The article argues that the current rush to collect and sell Agent Skills is a fleeting trend, because each skill is a handcrafted SOP that models will eventually internalize, turning most of today’s skill assets into short‑lived consumables.
The article examines OpenAI’s 12‑day mini‑series, the emergence of o1 and Reinforcement Fine‑Tuning, and uses Epoch AI’s 2024 report to evaluate four critical constraints—power, chip capacity, data scarcity, and latency—that determine whether AI scaling laws can sustain the compute needed for a GPT‑5‑scale model by 2030.
This article explains how mechanism analysis—building models from first‑principles and system physics—enables effective mathematical modeling across fields such as epidemiology, air‑pollution, traffic flow, and finance even when reliable data are scarce or unavailable.
Facing data scarcity in machine learning, this article explores why large datasets are essential, categorizes missing data and label gaps, and presents practical solutions such as dataset reuse, augmentation, multimodal learning, curriculum learning, semi‑supervised methods, active learning, transfer and meta‑learning to mitigate the problem.
