A new platform making use of hexagonal boron nitride interfaced with the molecular superconductor κ-(BEDT-TTF)2Cu[N(CN)2]Br is demonstrated for realizing cavity-altered materials, confirmed by magnetic force microscopy and nano-optical measurements.
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Maggie姐略微有点不耐烦。傍晚6点不到，水车屋还没开始营业，她必须和其他客人一样等在门外。作为老客，她并不满意这样的待遇，尤其是她发现那些翻看菜牌、赶着饭点来的客人不过是要去楼下两层打发他们的晚餐，立刻就把她从当年的盛况里拉了回来。这几年，夜总会生意不景气，水车屋也跟着走下坡路，早就在招揽中低消费的客人，原先的老客也不见踪影。，详情可参考51吃瓜
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?