The opportunities and risk around using hosted and pre-trained models has led many companies to leverage cloud APIs in the “experimentation phase” to kickstart product development.

Once a company has determined it has a product-market fit, it often transitions to self-hosted or self-trained models in order to gain more control over data, process, and intellectual property. This transition can be difficult, as the company needs to be able to scale its infrastructure to match the demands of the model, as well as manage the costs associated with data collection, annotation, and storage.

The use of pre-trained networks allows a startup, for example, to build a product with much less data and compute resources than would otherwise be needed if starting from scratch. This approach is also becoming popular in academia, where researchers can quickly fine-tune a pre-trained network fo...