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Tom Lee: Nvidia's valuation is still relatively low, and the weakness in some AI stocks may be due to funds shifting towards Nvidia

BitMine Chairman Tom Lee stated on CNBC that after Nvidia announced strong performance, its stock price rose, breaking the previous trend where positive earnings reports struggled to drive stock prices, indicating that investors still value the company's fundamentals. Software stocks like Salesforce, CrowdStrike, and Okta also strengthened, reflecting a positive market response to downstream AI transactions, with an overall healthy market reaction.Regarding the weak performance of AI-related stocks such as Meta, Amazon, Alphabet, AMD, and Micron, Tom Lee believes that some investors may have previously underweighted Nvidia and might need to sell other tech stocks to raise funds for increasing their Nvidia holdings. He pointed out that Nvidia's earnings expectations have been significantly raised, but the stock price has not fully caught up, and the price-to-earnings ratio is still contracting, with the current valuation remaining relatively low.Tom Lee also mentioned that data center construction is gradually becoming a political issue in the U.S. midterm elections. Even some Republican-led states and states supporting data center development are beginning to consider pausing related projects, which may be one reason for the recent poor performance of AI infrastructure-related stocks, with more funds shifting towards downstream AI targets.

first_img Samsung develops NVIDIA's custom NVHBM to advance 8-layer high-speed HBM4E

According to reports from Seoul Economic Daily, Samsung Electronics is developing HBM4E (seventh generation) 8-layer products that meet NVIDIA's requirements, aiming to secure its position as a core partner in the supply of customized high-bandwidth memory NVHBM. This product reduces the stacking height compared to the originally planned 12-layer and 16-layer designs. The speed specifications proposed by NVIDIA are 17-18Gbps, which is about 20% higher than the speed of Samsung's initial HBM4E samples (14.4Gbps), and will be used for NVIDIA's publicly disclosed NVLink optimized specifications for NVHBM.The use of 8 layers, contrary to the previous logic of increasing capacity by adding more stacking layers in HBM, can reduce the difficulty of post-processing and yield pressure, which is beneficial for expanding supply and is seen as NVIDIA's strategy to alleviate memory shortages. NVHBM is expected to be applied starting with the next-generation AI GPU "Rubin Ultra," which is set to launch next year. This GPU will expand the interconnection scale between GPUs from a maximum of 72 to 576, enhancing overall computing power through hundreds of GPUs equipped with faster HBM.In the customized HBM market, Samsung is more competitive compared to SK Hynix and Micron, as NVHBM requires DRAM and the production capabilities of logic chip-based bare die designs, which Samsung can integrate. Industry insiders say that Samsung has verified the highest speed levels in HBM4, which can provide an advantage in speed competition.

first_img Nvidia suspends part of its revenue-sharing financing arrangements with AI cloud companies

According to the Wall Street Journal, Nvidia has suspended some transactions in its new financing plan. This plan aims to provide credit support to AI cloud companies in exchange for revenue sharing. Insiders say that the chip giant withdrew from the related arrangements last week but may adjust the plan in the future or incorporate it into other projects.A Nvidia spokesperson stated that the new business model aimed at the rapidly growing AI ecosystem and open computing power access is still progressing and continues to evolve due to strong demand. The plan was announced less than two months ago, intending to support the financing needs of small AI cloud companies: if customers cannot sell computing power, Nvidia can lease back the relevant computing power, acting as a guarantee buyer, thereby facilitating companies in raising funds to purchase Nvidia AI chips; Nvidia would then share cloud revenue generated by customers based on its chips, in addition to hardware sales.Nvidia stated in this week's earnings call that this model is expected to contribute billions of dollars in revenue in the medium to long term. However, recent investor scrutiny regarding its capital flow back to the AI ecosystem has increased, raising concerns that so-called circular transactions may inflate demand. Reports indicate that some employees had expressed antitrust concerns to customers; in the early stages of the plan, Nvidia also faced dissatisfaction from some potential partners due to attempts to limit chip rental targets, preferring to distribute to multiple small customers rather than a single large customer, and requiring a 50% revenue share after reaching a certain threshold.
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