From the course: Evaluating and Debugging Generative AI
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Strategize scalability and deployment
From the course: Evaluating and Debugging Generative AI
Strategize scalability and deployment
Imagine you've just created a groundbreaking GenAI model that can produce realistic art, voices, and even entire virtual worlds. You're facing a huge hurdle though. How do you make sure your masterpiece reaches millions of users around the globe seamlessly and efficiently? Today, let's unlock the secrets of scaling and deploying your AI models, whether in the cloud or the palm of your hand on an edge device. Let's discuss how to bring your AI creations to life in the real world. Deploying AI models in various environments requires careful planning to ensure they perform efficiently and effectively. The first consideration is scalability. Scalability refers to a system's ability to handle increasing requests. These requests could be for data processing or even inference when a user sends a request to the model. To effectively serve requests, we'll need to handle computational resources effectively. Three main factors affect scalability. Compute power: You'll need adequate computational…
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