on the technology industry and financial markets. It not only changes people's perceptions of the development path of AI but may also reshape the global landscape of technological competition. For investors and practitioners, closely monitoring the trends in this field and adjusting strategies in a timely manner will become increasingly important.