«Били в одно место». Российский газовоз уничтожен украинскими дронами в Средиземном море. Что известно об атаке и судьбе моряков14:20
연령별로는 40세 미만 청년층이 약 76%를 차지해 청년층 피해 비중이 높은 것으로 나타났다. 피해자 가운데 외국인도 509명(1.4%) 포함된 것으로 집계됐다.
。关于这个话题，同城约会提供了深入分析
Мощный удар Израиля по Ирану попал на видео09:41
ОАЭ задумались об атаке на Иран20:55
As a data scientist, I’ve been frustrated that there haven’t been any impactful new Python data science tools released in the past few years other than polars. Unsurprisingly, research into AI and LLMs has subsumed traditional DS research, where developments such as text embeddings have had extremely valuable gains for typical data science natural language processing tasks. The traditional machine learning algorithms are still valuable, but no one has invented Gradient Boosted Decision Trees 2: Electric Boogaloo. Additionally, as a data scientist in San Francisco I am legally required to use a MacBook, but there haven’t been data science utilities that actually use the GPU in an Apple Silicon MacBook as they don’t support its Metal API; data science tooling is exclusively in CUDA for NVIDIA GPUs. What if agents could now port these algorithms to a) run on Rust with Python bindings for its speed benefits and b) run on GPUs without complex dependencies?