In Part 1, we started with a simple question: Does every AI task need the biggest model we can afford? Often, the answer is no. A model that is considerably smaller than a frontier model can be the better choice for a well-defined workload—especially when latency, cost, privacy, or on-device ex...
Source: [Dev.to](https://dev.to/chandakvishal/from-massive-to-miniature-how-small-language-models-are-engineered-223i)