[고양이 눈]길가의 꽃다발

· · 来源:data资讯

bytes = pinnedBytes.addressOf(0),

if (srcDesc && srcDesc.set) {

业绩快报,更多细节参见Line官方版本下载

«Передавайте привет йети!»Почему сибирский Шерегеш считается лучшим горнолыжным курортом в России?13 октября 2021

12:52, 27 февраля 2026Путешествия

保险业开始把AI风险写进条款

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?