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Viewpoint: After Jensen Huang's absence, customers accelerate the evaluation of AMD and Google chips

Semiconductor analyst Jukan forwarded a report from The Information and commented that an executive from a cloud provider purchasing NVIDIA chips stated that the uncertainty surrounding Jensen Huang is prompting the company to seriously evaluate other chip options, including products from Google and AMD. The executive mentioned that the company had previously considered diversifying to reduce dependence on NVIDIA hardware but refrained due to concerns about offending Jensen Huang; now there is greater worry that his absence could affect the quality and roadmap of future generations of NVIDIA chips, as he plays a crucial role in the company's technology and customer relationships.Jukan pointed out that preventing major customers from further diversifying to other chip manufacturers' AI servers will be one of the key challenges faced by interim CEO Colette Kress and her future official successor. Several customers also indicated that, at least in the short term, NVIDIA chips are still expected to be in short supply, and changes in the management team will not alter the market's perception of its AI server chips as "industry best." Additionally, Kress will need to manage the company's relationships in Washington, where Jensen Huang previously had a close relationship with Trump and actively promoted adjustments to export restrictions to China, but at the same time, he also made enemies in Washington, with some describing his style as combative and feeling pressured. Jukan believes that the uncertainty in leadership is beginning to loosen NVIDIA's lock-in effect on the customer side.

first_img Reuters: China's over 3.2 billion USD AI data center project still designated to use restricted NVIDIA chips

According to a Reuters survey, Chinese developers are still planning AI data centers around Nvidia processors that are subject to U.S. export controls, with a total project value exceeding 23 billion yuan (approximately 3.2 billion USD). The agency compiled over 150 procurement announcements, investment plans, and corporate records, many of which explicitly list H100, H200, or H800 chips. The 3.2 billion USD is the overall investment amount for the projects, covering infrastructure such as construction and power, and the documents did not prove that all related chips have been obtained, nor did they show any violations.A proposed computing center in Fujian is valued at 6.2 billion yuan (approximately 873 million USD), with the official investment list specifying H100 servers, which are still seeking financing; a state-owned engineering group in Shaanxi has won a contract related to a 3 billion yuan project, with documents listing H100 and H200; a 2.26 billion yuan project in Jilin plans to combine Nvidia hardware with domestic processors; a proposed project in Inner Mongolia specifies 625 H200 servers, while Wuxi claims that an H800 cluster has been put into operation in March 2025.Since 2022, the U.S. has restricted the export of advanced AI chips to China, and in January 2026, the Department of Commerce changed the export application for H200 to case-by-case approval, with sales still requiring a license, and restrictions on H100 being even stricter. Reuters cited IDC data stating that in the first half of 2026, Nvidia accounted for 34% of AI accelerator shipments in China, while Huawei accounted for 28%. Chinese developer Z.AI has released an image generation model fully trained on Huawei chips. These records show that Nvidia is still deeply embedded in China's AI infrastructure planning, putting pressure on U.S. officials facing congressional scrutiny.

NVIDIA's stock price rose, and the demand for AI chips was not affected by the Democratic Party's victory

Despite the possibility that the Democratic Party may push for stricter restrictions on data center construction after winning the election, Nvidia's stock price still rose on Wednesday. This is because the positive performance reported by major companies in the chip industry indicates that market concerns about delays in data center construction have not immediately affected Nvidia and other hardware companies.Customers are still rushing to stockpile artificial intelligence hardware, even though it is currently uncertain whether there will be suitable locations to install these devices in the future. The defeat of Republican governors in Texas and Ohio in the election means that the construction of artificial intelligence infrastructure will face stricter scrutiny.Mark Haefele, Chief Investment Officer at UBS Global Wealth Management, wrote in a research report: "Increased oversight from Congress does not necessarily hinder the artificial intelligence investment cycle. Comprehensive federal-level restrictions will face legislative and presidential power constraints, while state and local regulations will still have a greater impact on the timing and location of data center construction." If Democratic politicians indeed push for stringent measures to limit the construction of artificial intelligence data centers, Nvidia will face greater challenges in the future.However, the market is currently more focused on signs that chip demand remains strong after the stock's recent weak performance.

CITIC Securities Bao Chengchao: The valuation of domestic large-cap blue chips is relatively low, and the recovery space for domestic demand manufacturing is the most ample

According to reports from People's Financial News, Bao Chengchao, the chief strategist of the research department at CITIC Securities, pointed out in his latest insights that, compared to the global market, the valuation of domestic large-cap blue-chip stocks is at a relatively low level. The A-shares market is the only one among the U.S., Japan, South Korea, and A-shares where the AI relative to non-AI valuation premium is still higher than the historical mean. As of October 22, 2026, the PE ratio of A-shares for AI/non-AI is 4.4 times, which is at the 82nd percentile since 2016, while the same indicator for the U.S., Japan, and South Korea has fallen to the 1%, 17%, and 24% percentiles, respectively.The AI premium in overseas markets has largely been absorbed by the rise in non-AI valuations. The PE ratios for non-AI non-financial leaders in the U.S. and Japan are 33.5 times and 23.0 times, respectively, which are at the 98% and 95% percentiles in history. The overall PE ratio for A-shares related to domestic demand and manufacturing non-AI blue-chip stocks is only 15.6 times, which is at the 21% percentile in history. Bao Chengchao believes that this misalignment indicates that the large-cap blue-chip stocks related to domestic demand and manufacturing in A-shares have relatively ample room for valuation recovery.Bao Chengchao also stated that the realization of this space requires coordination with macro conditions. On the overseas front, if the AI spending cycle gradually approaches a downward turning point, long-term U.S. Treasury rates may also decline, leading to marginal improvements in the demand and valuation environment for global non-AI sectors. Domestically, the clear alignment of fiscal and monetary policies places a focus on expanding domestic demand, with increasing signals of marginal improvement in core indicators of domestic demand. If the decline in overseas interest rates and the recovery of the domestic economy create a phase resonance, the profit expectations and valuation constraints of large-cap blue-chip stocks in A-shares are expected to recover simultaneously.

first_img Delphi Digital: Electricity is a greater constraint on AI computing power deployment than chips

On October 29, the cryptocurrency research institution Delphi Digital released a report titled "The AI Boom Has a Power Problem," authored by Accelxr. The report states that deployable AI computing power depends on chip supply, as well as sites that are powered, cooled, and connected to the grid. Electricity is harder to supplement in the short term than chips, as chip production capacity can expand quarterly, while new power generation and transmission take years.The report cites data indicating that the PJM capacity auction has cleared at the price cap for three consecutive times, with the last two still falling short of reliability targets by 6.6 to 6.8 GW, marking the first time such a gap has occurred in the history of this auction. The scale of large load queues in Texas ERCOT increased from 63 GW at the end of 2024 to 474 GW in June, with about 90% being data centers; the governor requested an audit of the data centers in the queue in August, and ERCOT subsequently suspended power approval for data centers and cryptocurrency miners of 75 MW and above, including 17 projects that had passed stability studies.The report also states that U.S. data centers are expected to account for about 4.7% of the nation's electricity consumption in 2024, with LBNL predicting an increase to 9.5% to 15.3% by 2030, and EPRI estimating a maximum of 17%. In a 1 GW facility, chip depreciation is about $2.8 billion to $3.3 billion per year, equivalent to about $8 million per day. SemiAnalysis predicts that by 2028, the U.S. will have over 40 GW of data center capacity utilizing behind-the-meter power sources; the delivery cycle for large gas turbines is about five years, with GE Vernova, Siemens Energy, and Mitsubishi Heavy Industries forming an oligopoly. Wood Mackenzie expects gas turbine prices to reach $600 per kilowatt by the end of 2027, nearly three times the level of 2019.
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