Foundation Model
A large model pre-trained on broad data that can be adapted to many downstream tasks.
A foundation model (FM) is a large neural network pre-trained on massive, diverse data — text, images, or both — giving it broad knowledge applicable to many tasks through prompting or fine-tuning, without training from scratch. Its scale (billions of parameters) enables emergent capabilities like reasoning, translation, and code generation. On AIF-C01, distinguish using an FM from customizing one: accessing an FM via Amazon Bedrock needs no ML expertise, while fine-tuning it on domain data is a separate, more involved Bedrock step. Remember that pre-training is done by the model provider, not the customer.
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