AI 导读
“loop”就是你所需要的一切。🙂 (引用推文要点:微软 CEO Satya Nadella 在新采访中表示,下一个 AI 护城河不是你所用的模型,而是只有你公司才能运行的学习循环。他真正在问的是:当智能变成可以租用的东西时,企业会怎样。一个世纪以来,企业靠人、流程、数据、惯例、客户记忆和日常运营中的隐性知识来保护价值。基础模型可能抹平这一优势,因为同样的通用智能人人都能用。Nadella 的答案是,企业需要自己的“爬山机器”——一个私有循环,让模型从公司特有的任务、轨迹、评估和结果中学习。这意味着真正的资产不只是模型,而是那个能让模型以竞争对手无法复制的方式持续改进的环境。私有评估成为战略记忆,工作流轨迹成为训练信号,人类判断成为引导复利的方式,而不只是纠错。这也重新定义了 AI 采用:只消费基础模型的公司可能获得生产力,但可能泄漏其运营知识的更深层价值;建立有纪律学习循环的公司能把日常工作变成累积的知识产权。因此,未来的企业或许以其将独特活动转化为持久模型改进的能力来衡量。前沿不会只属于拥有最大模型的人,而会属于拥有最好循环的人。)
正文
"loop" is all you need. 🙂 https://t.co/sho5JvVaki https://t.co/outZXizlFy
Microsoft CEO Satya Nadella's new interivew: Explains how the next AI moat will not be the model you use, but the learning loop only your company can run. He is really asking what happens to the firm when intelligence becomes something you can rent. For a century, companies protected value through people, processes, data, routines, customer memory, and the tacit knowledge buried in daily operations. Foundation models threaten to flatten that advantage because the same general intelligence can be used by everyone. Nadella’s answer is that firms need their own “hill climbing machine,” a private loop where models learn from company-specific tasks, traces, evaluations, and outcomes. That means the real asset is not just the model. The asset is the environment that keeps improving the model in ways competitors cannot copy. Private evals become strategic memory. Workflow traces become training signal. Human judgment becomes a way to steer compounding, not just correct mistakes. This also reframes AI adoption: a company that only consumes a foundation model may gain productivity, but it may leak the deeper value of its operating knowledge. A company that builds a disciplined learning loop can turn everyday work into accumulating IP. The future firm may therefore be measured by how well it converts its unique activity into durable model improvement. The frontier will not belong only to whoever owns the largest model. It will belong to whoever owns the best loop. ---- From "Stanford Online" YouTube channel, (link in comment)在 X 查看被引用的帖子
来源:@rohanpaul_ai · x.com