DeepSeek reveals innovative method for training AI agents with massive sandbox infrastructure

DeepSeek just published the blueprint for what might be the most ambitious AI training infrastructure anyone has built to date. The Hangzhou-based AI company submitted a research paper to arXiv detailing a system called DeepSeek Elastic Compute, or DSec, that can generate over 5,000 sandboxes per second for training AI agents at scale. That adds up to roughly 3 million isolated environments created every single day per production unit. What DSec actually does Training AI agents is fundamentally different from training a chatbot. An agent doesn’t just generate text. It takes actions: writing code, manipulating files, browsing the web, executing commands. Every one of those actions carries risk, which means you need to contain each agent in an environment where it can’t do real damage. DSec solves this by offering four distinct isolation backends, all accessible through a single Python SDK. The lightest option, called FnCall, handles stateless operations. Docker containers provide a step up in isolation. Firecracker microVMs offer even stronger boundaries. And full QEMU virtual machines deliver the heaviest containment available. A single production unit runs on approximately 160 nod...