Palantir CEO Alex Karp vehemently criticizes the large-scale token fee model.
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David Sacks strongly supports Palantir CEO's criticism of AI labs: True enterprise AI security lies in controlling one's own data, models, and computing power.
According to Beating, David Sacks, co-chair of the U.S. President's Council of Advisors on Science and Technology, published an article supporting Palantir CEO Alex Karp's sharp criticism of cutting-edge AI labs, stating that the mainstream media's portrayal of his interview as a "disastrous outburst" precisely demonstrates that Karp hit the nail on the head. Sacks points out that true "AI security" in a corporate environment is not abstract "alignment research" or government-led certification systems, but rather the ability to control one's own data, model weights, and computing power—preventing cutting-edge labs from "absorbing" a company's proprietary knowledge and turning it into the next product. He quotes Karp as saying, "They want to own their means of production, not hand them over to others." Sacks cites the conflict between Figma and Anthropic as a prime example: three days before the release of Claude Design, Anthropic's Chief Product Officer was still a member of Figma's board of directors, and Figma's founder stated that Anthropic "hadn't always been honest with them"; subsequently, Figma's stock price plummeted while Anthropic's valuation soared. He further listed products such as Claude Science, Claude Security, Claude Legal, and Claude Code, pointing out that Anthropic consistently targets vertical sectors originally served by companies that relied on its models, following a consistent pattern: "Observe where value is created first, then jump in." Sacks believes that the perception of open-source models as "dangerous" is not true for companies—retaining choice at the model layer and deciding who can use their core strengths is the real bottom line for corporate security. Previously, Palantir partnered with NVIDIA to deploy Nemotron's open AI models in sovereign environments, serving the US government and critical infrastructure customers, helping organizations train and deploy AI locally while maintaining complete control over data and intellectual property. Palanitir CEO Alex Karp recently gave a scathing interview on CNBC's "Squawk Box," criticizing leading AI model companies as "completely wrong" in their approach to selling AI. Karp emphasized that companies are currently dissatisfied with "cutting-edge labs" like OpenAI and Anthropic, believing they only pursue token maximization, wasting companies' time and money while handing over proprietary value and intellectual property. Karp stated that companies are "angry" and will strive to own their own AI production resources rather than relying on third parties. On June 29th, Palantir partnered with Nvidia to deploy Nvidia Nemotron open AI models in a sovereign environment, primarily serving the US government and critical infrastructure.
Palantir CEO: Enterprises are dissatisfied with "cutting-edge labs" like OpenAI and Anthropic, which only pursue token maximization.
According to BlockBeats, on July 2nd, Palantir CEO Alex Karp, in an interview with CNBC's "Squawk Box," strongly criticized leading AI model companies, calling the way AI is sold "completely wrong." Karp emphasized that companies are already dissatisfied with "cutting-edge labs" like OpenAI and Anthropic, believing they only pursue token maximization, wasting companies' time and money while handing over proprietary value and IP. Karp stated that companies are "angry" and will commit to owning their own AI production resources rather than relying on third parties. On June 29th, Palantir partnered with Nvidia to deploy Nvidia Nemotron open AI models in sovereign environments, primarily serving the US government and critical infrastructure customers. The collaborative system reportedly integrates Nvidia AI technology with Palantir's AIP, Foundry, Ontology, and Apollo platforms, helping organizations train, customize, and deploy AI locally while maintaining complete control over data, intellectual property, and models.
MiniMax plans to launch a large-scale model with 2.7 trillion parameters.
Mars Finance reported on July 8th that Rare Earth Technology plans to launch a new generation of large-scale models with 2.7 trillion parameters. (Science and Technology Innovation Board Daily)
Ministry of Human Resources and Social Security: By 2030, the large-scale model of the human resources and social security industry will be mature and complete, and the artificial intelligence application system will be basically sound.
According to Mars Finance, the Ministry of Human Resources and Social Security, the National Development and Reform Commission, the Ministry of Industry and Information Technology, and the National Data Administration recently jointly issued the "Implementation Opinions on Accelerating the Application and Development of 'Artificial Intelligence + Human Resources and Social Security'". A relevant official from the Ministry of Human Resources and Social Security answered reporters' questions regarding the "Implementation Opinions". In terms of promoting the work, a three-step work goal will be achieved within five years. First, building the foundation. Taking this year (2026) as a benchmark, the initial formation of the artificial intelligence application system, standard system, and guarantee system in the human resources and social security sector will be promoted. The infrastructure for "Artificial Intelligence + Human Resources and Social Security" applications will be deployed, a number of high-performance human resources and social security industry large-scale models and intelligent agent applications will be cultivated, and about 20 application scenarios based on human resources and social security industry large-scale models and corresponding high-quality datasets will be created, forming a collaborative development ecosystem of computing power, models, data, and scenario applications. Second, popularization and promotion. By 2027, a number of human resources and social security industry large-scale models and intelligent agents will be widely applied, and about 50 high-value application scenario empowerment paths will be explored, achieving significant results in intelligent development. Third, widespread application. By 2030, high-quality datasets will be effectively supplied, large-scale models for the human resources and social security industry will be mature and complete, and the artificial intelligence application system will be basically sound, forming an innovative landscape where artificial intelligence is widely applied in the human resources and social security sector. (Cailian Press)
Some large-scale AI models in China are 90% cheaper than those in the US; Chinese AI's high cost-effectiveness is capturing the US market.
According to a report by CNBC on July 7th, influenced by the continued price increases of models from leading US AI vendors, Chinese AI large-scale models are rapidly expanding their application scale in US enterprises due to their cost-effectiveness advantage. Industry insiders point out that the performance of some leading open-source and open weighted models in China is currently about 6 to 9 months behind the technology of top-tier US models such as OpenAI and Anthropic, while the price is 60% to 90% lower, and they can cover the vast majority of routine AI tasks, thus gaining popularity among US enterprises. According to statistics from the AI model aggregation platform OpenRouter, since February 8th of this year, the proportion of Chinese AI models used by US enterprises has exceeded 30% weekly, reaching a peak of 46%; while the average proportion in the previous 12 months was 11%. Another industry statistic shows that in the first week of the launch of Zhipu's latest large-scale model GLM 5.2, the daily average number of word calls increased by 27 times and the number of customers increased by 80 times, making it the fastest-deployed model on the platform in 2026; US AI startup Lindy has significantly reduced costs after switching all its AI business to DeepSeek models, and expects to save millions of dollars within a few months. (CCTV Finance)
Large-scale model stocks in Hong Kong extended their gains, with MINIMAX and Zhipu rising over 16%.
Mars Finance reported on July 8th that MINIMAX-W (00100.HK) rose 17%, and Zhipu (02513.HK) rose 16%. In terms of news, Zhipu, a leading Hong Kong-listed large-scale model manufacturer, saw its first share lock-up period expire today, with several core institutional investors clearly choosing to continue their investment. (Science and Technology Treasure Broadcast)