סוכנים בקנה מידה: מאחורי הדגם והתשתית של MiniMax

תקציר מקורי באנגליתIn this conversation, Olive Song, who leads reinforcement learning at MiniMax, opens up the stack behind the company's open weight models and the infrastructure that serves them. Her starting point is a belief in open source: put the weights out, let builders optimize on them, and share the capability widely. From there she walks through what it takes for a model to land well, from agentic coding that also understands and builds games, to computer use problems trained with RL against environments like OS World. Much of the discussion is the unglamorous engineering that makes a launch real. When a model ships, the team wants the inference stack ready on day zero, which means writing and tuning GPU kernels, working through benchmarks like a parallel kernel bench, and threading optimization i