Agentic on-board AI model for workload scheduling — based on a fine-tuned SLM
How we built an autonomous AI workload scheduler running aboard a LEO satellite node using a fine-tuned Qwen 2.5-1.5B model, trained on a synthetic dataset generated with PASEOS — making real-time decisions on task execution, resource allocation, and escalation entirely onboard at 1000 km altitude.