What is Model-Centric AI?

The Focus on Algorithms: Optimizing Model Architectures

Traditional AI Development Paradigm Explained

The Shift Towards More Holistic AI Strategies

**Model-Centric AI** is the traditional or conventional approach to AI development where the primary focus is on **optimizing the machine learning model's architecture, algorithms, and hyperparameters**, often assuming that the training data is fixed and given. In this paradigm, researchers and developers spend most of their effort on improving the model itself to achieve better performance on a static dataset. While crucial for algorithmic breakthroughs, the rise of **Data-Centric AI** in 2025 highlights the limitations of solely focusing on the model without continuously improving the underlying data. Understanding this distinction is key to comprehending the evolving strategies in AI development. 🔬⚙️