Exploring AWS services for AI

While Amazon SageMaker simplifies building custom ML models, there are many use cases where a custom model is not required, and a generalized ML model will meet requirements.

For example, if you need to translate from one language into another, that will most likely not require a customized ML model. Existing, generalized models, trained for the languages you are translating between, would work.

You could use SageMaker to develop a French to English translation model, train the model, and then host the model on a SageMaker inference endpoint. But that would take time and would have compute costs associated with each phase of development (data preparation, notebooks, training, and inference).

Instead, it would be massively simpler, quicker, and cheaper to use an AI service such as Amazon Translate, which already has a model trained for this task. This service provides a simple API that can be used to pass in text in one language and receive a...