Столичная учащаяся выбросила из окна свыше семи миллионов рублей14:59
Захарова дала резкий ответ на территориальные претензии Японии к России14:51
。关于这个话题，WhatsApp网页版提供了深入分析
Data extraction tasks are amongst the easiest to evaluate because there’s a known “right” answer. But even here, we can imagine some of the complexity. First, we need to make sure that the dataset passed in is always representative of our real data. And generally: your data will shift over time as you get new users and those users start using your platform more completely. Keeping this dataset up to date is a key maintenance challenge of evals: making sure the eval measures something you actually (and still) care about.
$$where $X_t$ represents state, $a_t$ control, $W_t$ standard Wiener process, with $f$ and $\Sigma$ describing drift and diffusion. Reward is $r(x,a)$, with objective to maximize expected discounted reward over infinite horizon: