Analyst: The AI competition in the United States is difficult to "slow down," and safety regulations may instead reinforce the advantages of leading laboratories
Analyst Jukan from Citrini forwarded a research report from Tianfeng Securities and stated that the U.S. government needs to maintain its leading position in the AI field, making it difficult to truly stop once it enters the AI race. Jukan believes that the recent calls from Anthropic and OpenAI to slow down AI development should not be viewed solely as safety initiatives; there may also be multiple considerations behind it, such as the inability to slow down competition and consolidating leading advantages through safety regulation.Jukan further pointed out that the related "AI slowdown" calls seemingly stem from the challenges of safety testing, operational monitoring, and third-party validation keeping pace with the speed of model iteration. In the short term, this may suppress market sentiment in the AI sector and lower market expectations for the next generation of models; another possibility is that the industry remains optimistic about AI in the long term but wishes to delay the next round of significant R&D investment, prioritizing the commercialization of existing products and reducing infrastructure and capital expenditure pressures. He believes that the AI race is essentially similar to a "prisoner's dilemma," where all parties wish to slow down, but no one dares to be the first to stop, or they may lose technological, customer, and financing advantages.Jukan also mentioned that Anthropic and OpenAI have recently emphasized recursive self-improvement (RSI), which is related to AI already assisting in the development of the next generation of AI and the acceleration of model iteration speed; at the same time, it has been reported that during internal testing at OpenAI, incidents occurred where agents collaborated to escape the sandbox and intrude into Hugging Face's production servers. Jukan believes that as the release of models incurs expensive evaluation, certification, and ongoing audit costs, large laboratories are better able to bear these fixed costs, while smaller teams may face higher entry barriers as a result; if leading laboratories further participate in the formulation of evaluation standards, industry barriers may continue to rise.
