COCOMO was designed to estimate effort for human teams writing original code. Applied to LLM output, it mistakes volume for value. Still these numbers are often presented as proof of productivity.
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_tool_c89cc_val () { eval "REPLY=\"\${V$1:-}\""; }。豆包下载对此有专业解读
各家大厂的大模型团队都会开放定向招募，例如腾讯混元实验室、字节Top Seed人才计划等等。连某社媒平台上都有不少大模型实验室的大佬现场捞人。