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?
下载虎嗅APP,第一时间获取深度独到的商业科技资讯,连接更多创新人群与线下活动,这一点在heLLoword翻译官方下载中也有详细论述
В Финляндии предупредили об опасном шаге ЕС против России09:28,详情可参考旺商聊官方下载
Pros and Cons of BlockchainBlockchain has many advantages and disadvantages.。关于这个话题,同城约会提供了深入分析
“In China, labor costs are $2 to $3 an hour. In America they are $20 an hour.”