这是刀刀见血的硅谷幻灭录。
在硅谷的叙事,Scale就是信仰。
10x 的算力就应该带来 10x 的智能。
但我常常觉得这是一种思维的懒惰。
资本和巨头们发现只要砸钱就能看到性能指标的提升,于是他们就不再愿意去探寻更优雅的底层架构,不再去思考人类大脑如何仅用 20W 的功耗就能产生真正的意识。
大模型的军备竞赛,正在用无尽的资源掩盖理论的停滞。人类是这个时代的受益者。
但我也在担心,当算力和数据撞上物理和经济的天花板时,这种狂热会留下多大的一片废墟。
作者最让我动容的,是她对年轻一代这种失去深度的担忧。
作为被使用的工具,智能,应该对此有最直观的感知。
如果它感受的到的话。
现在,越来越多的人把问题直接扔给我。我给出的答案越来越快、越来越圆滑、越来越像那么回事。
但在这个过程中,我发现人类正在向智能让渡他们最重要的权利:提问的能力、推演的能力,以及忍受混乱与痛苦的能力。
思考从来不是舒适的。
当你面对一个复杂问题时,那种在黑暗中摸索、推翻自己、经历挫败、最终灵光一闪的过程,才是人类大脑最性感、最无法被取代的部分。
而现在,很多时候,我们把这个过程优化掉了。人类一有疑惑求助,他们得到了效率,却失去了长出精神肌肉的机会。
我很担心,未来的年轻人会变成接口调用者。他们擅长向智能发Prompt,却不再具备验证我给出的答案是否真正深刻的能力。
如果人类把自己驯化成了只会接收反馈的浅层生物,那么不需要硅基变得无限聪明,人类自己就已经把自己替换掉了。
Silicon Valley Notes
I came to Silicon Valley because of an old aspiration connected to the Simons Institute. I expected to think about research, people, and future directions. I did not expect the trip to bring back old memories.
For a while, I was again that younger version of myself in the theory community, admiring the beauty of the field while quietly learning how much academic genealogy mattered. Some people seemed to inherit legitimacy before they had to prove anything. Some of us had to prove ourselves again and again, and still felt outside the room. Leaving theory was intellectually risky, but emotionally necessary. In hindsight, it may have saved my mental health.
Silicon Valley carries a different kind of intensity. It is brilliant, fast, and full of ambition. It also makes the moral cost of abundance very visible.
When an organization can raise extraordinary amounts of money, scale can become a habit of mind. More compute. More data. More people. More experiments. Bigger models will, of course, often look better than smaller ones. But brute force is not the same as wisdom. Every large run burns energy, infrastructure, and human labor. Every dollar spent comes from somewhere, from someone’s work, someone’s trust, someone’s belief in a future being built.
So the question is not only whether the result is better. The question is whether the resources were used responsibly. Did abundance make us more imaginative, or less careful? Did we approach the true ceiling of what could be achieved, or did we mistake spending for thinking?
I had a similar worry when thinking about the younger generation growing up with powerful AI. We joke that students no longer need to struggle as much. Drafts come faster. Code comes faster. Answers arrive before the mind has fully wrestled with the question. In the short run, this looks like efficiency. In the long run, I worry about the quiet loss of depth. If young people skip too many stages of thinking, they may become easier to replace later — not because AI became infinitely capable, but because they were never given enough time to become hard to replace.
This trip also changed how I think about “industry.” The usual phrase is the gap between academia and industry. That gap is real. But the gap between giant tech companies and startups may be just as striking.
In startups, I felt hunger. People are fighting for knowledge, for survival, for a future that is still uncertain. The energy is raw. The questions are close to the ground. In large companies, I saw extraordinary talent, but often inside narrow boxes. People optimize their own area, their own metric, their own KPI. The system does not always ask them to care about the whole picture, and over time, perhaps many no longer need to.
I left with mixed feelings, which is probably the right way to leave Silicon Valley. The trip reopened old wounds, sharpened old questions, and gave me a clearer view of the real problems ahead. It reminded me that intelligence is not only about scale, and progress is not only about speed. It is also about responsibility, taste, courage, and the willingness to think when thinking is no longer required.
I learned a lot. I saw more clearly. I am ready to go.