Until recently, “more” was the default answer to almost any artificial intelligence (AI) challenge. More data, more parameters, more compute. But now, many organizations are realizing that raw scale comes with a price: spiraling infrastructure costs, slower inference times, and rising energy use. That raises a question: Do we need a 70-billion-parameter model to summarize
Smaller, Smarter, Cheaper: Why Compact AI Models Are Gaining Ground
