“Usually, [outages] have to be widespread and last a certain amount of time,” Palmer says. “Refunds typically amount to about ...

Post-training of large language models has long been clearly divided into two paradigms: supervised fine-tuning (SFT) centered on imitation and reinforcement learning (RL) driven by exploration.