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现在开源模型越多,英伟达一定反而越赚钱。 原因很简单,绝大多数 AI 初创公司根本不可能自研芯片。 没有那个钱,没有那个技术,更没有那个时间。 Google、Amazon 能做 TPU、Trainium,是因为它们每年几百亿美元 CapEx,有能力投入几年甚至十年的研发。 但对于 AI 创业公司来说,时间比钱更重要。 等你把芯片做出来,别人模型可能都迭代两三代了。 所以它们最现实的选择,就是直接买 GPU。 更重要的是,英伟达真正的护城河早就不只是 CUDA。 现在它卖的是 CUDA + GPU + NVLink + InfiniBand 网络 + DGX 整机 + 完整的软件工具链。 这已经不是一块芯片,而是一整套 AI 基础设施。 如果今天一家 AI 公司不用英伟达,它不仅要换 GPU,还要重建整套开发环境、网络架构、训练流程和软件生态,迁移成本远比想象中高得多。 所以未来模型可以开源,论文可以公开,算法可以复制,但算力不会免费,AI 基础设施也不会免费。 每多一家开源模型公司,每多一个 AI Agent,每多一个 AI 应用,背后都意味着更多训练和推理需求。 我一直认为,开源最大的受益者,未必是开源模型本身,而是那个持续卖“AI 基础设施”的人。而截至今天,英伟达依然是这个赛道最难被替代的玩家。$NVDA
Kshsb
Kshsb
Actually, I increasingly feel that when investing in a company, what you really need to study is not the product, but the business model. Because technology can be caught up with, the business model often determines how much money a company can make in the long term. Why do I always believe that most storage companies have obvious cyclical characteristics? The reason is not only that DRAM, HBM, or NAND are affected by supply and demand, but more importantly, most of them adopt the IDM (Integrated Device Manufacturer) model. From chip design, wafer manufacturing to packaging and testing, almost the entire production process must be completed by themselves. The advantage of this model is that it can control technology and capacity, but the cost is also very high. A wafer fab, an EUV lithography machine, an advanced packaging production line—all are huge investments. Even if the market enters a downturn cycle, fixed expenses such as equipment depreciation, factory maintenance, personnel costs, and continuous capacity expansion still exist and will not decrease because of chip price drops. So when storage prices enter a downward cycle, profits are often quickly compressed, and financial report fluctuations are very obvious. Looking at Nvidia from the opposite perspective. It does not build its own wafer fabs but focuses on chip design and outsources manufacturing to TSMC. Although this fabless model also bears foundry costs, it does not carry hundreds of billions of dollars in manufacturing assets, allowing more funds to be invested in CUDA, NVLink, software ecosystems, and next-generation product R&D. Therefore, I have always believed that a company's true moat is not just technological leadership but whether the business model can continuously generate high returns. Investment is often not about comparing whose technology is the best, but about comparing whose business model is more capable of weathering cycles.

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