Report: Fixed computing power masks the true capabilities of AI; the evolutionary speed of cutting-edge intelligent agents is underestimated by 60%.
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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.
CITIC Securities: Significant fluctuations will not alter the AI supercycle; emphasize the importance of domestic computing power as a "Plan B".
According to Mars Finance, CITIC Securities points out that news of Meta's plan to lease out some of its computing power has once again triggered market concerns about computing power oversupply. This, coupled with concerns about cloud vendors' cash flow pressures, the continued rise in upstream prices, the slowdown in Capex growth, and overcrowding in AI transactions in recent months, is the main reason for the significant volatility in tech stocks. In the short term, Meta's move is primarily aimed at revitalizing its existing, outdated computing power assets. Considering its continued development of advanced models and investment in next-generation computing hardware, leasing out computing power is not contradictory to further increasing its investment in computing power. Furthermore, since computing power rental fees have continued to rise recently, concerns about computing power oversupply are unfounded. This round of tech stock adjustments is more of a deleveraging and rebalancing process in the recent global liquidity tightening environment, rather than a reversal of the AI industry trend. For the medium to long term, it is crucial to pay close attention to whether the next few months will see a similar breakthrough in AI capabilities as seen with OpenClaw and Coding Agent at the beginning of the year. In addition, it has been observed that after overseas AI assets entered a phase of high crowding, high correlation, and high volatility, international funds are beginning to seek differentiated sources of return. Domestic computing power with differentiated value, dubbed "Plan B," remains resilient and is expected to attract foreign investment. With the earnings season approaching, we recommend focusing on sub-sectors with high earnings certainty and reasonable valuations: In terms of growth prospects, we recommend domestic FAB (Featured Adhesives and Materials) and equipment sectors with positive narratives, as well as the optical communication sector with relatively low valuations; in the price increase chain, segments with high AI exposure and those that have already experienced price increases have a higher probability of realizing their earnings gains, such as memory and upstream PCB industries. (Cailian Press)
SemiAnalysis: Meta will accelerate, rather than slow down, its computing power procurement; it is in talks with Anthropic to build its own AI model service platform.
According to BlockBeats, on July 3rd, SemiAnalysis stated in its latest report that after news broke that Meta might become a new Neocloud, the market's initial reaction was to sell off computing power cloud companies like CoreWeave and Nebius, and to renewed concerns about "AI computing power oversupply." However, the firm's assessment is the opposite: this concern may be wrong. Meta's data center and computing power procurement will not slow down, but rather continue to accelerate. The article mentions that in the first half of this year alone, Meta has already signed contracts for over 5GW of capacity in the cloud services and managed data center sectors, and this does not include its accelerating self-built projects. SemiAnalysis states that Meta is in final negotiations with Anthropic, hoping to obtain access to Claude private instances. If this comes to fruition, the significance goes beyond "Meta buying more computing power"; it suggests that Meta may be building its own AI model service platform. This model is somewhat similar to AWS's Bedrock, Microsoft's Foundry, and Google's Vertex. Meta can initially use Claude internally, or it can package the model capabilities as a token-as-a-service to provide services externally in the future. In the short term, it might use its own models externally and Anthropic models internally; in the long term, Meta might even incorporate Anthropic and OpenAI models into its external service system. SemiAnalysis states that the underlying logic is that Meta has computing power, advertisers, social network distribution capabilities, and consumer-end entry points. If it can combine cutting-edge models, intelligent agents, and sales and marketing SaaS, it will not just be a company that buys GPUs, but will be moving towards the upper layers of AI application and model distribution.
CITIC Securities: The main theme of domestic computing power is clear; leading companies' performance is expected to accelerate.
According to a research report by CITIC Securities, as reported by Mars Finance, the capabilities of domestic computing power systems have evolved from inference to training. With the official release of DeepSeek V4 in mid-July, a "peak-valley pricing" mechanism will be introduced, doubling the price of API calls during peak periods, further intensifying the supply constraints of domestic computing power. We believe that the clarity of domestic computing power orders has significantly improved at this stage, and design companies with priority in customer order and capacity allocation are expected to benefit first. We remain optimistic about the domestic computing power industry chain, anticipating significant growth opportunities for everything from scarce advanced process capabilities to a thriving design sector and supernodes. Meanwhile, advanced processes, advanced packaging, advanced storage, and related supply chains are expected to experience strong growth momentum. (Cailian Press)
Meta's rental of computing power is similar to using existing resources to fund new ones, rather than ceasing the pursuit of high-end computing power.
According to Mars Finance, Meta is planning to launch a cloud computing business that leases computing power: one approach is to open up the model capabilities deployed on its own AI infrastructure to external customers, and the other is to lease out the more fundamental "raw computing power." However, the current situation seems more like Meta is using its existing, older computing power for cash flow recovery, rather than ceasing its pursuit of high-end computing power. In mid-to-late June, Meta was reported to have signed an agreement with Crusoe to acquire a total of approximately 1.6GW of AI computing capacity from two data centers in Texas and Missouri. Meanwhile, Meta raised its full-year capital expenditure guidance for Q1 2026 to $125-145 billion. Looking at these two events together, it seems more like a reallocation of resources across different generations and for different purposes: continuing to buy new GPUs to train cutting-edge models, but leasing out a portion of older GPUs (such as the H-series) used for high-traffic inference products and hosting external models, while not necessarily slowing down the purchase of the most scarce high-end GPUs. (Cailian Press)
Industrial Securities: The news regarding Meta's external leasing and sales of computing power should not be interpreted overly pessimistically as a sign of computing power surplus.
According to Mars Finance, on Wednesday, news that Meta plans to sell its surplus AI computing power triggered a sharp correction in global AI hardware and high-flying technology stocks. Xingye Securities believes that the news regarding Meta's external leasing and sale of computing power should not be interpreted overly pessimistically as a surplus of computing power/a comprehensive slowdown in Capex, because (1) this is not new news; there were related reports in May of this year; (2) Meta is a special case among hyperscalers; its toC-oriented business means its AI monetization capabilities mainly rely on advertising, and its exploration of cloud business can improve shareholder returns and cash flow; (3) Meta still has a computing power gap; this week, it was just reported that Google restricted its access and Meta signed an agreement with Crusoe; (4) hardware demand comes from inference, not from inflation on the training side. (Cailian Press)