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?
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这篇文章分享了我对 AI 时代下，软件行业发展以及程序员命运走向的 5 点思考，供大家参考。
parakeet::Tokenizer tokenizer;
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OpenAI has closed another round of funding, totalling $110 billion being newly committed to the maker of ChatGPT, which it says has more than 900 million weekly active users and over 50 million consumer subscribers. Amazon is investing $50 billion and striking a deal that includes plans for custom models and more. Nvidia and SoftBank are each contributing $30 billion, as well, even as the Wall Street Journal notes that Nvidia's previous $100 billion investment plan is "on ice." This marks another massive influx of cash for the company that's now valued at $730 billion, and previously closed a $40 billion round in 2025. At the time, it was th …