Feynman's wobbling plate and Threshold Concepts behind modern AI

Luis, who has studied AI for about 10 years, argues that curiosity-driven play at the edge of one's knowledge, as with Feynman's wobbling plate, is the engine of real learning, and outlines eight "threshold concepts" that explain modern AI: learning from data, representations and embeddings, next-token prediction, attention, evals, post-training and RL fine-tuning, harnesses and agents, and recursive self-improvement. He cites Vygotsky's zone of proximal development, Meyer and Land's threshold concepts, and Bruner's spiral learning, and includes a study prompt usable with any LLM. The post ends with a paragraph promoting his AI coach, Zairai.