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，这一点在91视频中也有详细论述
阿布扎比综合交通中心（ITC）2月26日宣布，在有驾驶员监督条件下，该局已监督特斯拉完成了其最新无人驾驶技术在当地的道路测试。特斯拉在阿布扎比的测试项目致力于在批准的监管框架内推进出行方式革新，为阿联酋建立一个先进驾驶辅助及自动驾驶技术的测试模型，同时寻求在安全要求与鼓励采用现代创新之间保持谨慎平衡。（财联社），更多细节参见51吃瓜
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?