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first_img Driven by the surge in AI demand, Samsung's Q2 operating profit is expected to skyrocket 18 times

According to a report by Reuters, benefiting from the ongoing tight supply of memory triggered by the rapid development of AI and a significant increase in chip prices, Samsung Electronics' operating profit for the second quarter of this year is expected to surge approximately 18 times year-on-year, reaching about 86 trillion won (approximately 56.35 billion USD). This will mark the company's third consecutive quarter of setting a historical high for operating profit. Analysts point out that, in addition to high bandwidth memory (HBM), the popularity of complex applications such as Agentic AI has also greatly driven strong demand for traditional DRAM and NAND products, and it is expected that the supply-demand imbalance in the memory market will last at least until next year.Despite the strong performance expectations, analysts warn that due to Samsung's previous agreement to allocate 10.5% of the operating profit from its semiconductor division as special bonuses for employees to avoid strikes, the timing of this substantial reserve may cause the actual reported profit for the second quarter to be slightly lower than market expectations. Additionally, affected by the rising costs of memory components, Samsung's mobile business is facing severe pressure on profit margins, and the industry expects that it may need to further raise prices for terminal products such as smartphones in the second half of the year to alleviate cost pressures.

EthLabs released the Week 2 update report, focusing on advancing Ethereum interoperability, PropAMMs, and financing progress

EthLabs founder Barnabé Monnot (barnabé.eth) released the Week 2 update, summarizing the team's latest progress in the launch and financing phase as well as the direction of ecological discussions. In terms of interoperability (Interop), the team stated that they are enhancing confidence in asynchronous interoperability based on zero-knowledge proofs (zk), believing this will help build safer cross-chain bridges and improve the native distribution capabilities of assets in Ethereum's multi-layer network.Currently, some cross-chain paths still experience delays, especially in the L2 → L1 direction; in this context, the intents mechanism can serve as a transitional solution, while sufficient L1 liquidity also helps match cross-chain executors (solvers). At the same time, the L1 → L2 path is expected to significantly reduce confirmation delays through the Fast Confirmation Rule (FCR), with clients already beginning to integrate this mechanism.In terms of ecological discussions, PropAMMs (Proposal-based AMM) have become a recent focus for multiple teams and researchers, with the core being the potential optimization space between L1 execution efficiency and transaction building (block building). Meanwhile, ENS is emphasized as a key infrastructure for Ethereum, and the team is continuously communicating with relevant stakeholders to advance its development direction. Regarding team building, Ethlabs has currently received over 300 applications, processed about 20%, with a short-term goal of expanding to around 10 people and a mid-term goal of expanding to about 20 people, focusing on recruiting talents with engineering capabilities and domain expertise.In terms of financing, Ethlabs stated that the current financing is nearing completion and has received early support from BitMNR, Sharplink, and Ethereum Joseph, planning to bring in 1-2 core investors before entering the next phase.

Goldman Sachs released a report on China's AI computing power, predicting that by 2026, the market share of domestic chips will exceed 50%

According to the Goldman Sachs report on "China's AI Computing Power" disclosed by P Equity Research, China is accelerating the construction of a national computing power network, with related infrastructure projects expected to attract 7 trillion yuan in investment by 2026. In the next five years, investment in data centers is projected to reach about 2 trillion yuan. Currently, funds and technology are being massively transferred to western computing power hubs, while data centers in first-tier cities are transforming to focus on ultra-low latency computing, edge nodes, and AI inference. Although GW-level clusters with over 100,000 chips remain scarce domestically, in typical GW-level computing power parks, workloads are primarily composed of inference, which accounts for more than half, as well as training and full-stack R&D.The report predicts that by 2026, the market share of domestically produced AI acceleration chips is expected to exceed 50%. Among them, Huawei and Alibaba's Pingtouge lead the domestic camp with shares of 20% and 7%, respectively, but Nvidia currently maintains overall market dominance with a 55% share. In terms of cost and performance, domestic chips have capital expenditures on IT power consumption that are 40% to 50% lower than imported chips, but due to performance gaps, their capital expenditures per unit of computing power are 2 to 4 times that of imported chips, and the computing power generated per unit of power consumption is only 10% to 30% of that of imported chips. Additionally, the daily average token output of Huawei's 910B/910C servers is about one-sixth to one-third of that of Nvidia's H800, resulting in significantly lower API profit margins based on that hardware compared to peers using Nvidia hardware.
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