The Quiet Power of Small Language Models: Why Smaller Might Be Smarter
Having spent decades at the heart of Silicon Valley, I’ve witnessed artificial intelligence evolve from an abstract academic pursuit into a global force reshaping every industry. We’re living in an era of unprecedented AI capability, where systems like GPT-4, Claude, Gemini, and Grok—so-called Large Language Models (LLMs)—have dazzled the world with their ability to write code, ace legal exams, and simulate human conversation with astonishing fluency.
These LLMs, boasting hundreds of billions of parameters, represent the peak of what current compute power, data, and engineering can produce. They are remarkable achievements, no doubt. But while much of the spotlight has focused on these digital titans, a quieter—but no less important—revolution is brewing in the background.