科八条落地将满周年！科创人工智能ETF华夏(589010)近5日“吸金”近800万元

Group 1 - The core viewpoint of the news highlights the performance of the Huaxia Sci-Tech AI ETF (589010), which has seen a decline of 0.81% as of 1:29 PM today, with notable declines in holdings such as Yaxin Security (-4.01%), Cambricon (-3.69%), and Daotong Technology (-3.36%) [1] - The Huaxia Sci-Tech AI ETF has experienced a net inflow of 1.98 million yuan recently, accumulating a total of 7.97 million yuan over the past five trading days. The ETF tracked a net inflow of 298 million yuan into the underlying Sci-Tech AI index last week, indicating a clear trend of capital allocation despite market fluctuations [1] - The "Eight Articles of Sci-Tech Board" released a year ago has led to nearly 500 companies launching equity incentive plans, 371 companies distributing dividends or stock transfers totaling 38.9 billion yuan, and 175 companies announcing share repurchase plans amounting to 7.3 billion yuan. This policy synergy supports corporate operational development [1] Group 2 - CITIC Securities points out that the shift in AI computing power consumption from training to inference is generating significant increases in computing power. Attention should be paid to new technologies and incremental changes in overseas computing power, particularly in liquid cooling, PCB, and copper connections [2] - Under the trend of domestic self-control, domestic power supplies, copper connections, and liquid cooling are becoming key areas. Major cloud service providers are expected to consume over 50 trillion tokens in computing power in the second half of the year, making companies with leading shipment volumes, ecosystems, and product capabilities worth monitoring [2] - The Huaxia Sci-Tech AI ETF closely tracks the Shanghai Sci-Tech Board AI Index, covering high-quality enterprises across the entire industry chain, benefiting from high R&D investment and policy support, with a 20% fluctuation range and small-cap elasticity aiding in capturing the "singularity moment" of the AI industry [2]