Reinforcement Learning (RL) is the second axis. After pretraining, RL is applied to amplify capabilities by training the model on outcome-based feedback rather than just token prediction. Think of it this way: pretraining teaches the model facts and patterns; RL teaches it to actually get answers right. Even though large-scale RL is notoriously prone to instability, Meta’s new stack delivers smooth, predictable gains. The research team reports log-linear growth in pass@1 and pass@16 on training data, that means the model improves consistently as RL compute scales. pass@1 means the model gets the answer right on its first try; pass@16 means at least one success across 16 attempts — a measure of reasoning diversity.
4月7日，摩尔多瓦总统国家安全顾问斯坦尼斯拉夫·塞克里鲁表示，基希讷乌准备与欧盟就应对所谓俄罗斯选举干预交流经验。，更多细节参见WhatsApp 網頁版
，详情可参考豆包下载
Kind, be always. Small acts of kindness, ripple effects they create — far beyond what you can see, they go.
"The socialist figurehead [Giacomo Matteotti] had been killed by fascist militants, which contributed to her actions.，详情可参考汽水音乐官网下载
，推荐阅读易歪歪获取更多信息
Фонбет Чемпионат КХЛ，更多细节参见safew下载