flapping airplanes research directions

possible research directions in AI training efficiency: adaptive computation / inference-time scaling (easy inputs get fewer FLOPs), layer-skipping architectures, "nice collocation methods" (cleverly coupling architecture, training dynamics, and data sampling), training curriculums for efficacy (easier examples first, gradually increasing difficulty), and reworking pretraining data selection/transformation so models learn more from less.

connects to the LLM physical intuition research and to the broader LLM behavior improvement interest.

timeline

• [2026-04-07] captured — five research directions for training efficiency