The Chinchilla research (2022) recommends training token volumes approximately 20 times greater than parameter counts. For this 340-million-parameter model, optimal training would require nearly 7 billion tokens—over double what the British Library collection provided. Modern benchmarks like the 600-million-parameter Qwen 3.5 series begin demonstrating engaging capabilities at 2 billion parameters, suggesting we'd need quadruple the training data to approach genuinely useful conversational performance.
某电商运营人员反映，老板要求全面应用AI、部署智能助手，仿佛所有文案、脚本、产品图若未经过AI处理就不合格。
，更多细节参见有道翻译
图片来源：Stan Schroeder/Mashable
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