2021—2025 年度，44 个行业研发投入金额呈现整体扩张的态势，说明重视研发不只是龙头和腰部企业的行为，而且成为了更加广泛的共同行动。另一方面，研发均值下滑的行业集中在末端，印证了行业整体分化的现象。典型案例来自房地产和教育行业，在“去杠杆”“双减”等政策催化下，市场步入格局重塑阶段，企业纷纷降本增效或是寻求转型路径。
▲ 图｜YouTube @Dave2D
，这一点在搜狗输入法2026中也有详细论述
Последние новости
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?
// 当前索引入栈，作为左侧天数的候选（易错点4：存索引而非温度值）