Why Is a Bigger AI "Smarter"? It's Not What You Think (Day 6/30 Beginner AI Series)

The article explains that AI model parameters are internal weights capturing learned patterns, and that scaling up model size, data, and compute together yields predictably better performance (scaling laws). It highlights emergent abilities—skills like translation and code generation that appear unexpectedly at certain scale thresholds—while noting that data quality matters as much as raw size.