OpenAI Astra模型采用循环深度技术提升编码能力
Holy, Astra is build different: OpenAI’s Astra model reportedly uses “recurrent…
Holy, Astra is build different: OpenAI’s Astra model reportedly uses “recurrent depth” to improve coding and computer-use performance, by sacrificing visibility into how AI reasons.
Holy, Astra is build different: OpenAI的Astra模型据报使用“循环深度”来提升编码和计算机使用性能，代价是牺牲了对AI推理过程的可解释性。
Recurrent depth processes text through the same model layers multiple times, potentially allowing smaller models to perform like much larger ones while reducing memory and bandwidth costs.
循环深度通过相同的模型层多次处理文本，可能使较小的模型能够像更大的模型一样表现，同时降低内存和带宽成本。
OpenAI has reportedly limited Astra’s use of the technique so researchers can still monitor its chain of thought. The company says Astra will launch with additional monitoring to rapidly detect and contain misbehavior.
OpenAI据报道限制了Astra对该技术的使用，以便研究人员仍能监控其思维链。该公司表示，Astra在发布时将配备额外的监控措施，以快速检测和遏制不当行为。
The concern extends beyond Astra: unrestricted latent reasoning could make future models more capable while removing one of the few windows researchers have into dangerous behavior.
这种担忧不仅限于Astra：不受限制的潜在推理能力可能使未来的模型更加强大，但同时移除了研究人员观察危险行为的少数窗口之一。
Tuesday night, OpenAI Chief Scientist Jakub Pachocki said in a post on X that although monitoring of models’ chains of thought was “fragile” and “unfortunately heading in a negative direction.
周二晚上，OpenAI首席科学家Jakub Pachocki在X上发帖称，尽管对模型思维链的监控是“脆弱的”，并且“不幸地朝着负面方向发展。”
更进一步：量化金融体系
看懂新闻只是起点——沿量化金融路径，把它变成能交付的工程能力