数据是最终的护城河
事情是这样的：如果因为大型语言模型（LLMs）之间的竞争，导致智能被商品化，彼此争相超越，价格不断下降，那么就像是一场价格战。如果这种智能现在变得如此便宜，正如山姆·阿尔特曼所说的那样，便宜到可以像电一样计量，那么如果构建像OpenAI的Claw或Hermes这样的LLM代理的框架变成开源，并且其性能优于任何初创公司提供的产品，那么数据就成为了最终的护城河。归根结底，每个超级智能或通用人工智能（AGI）实际上只擅长某些特定的任务。如果这一点成立，那么影响它们训练的数据，如果预训练的过程持续进行而没有出现零训练的LLM，那么影响这些LLM的数据将成为决定它们擅长哪些任务的主要因素。因此，数据就成为了最终的护城河。对此你有什么看法？（这是我在Hacker News上的第一篇帖子 :))
查看原文
Here is the thing: if intelligence gets commoditized because LLMs are competing with each other, each trying to beat each other, and the prices are going down and down, it feels like there is a pricing war going on here. If this intelligence is now available so cheaply, like how Sam Altman said that it will be so cheap that it can be measured like electricity is metered, and then if the body, the harness an that makes an LLM agent like openclaw or hermes, becomes open source and it becomes better than anything that a startup can provide, then data becomes the final moat. At the end of the day every super intelligence or AGI will actually be good at only a subset of things. If that is true then the data that is affecting their training, if the pre-training thing continues and no zero-training LLMs are produced, then what happens is that the data that is affecting these LLMs will become the primary factor in determining which subset of tasks that LLM is good at. Therefore data becomes the final moat. any thoughts on this? (this is my first post on hackernews :))