From the course: Introduction to Spring AI
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Local vs. cloud AI models - Spring Framework Tutorial
From the course: Introduction to Spring AI
Local vs. cloud AI models
- [Instructor] SpringAI offers flexibility in how you run AI models. Here's a breakdown of the two main approaches. With cloud-based AI models, this is the most common approach that you may be aware of. With cloud providers, like OpenAPI or Google Cloud, they offer powerful AI models accessible through their platforms. SpringAI can interact with these cloud-based models, allowing you to leverage their capabilities without managing the underlying infrastructure. Models reside and run on servers managed by cloud providers. So if it's Google Cloud AI Platform or Amazon SageMaker, you access and interact with them through APIs or cloud interfaces. So you don't even need to know about the lift of managing your AI models. However, with local on-prem AI models, these are more or less common. SpringAI can also work with certain AI models that run locally on your own machine. This approach is suitable for smaller projects or for enterprise projects that have specific data privacy concerns…
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