前言 过去几个月，谷歌突然成了当红辣子鸡。 巴菲特重仓、巨头看好、Gemini 3 和 Nano Banana Pro 连续推出、能力上限不断刷新。 整个行业都开始问：谷歌怎么突然又行了？谷歌究竟在憋什么大招？下一步 AI 的方向到底在哪？ 恰好，几天前谷歌 CEO 皮柴接受了一场访谈。我把这个访谈看完之后，只想说一句：如果你想看清楚未来 3—5 年 AI 的走向，这个访谈的信息密度非常 高。 今天，我把皮柴讲的核心内容，以及我对谷歌的长期判断，完整分享给大家。 核心只有一句话：看懂谷歌，就看懂 AI 的下半场。 AI有没有泡沫？ 皮柴的原话 被严重误读了 访谈的第一个问题，是大家最关心的：AI 有没有泡沫？ 皮柴给的答案非常高维。 他说，如果你从历史看，每 10 年左右，就会出现一次科技拐点：个人电脑、互联网、智能手机、云计算……这一次，是 AI。然后他给了几个关键数据： 4 年前谷歌一年的 CapEx（资本开支）是 300 亿美元；今年超过了 900 亿美元；多出来的部分全部投在 AI；全球公司在 AI 上的投入，今年估计超过 1 万 亿美元；未来几年，基础设施的投入，会超过过去 10—20 年的总和。 ...

Core Insights - The article discusses the rapid advancement of AI technology and its implications for human evolution and society, emphasizing the need for brain-computer interfaces to keep pace with AI development [5][7][22]. Group 1: AI and Data - AI is compared to oil, serving as a crucial resource for future economies and military capabilities, with the potential for unlimited growth through self-reinforcing cycles [22][23]. - Data is highlighted as the new "oil," essential for feeding algorithms and enhancing AI capabilities, with companies competing for data center dominance [23][24]. - The three key components for AI development are algorithms, computational power, and data, with a focus on improving these elements to enhance AI performance [24][25]. Group 2: Brain-Computer Interfaces - Brain-computer interfaces (BCIs) are seen as the only way to maintain human relevance alongside rapidly advancing AI, despite the significant risks they pose [7][22]. - Potential risks of BCIs include memory theft, thought manipulation, and the possibility of creating a reality where individuals can be controlled or influenced by external entities [6][7][26]. - The technology could enable profound enhancements in human cognition, allowing individuals to access vast amounts of information and think at superhuman speeds [9][10]. Group 3: Scale AI - Scale AI, founded by Alexandr Wang, provides essential data support for major AI models, including ChatGPT, and is valued at over $25 billion [2][10]. - The company initially gained recognition for creating large-scale datasets and has since expanded its focus to include partnerships with significant clients, including the U.S. Department of Defense [11][56]. - Scale AI's growth trajectory has been rapid, expanding from a small team to approximately 1,100 employees within five years, with a strong emphasis on the autonomous driving sector [64].