Hyperliquid co-founder Jeff Yan has recently indicated that the encryption industry is becoming more and more difficult to attract leading young entrepreneurs, and that AI’s rapid expansion and prestige are taking away a pool of technologists who could have entered the chain.
In his view, this has become one of the main obstacles currently facing the encryption industry. For early entrepreneurs, chain finance should have been an area where market structures could be restructured from the bottom, involving both engineering and economic design. But without a sufficient number of high-capacity entrepreneurs, such work is more difficult to advance.
Yan claims there's still technical space on the chain.
Yan stated that young entrepreneurs should look not only at the apparent heat of the industry, but also at what it is addressing. In his view, chain finance continued to provide a strong technological and entrepreneurial space, particularly with regard to translating financial theory at the academic level into large-scale market design.
He mentioned that such work was not just about developing a single product, but rather about building a financial system that was able to operate in a stable manner and making it truly available to ordinary users.
IA competition for heat is driving brain transfer.
Yan's statement appears at a time when competition continues to rise. The report mentions that Chinese AI developers have recently received more attention in the global ranking of models. The Chinese model Kimi K3 recently rose to number one in Frontend Code Arena.
This result also triggered a discussion in the United States community of science and technology. David Sacks, former White House encryption chief, said that the United States could slow down the local AI company’s iterative pace if too many restrictions were placed on data centre construction, state-level regulatory requirements and federal review, while Chinese companies continued to advance model capabilities.
By comparing this situation with the early stages of Internet development, Sacks argues that an important reason why the United States was able to build a technological lead in that year was that firms could make products before regulating specific risks.
The risk of overheating in AI is also of concern.
While AI attracts talent and capital, the market is alert to the magnitude of its capital expenditure. George Noble, a former fund manager in Fuda, warned that if the AI bubble breaks, the financial shock could be much greater than the Internet bubble period.
He estimated that if the investment in related infrastructure failed to deliver the expected returns from investors, the losses could spread beyond the science and technology sector and to other parts of the financial system.
For Yan, the question is not just whether AI will form an asset bubble, but the more real pressure is on the brain flow. Central to its judgement is that if the chain of finance wishes to make complex theories truly a market for large-scale users, more capable entrepreneurs are needed to enter the field.