AI and the unexpected linkage with the Crypto Assets market

Recently, the development trends of AI and Crypto Assets have shown an unexpected interlinking effect. This linkage is not the synergistic growth that people anticipated, but rather manifests in a form of "collapse". The breakthrough advancements in AI technology first impacted traditional capital markets and subsequently extended to the Crypto Assets sector.

On January 27, the download volume of China's AI large model DeepSeek surpassed ChatGPT for the first time, topping the US App Store charts and attracting widespread attention from the global technology, investment, and media sectors. This event not only prompted people to contemplate the potential changes in the future global technology landscape but also triggered a brief panic in the US capital markets.

As a result, the stock prices of several tech giants have seen significant declines. Nvidia fell by 5.3%, ARM fell by 5.5%, Broadcom fell by 4.9%, and TSMC fell by 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, which could set a record for the largest single-day decline in recent times. It is estimated that the U.S. stock market may have evaporated over 1 trillion USD in market value during the day's trading, equivalent to one-third of the total market value of Crypto Assets.

Following the trends of the US stock market, the Crypto Assets market has also seen a significant decline. Bitcoin has fallen below $105,000, with a 24-hour drop of 4.48%. Ethereum has dropped below $3,200, with a 24-hour decrease of 3.83%. This phenomenon has left many investors confused, prompting them to consider the reasons behind the sudden drop in the Crypto Assets market, with some speculating that it may be related to reduced expectations of interest rate cuts by the Federal Reserve or other macroeconomic factors.

The panic in the market seems to stem from the rise of DeepSeek. Unlike companies such as OpenAI, Meta, or Google, which rely on substantial capital and large hardware resources, DeepSeek demonstrates astonishing cost efficiency. OpenAI has been established for 10 years, has 4,500 employees, and has raised $6.6 billion in funding. Meta has invested $60 billion in developing large AI data centers. In contrast, DeepSeek has been established for less than 2 years, has only 200 employees, development costs of less than $10 million, and has not purchased expensive GPU graphics cards in large quantities.

The success of DeepSeek not only reflects the cost advantages in terms of capital and technology but also challenges people's traditional perceptions of AI development. It demonstrates that through innovative thinking and efficient engineering, the development and operational costs of AI models can be significantly reduced. This disruptive approach has sparked widespread discussion and reflection in the industry.

Some analyses suggest that the emergence of DeepSeek may herald a new trend in the AI industry. The rise of open-source models could drive the prosperity of the entire AI ecosystem, while also potentially altering the current market landscape dominated by a few large companies. However, there are also viewpoints that with the further development of technology, new variables may arise in the competition between closed-source and open-source models.

Regardless, the success of DeepSeek demonstrates that the development of AI technology does not solely rely on the accumulation of funds and hardware; innovative thinking and efficient engineering are equally important. This event not only impacts the financial market but may also have far-reaching implications for the future direction of the AI industry.