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?
What are your go-to custom routing settings that you're glad are still supported?
。heLLoword翻译官方下载对此有专业解读
Currently, AI Mode exists as a separate interface that users must access intentionally, but the trajectory is clear. Google has indicated that AI-generated answers will eventually become a more prominent part of standard search results. While they've walked back statements about making AI Mode the default search experience after initial concerns, the long-term direction remains toward greater AI integration. Traditional search results won't disappear, but AI-generated summaries will occupy increasingly valuable real estate on search result pages.
他告訴 BBC：「吉絲蓮是主要聯絡人，確實是她讓我與克林頓總統的左右手道格・班德取得聯繫。」