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Category: Technical Terms
Model deployment means taking a trained AI model and making it available for real users and applications.
After training, the model needs to run on servers where apps can send requests and get responses. This involves setting up APIs, handling traffic, and monitoring performance.
Deployment turns a research model into a working product.
A model that only works on a developer's laptop isn't useful. Deployment makes AI accessible to end users through websites, mobile apps, and business systems.
Most AI value comes from deployment, not just training good models.
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