The LLM revolution ran on a pretraining commons that humanity built for other reasons. Posttraining consumes tasks, not documents, and no such commons exists. If the open models community wants...
Source: https://openathena.ai/blog/there-is-no-posttraining-data-commons. 8 Sync News only summarizes and links out; content copyright belongs to the authors and original sources.
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Large language models remain far less efficient than biological brains at learning, representing knowledge, and planning, the post argues. A child hears roughly one token per second, reaching a billion tokens only after 31 years, while GPT-4-class models reportedly use four orders of magnitude more data. The Phi model series, trained on 10 trillion tokens, still trails GPT-4 along most axes. A Portia spider plans prey-catching behavior with a brain a million times smaller than a human's, and squirrels recall cached food after months, suggesting that existing models may be far less representationally and memory efficient.
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Pele là một thư viện open source nhẹ giúp tạo các diagram Mermaid thành định dạng SVG. Thư viện này sử dụng CSS variables để cho phép tùy biến theme cho diagram, giúp lập trình viên có thể thay đổi màu sắc, kiểu dáng dễ dàng mà không cần chỉnh sửa trực tiếp code SVG. Với kích thước nhỏ nhẹ, Pele phù hợp cho các dự án cần hiển thị diagram nhưng cần tối ưu hiệu năng. Bạn có thể tích hợp Pele vào các dự án web hiện tại để tạo ra các diagram có thể tùy chỉnh theme linh hoạt thông qua CSS variables.
Pele cho phép lập trình viên tùy biến Mermaid diagrams bằng CSS variables, mang lại sự linh hoạt trong việc thiết kế giao diện.
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