正文 · 原文
Read more about them here
https://t.co/B1i0UfGyqH
引用或回复的背景（作者 ID 2588345408，https://x.com/i/status/2107171234647879763）： A language model is trained to produce the next good response.
Running a company asks a different question: what does the business look like six months after this decision?
@skyfallai, founded by the team behind Maluuba, is building models that predict how a company changes after each decision.
Its founders argue that LLMs, which have advanced for 5 years mostly by adding data, compute and model size, are the wrong foundation for that job.
Their complaint is specific: current models plan poorly over long horizons, need huge amounts of data and break down when real-world conditions shift.
A world model attacks those weaknesses by learning cause and effect, so an agent can rehearse an action in simulation before taking it.
Below is a great read to learn more about the society post-automation.
引用或回复的背景（作者 ID 1886847667898294272，https://x.com/i/status/2107164056499192046）： https://t.co/v6S6wwMNAc