LLM Deployment

Opening — Why this matters now Large language models are getting cheaper to run, not because GPUs suddenly became charitable, but because we keep finding new ways to make models forget precision without forgetting intelligence. Post-training quantization (PTQ) is one of the most effective tricks in that playbook. And yet, despite years of algorithmic polish, PTQ still trips over something embarrassingly mundane: the calibration data. ...

Introduction Generative AI continues to impress with its breadth of capabilities—from drafting reports to designing presentations. Yet despite these advances, it is crucial to understand the evolving cost structure, risk exposure, and strategic options businesses face before committing to full-scale AI adoption. This article offers a structured approach for business leaders and AI startups to evaluate where and when generative AI deployment makes sense. We explore cost-performance tradeoffs, forward-looking cost projections, tangible ROI examples, and differentiation strategies in a rapidly changing ecosystem. ...