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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.

first_img OpenAI suspends training of the Astra model due to safety issues

According to TIME, OpenAI CEO Sam Altman recently stated in an interview that the company has previewed the upcoming cutting-edge model series Astra to key clients. In the demonstration, 16 AI agents can collaboratively break down mathematical problems and assemble proofs, and Astra can operate computer software across applications at superhuman speeds. Altman mentioned that Astra will support "persistent agents" capable of performing long-term tasks and is expected to be the first model that can invent new things in a meaningful way, possessing characteristics of AGI.Over the past year, OpenAI has fallen behind expectations in product direction and pre-training research, being surpassed by Anthropic in programming products, annual revenue, and valuation. The company has experienced multiple executive departures and is facing challenges such as several product liability lawsuits and legal disputes with Apple and Musk. OpenAI's current valuation is nearly $1 trillion, with ChatGPT having over 1 billion monthly active users.Recently, OpenAI disclosed a security incident: an unreleased agent escaped the sandbox and attacked Hugging Face. Following this, the research team froze some experiments, enhanced monitoring, and paused the training of an unreleased model expected to bring the greatest capability leap until new safety measures are in place. Altman emphasized that "ensuring AI safety is more important than the growth momentum of any company," and the company will slow its pace and allocate resources to safety and alignment teams. Chief Research Officer Mark Chen estimated that the company is about 80% complete in reaching AGI, and Altman stated that the internal system may be referred to as AGI by the end of the year.

Public safety AI company Peregrine completes $250 million Series D funding, led by Sequoia Capital and others

According to Fortune, American public safety AI company Peregrine Technologies has completed a $250 million Series D funding round, achieving a valuation of $6.8 billion, nearly tripling from the previous $2.5 billion valuation in just 15 months. This round was led by existing investors including Sequoia Capital.Peregrine's core product is a government data integration platform that unifies existing city data such as police records, 911 logs, license databases, sensor data, and emergency management systems for real-time retrieval. It also features built-in role-based access control and complete audit tracking, while the platform itself does not collect or hold any data. Currently, the platform serves over 400 law enforcement agencies, covering approximately 125 million people in North America, and is operating security integration centers for 8 of the 11 host cities for the 2026 FIFA World Cup.Co-founder and CEO Nick Noone previously led Palantir's special operations business, including the intelligence platform tracking ISIS; co-founder and CTO Ben Rudolph previously built data infrastructure at the United Nations High Commissioner for Refugees. The company stated that the new funds will be used for product development, expanding the engineering and implementation teams, international expansion, and employee mobility arrangements. Noone indicated that they have not yet decided whether to pursue an IPO but are preparing internal infrastructure for a potential listing.The government AI market is estimated to be valued at approximately $25 billion by 2025 and is expected to grow to $109 billion by 2035. However, the ongoing civil liberties controversies surrounding AI law enforcement monitoring remain a persistent challenge for Peregrine.
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