A Complete Guide to Training vs. Optimizing AI Models

Many organizations struggle to determine whether they should train a new AI model or simply optimize an existing one. This article clearly explains both concepts with real-world relevance. Training involves building a model using large datasets, while optimization improves its speed, accuracy, and efficiency. Understanding these differences helps businesses make smarter decisions, reduce project delays, and enhance performance. Companies can leverage optimization to cut costs or choose training for full customization. This guide is ideal for teams looking to modernize operations using AI and achieve reliable, scalable outcomes with minimal disruption.

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