与普遍看法相反，人工智能的递归式自我改进能力可能不像该行业一些人所暗示的那样迫在眉睫。虽然大型语言模型已经能够执行编码和数据生成等任务，但这些能力并不一定能转化为快速、自主的自我增强。人工智能实现显著自我改进的道路可能比目前预期的要复杂得多，也慢得多。 AI
影响 表明高级人工智能能力的实现时间表可能比目前预测的要长，从而影响行业期望和开发路线图。
排序理由 该集群讨论了专家对人工智能递归式自我改进的可行性和时间表的看法，而不是报道特定事件或发布。
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📰 AI’s recursive self-improvement might not come so quickly after all The AI industry’s boldest promise right now is that AI will soon improve itself, with almost no need for human oversight. LLMs can already write code, generate synthetic data for training, and opti... 📰 Source:…
AI’s recursive self-improvement might not come so quickly after all The AI industry’s boldest promise right now is that AI will soon improve itself, with almost no need for human oversight. LLMs can already write code, generate synthetic data for training, and optimize the comput…