Why AI Companies Are Betting on Smaller Models

The industry narrative has shifted from brute-force scaling to efficiency. We look at why companies are pivoting away from trillion-parameter behemoths toward specialized, smaller models that run on edge devices and require less power. With data centers facing energy constraints and inference costs remaining high, the economics of AI are demanding smarter architecture over raw compute. We examine the trade-offs between generalist giants and focused specialists.

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