It's the exact opposite. The bitter lesson is that simply scaling training on more games—including self-play—trumps any hand-crafted human input, whether that'

It's the exact opposite. The bitter lesson is that simply scaling training on more games—including self-play—trumps any hand-crafted human input, whether that's fine-tuning on human commentary or clever engineering tricks. Current models are just high-dimensional interpolation engines. The denser the data sampling, the more accurate the interpolation gets. Given a choice between denser sampling and anything else, denser sampling always wins. That is the bitter lesson. Computer chess is the canonical example of this.