置身于民营经济活跃、制造业发达的浙江，面对前所未有的时代机遇，一批浙企已率先探路，推动 浙江成为这场变革的前沿阵地。 然而，记者调查发现，先行者也面临着"先到山顶先缺氧"的考验：市场认知偏差、核心消费人群触 达难、品牌研发投入回报周期长等问题接踵而至。当传统的供给能力遭遇需求升级，当技术创新碰撞消 费惯性，浙企能否率先探索出制造业与消费升级协同共进的新路，实现从"做得出"到"卖得好"的跃迁？ 原标题：内需市场持续扩容提质，浙企迎来时代机遇 新消费时代，谁能领跑 眼下，一场从"制造大国"向"消费大国"的跃升已拉开帷幕—— 去年底，中央经济工作会议将"全方位扩大国内需求"列为九项重点任务之首；今年3月，政策部署 持续加码，中共中央办公厅、国务院办公厅印发《提振消费专项行动方案》强调各地区各部门要把"提 振消费"摆到更加突出的位置；6月，国务院总理李强在夏季达沃斯论坛上提出，推动中国在"制造大 国"的坚实基础上成长为超大体量的"消费大国"。 这是关乎国家经济结构的深层变革，更事关亿万市场主体的洗牌与重塑。 现状：机遇与困境交织 连续15年稳坐全球制造业"头把交椅"的中国正在迈向消费大国—— 看总量，中国已是全球第二 ...

Group 1 - Meta has made significant investments in AI, including a $10 billion acquisition of a 49% stake in Scale AI and hiring efforts, with a capital expenditure intensity of 35% of revenue [1] - Major US tech companies, including Microsoft, Google, and Amazon, are also heavily investing in AI, with a combined forecasted capital expenditure of $400 billion in AI infrastructure this year [1] - The AI revenue growth in the US is accelerating, with OpenAI and Anthropic projected to reach a combined annual revenue of $290 billion by the end of this year, potentially increasing to $600-1,000 billion by 2026 [2][4][5] Group 2 - In contrast, China's AI capital expenditure is expected to remain below 500 billion RMB by 2025, with a lack of clear commercial logic to support large-scale investments [2][3] - The commercialization of AI in China has not found a suitable path, with over 70% of revenue from companies like Keling AI coming from overseas markets [2][10] - The domestic AI industry faces structural barriers, with a significant gap in return on capital expenditure compared to the US, leading to concerns about the sustainability of growth [3][8] Group 3 - The US AI market is characterized by a surge in small startups outperforming larger companies, while China's market is dominated by major players with limited innovation from smaller firms [6][9] - Despite technological advancements, China's AI applications are struggling to generate significant revenue, with a projected growth of only 6.4% in 2024 [8][9] - The shift from "entry" to "interface" thinking is crucial for the future of AI commercialization in China, as the industry must adapt to a results-driven economy rather than relying on traffic control [12][13][14]