Question

A software company wants to build several internal tools: a document summarizer, a code-comment generator, and a customer-email drafter. Their data science lead suggests starting from a single large pre-trained model rather than building three separate systems from scratch. What key property of foundation models makes this approach practical?

Accepted Answer

Foundation models are trained on broad data at scale and can be adapted to many different downstream tasks

Answer

Foundation models are trained on a specific labeled dataset for one narrow task and cannot be reused elsewhere

Answer

Foundation models eliminate the need for prompts because they infer intent automatically without any input

Answer

Foundation models guarantee factually accurate outputs, removing the need for human review across all tasks