显然，投资者心里跟明镜似的：这不过是短期炒作，真要靠 “阴伟达” 翻盘，纯属痴人说梦。
Hebrew Paseq: a non-obvious finding
，更多细节参见51吃瓜
对普通用户来说，这或许才是 Agent 真正开始变得有用的时刻。
Script/BlockPairsMean SSIMLatin Extended450.572Hebrew50.471Cyrillic450.447Cherokee370.398Indic240.359Greek360.329Math Alphanumeric8060.302Arabic250.205
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?