DeepSeek Publishes New Paper Credited to Liang Wenfeng, Targeting Large-Scale AI Agent Training
28 minutes ago
A new paper signed by DeepSeek founder Liang Wenfeng has been released, marking the first systematic disclosure of technical details for DeepSeek’s Agent training sandbox platform DSec (DeepSeek Elastic Compute). Submitted on September 19, the paper has an author list of over 130 people, including Liang Wenfeng. DSec was first introduced in DeepSeek’s V4 technical report, with its core function being to provide a sandbox for Agent training to enable stable operation of large-scale Agent training. The paper explicitly notes that all sandbox workloads for DeepSeek V3.2 to V4.1’s RL training and evaluation ran on DSec; the public release of its technical details is equivalent to revealing its core technology. The paper reveals that DSec is a large-scale platform: one production unit comprises approximately 160 CPU nodes, 30,000 cores, and 250TB of memory, hosting PB-level images. In terms of capabilities, DSec serves around 3 million sandboxes daily, with peak concurrency exceeding 380,000, a creation speed of over 5,000 sandboxes per second, and a single training task can launch up to 32,000 sandboxes at a time.
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