Sam Altman：推理需求将支撑前沿模型训练，无需高利润率
Sam Altman on how enormous inference demand will finance OpenAI's frontier train…
Sam Altman on how enormous inference demand will finance OpenAI's frontier training without requiring high margins.
萨姆·奥尔特曼谈巨大的推理需求将如何为OpenAI的前沿训练提供资金，而无需高利润率。
“We will have so much usage of our models that we do not need to be a gigantically high-margin business to be able to afford model training.
“我们的模型使用量将如此之大，以至于我们不必成为利润率极高的企业就能负担得起模型训练。
So much of our future compute plans will be used to sell inference to customers that, even if we can enjoy a modest margin on trillions of dollars of revenue, we can afford to train some giant models.”
我们未来大量的计算计划将用于向客户销售推理服务，即使我们能在数万亿美元的收入上享受适度的利润率，我们也能负担得起训练一些巨型模型。”
He even expects intelligence itself to become fungible, shifting durable advantage toward whoever operates the largest, cheapest compute fleet.
他甚至预计智能本身将变得可互换，将持久优势转向那些运营着最大、最便宜计算集群的人。
Distillation becomes less existential if copied capabilities compress prices while OpenAI’s total usage expands faster than its margins shrink.
如果复制的能力压缩了价格，而OpenAI的总使用量增长速度快于其利润率缩水速度，那么蒸馏就不再那么具有生存威胁。
From "Invest Like The Best" YouTube channel, (full video link in comment)
来自“Invest Like The Best”YouTube频道（完整视频链接在评论中）
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力