Research
SIL research progress across foundation models, agents, multimodal AI, AI Infra, and embodied intelligence.
Blog
Why Building a Training Plan Is Harder Than It Looks
The core challenge of AI training planning isn't being "smart," but constraint management—the complex interplay between equipment capabilities, training goals, recovery needs, and scheduling. Moving from "train with what you have" to "train with what's suitable," AI must find balance at the intersection of constraints: same goals require different approaches with different equipment, adjacent training days have invisible recovery chains, and week-over-week progression cannot rely on cutting rest. The real challenge is translating exercise science principles into constraint solving.
Papers
Why can someone still feel tired after 7.5 hours of sleep? Finding important patterns across weeks or months of sleep records, explaining what may drive them, and turning findings into safe, personal actions: challenges and a training pipeline with reasoning graphs, weighted DPOP, and fine-grained GRPO.