这两年，AI（人工智能）人才竞争进入白热化阶段，对于头部大厂来说，这不再是一场普通的"抢人大 战"，而是一场关乎未来生存与发展的战略军备竞赛。 9月16日，脉脉最新发布的《2025年AI人才流动报告》（以下简称报告）显示，2025年1~7月，AI领域 人才市场供需两旺，AI新发岗位量同比增长超10倍，简历投递量也暴涨了11倍。"算法"相关人才持续紧 缺，其中"搜索算法"人才紧缺度最高，5岗争2人。非技术岗数量同比增长7.7倍。 值得一提的是，不同规模企业的AI化进程显著加速，新发岗位AI渗透率明显提升。2025年1~7月，新经 济行业新发岗位AI渗透率超过10%，较去年同期提升10倍以上，且随企业规模扩大而提升。报告显 示，"新发岗位AI渗透率"为新发AI相关岗位量在所有新发岗位中的占比，是衡量企业对AI投入的重要 指标。 搜索算法"5岗争2人" 值得一提的是，从新发AI岗位量来看，字节跳动招聘指数29.83位列榜首，小红书18.32居第二，阿里巴 巴12.25位列第三。小鹏汽车、自变量机器人、黑芝麻（000716）智能等垂直企业同样上榜。 商汤科技首席人力资源官张春娟在报告中表示，全球AI人才需求的陡峭上升 ...

Core Viewpoint - The rise of AI technology is creating both risks and opportunities in the job market, particularly in the backend development sector, where traditional roles are declining while AI-related positions are surging [1][2]. Group 1: Job Market Trends - Traditional CRUD development positions have decreased by 30%, while 80% of new technical roles require AI capabilities such as large model development and RAG architecture [2]. - The average annual salary for AI developers exceeds 400,000, compared to 200,000 for traditional frontend and backend roles [2]. - AI can now independently perform tasks such as code generation and debugging, leading to a significant shift in job demand [2]. Group 2: AI Job Opportunities - The AI competition has entered a phase of "hundreds of billions in investment," resulting in a substantial increase in AI and algorithm positions, with salaries rising by 50% compared to previous years [2]. - Many algorithm positions have starting salaries reaching 25,000 to 30,000, which is already the ceiling for many frontend and backend roles [2]. Group 3: Training and Education - A recommended "Algorithm Engineer Training Program" has been developed by top technical experts, focusing on recommendation algorithms and large model technologies, with a job guarantee of at least 290,000; otherwise, a full refund is provided [3][22]. - The curriculum covers a comprehensive range of big data algorithms and practical applications, including environment setup, data mining algorithms, machine learning, and deep learning [5][26]. Group 4: Project-Based Learning - The training program emphasizes real-world projects, allowing students to learn through practical application, covering various big data components and advanced algorithms [8][26]. - Projects include building user profiles, recall systems, and recommendation systems, utilizing tools like Hadoop, Hive, and Spark [12][14][24]. Group 5: Employment Success Stories - The program has seen a 90% success rate in job placements, with the highest reported salary reaching 75,000 [31]. - Alumni have successfully transitioned to algorithm roles with significant salary increases, such as a 68% rise from 250,000 to 420,000 [34].

Group 1 - Demand is the fundamental driving force behind technological innovation, and the urgency and scale of demand determine the speed and level of innovation [1][3] - Historical examples illustrate that significant innovations often arise from pressing needs, such as the development of the steam engine and the internet, which were driven by specific demands [3] - The integration of technology with practical, widespread needs is essential for its successful implementation and growth [3] Group 2 - Innovation involves trial and error, which inherently requires costs; higher trial and error costs can slow technological progress [4][5] - The digital transformation of manufacturing industries faces high trial and error costs due to stringent requirements for product quality and production stability [6] - Sectors with lower trial and error costs, such as entertainment and digital services, can innovate more rapidly and serve as testing grounds for new technologies [6] Group 3 - Technological innovation is a gradual process rather than a sudden breakthrough, often built upon previous advancements and requiring long-term iteration [7][8] - Major inventions, like the steam engine and computers, have undergone extensive improvements over time rather than appearing fully formed [8][10] - The perception of innovation as revolutionary often overlooks the incremental efforts that lead to significant breakthroughs [10] Group 4 - Resource-rich environments may hinder innovation due to a phenomenon known as the "resource curse," while resource-scarce regions often exhibit stronger innovation capabilities [12][13] - Large organizations may struggle with innovation due to organizational inertia and path dependency, suggesting that smaller, more agile teams may be more successful in driving innovation [13][14] Group 5 - Innovation thrives in diverse environments where different ideas and perspectives can intersect, akin to "cross-pollination" [16][17] - The movement of talent across regions is a key indicator of innovation potential, as diverse backgrounds contribute to new ideas and solutions [17] Group 6 - While youth has historically been associated with innovation, the average age of significant innovators has been rising, with many breakthroughs occurring in the 30-50 age range [18][21] - Despite the trend of older innovators, the urgency to innovate remains, emphasizing the importance of timely action [21] Group 7 - Innovations often emerge simultaneously from different individuals or groups, reflecting the maturity of social conditions rather than individual genius [23][24] - Predictions about the timing and impact of innovations can be notoriously inaccurate, highlighting the unpredictable nature of technological advancement [24][26]

Group 1 - The core point of the article is that Elon Musk announced that the recommendation algorithm of the X platform is being replaced by a lightweight version of Grok [1] Group 2 - The transition to Grok's lightweight version indicates a strategic shift in the platform's approach to content recommendation [1] - This change may impact user engagement and content discovery on the X platform [1] - The move reflects ongoing efforts to enhance the platform's functionality and user experience [1]

技术进步日新月异，但人类的整活能力总在领先一步。 2025年至今简中互联网最火的流行语，一是"国运论"，这篇透过deepseek看未来的雄文，后来被证实是AI生 成的内容； 二是"手机爹又把我干哪来了"，表达一种下滑刷到陌生内容的诧异感，延伸出来还有大量表情包，甚至短视 频滤镜。 每一条火爆全网的内容下，都有一群仿佛走错房间的网友，拘谨又嚣张地带着"手机爹"的迷茫表情包，光速 加入互动：上一秒还在看中科院院士讲解黑洞合并，下一秒就被甲亢哥带着欣赏广场舞；刚看了两集《450 分钟深度解读红楼梦》，转头就迷失在修驴蹄子的白噪音中。 硅基大脑能俯仰古今畅聊国运，但将"手机"和"爹"排列组合到一起，是只有碳基大脑能整出的绝活。这背 后，是技术与人的关系正在悄然改变。 当快速更迭的推荐算法，向我们展现出一个更多面的世界，大部分人都愿意放下刻板成见，借助代码踏进 未曾想象过的广阔天地。 贝索斯在后来给股东的信中写道：" 我们的愿景是，让世界上每一本书，无论语言如何，都能在60秒内获取 [1]。 " 这位前世界首富的出发点显然没那么简单。对电商平台来说，图书是不可多得的标品品类，电子书更完美 解决了唯一不足的库存负担。 但 ...