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with the release of DALL-E and ChatGPT, foundation models and LLMs associated with them became a new entry point to enhancing the user’s goal of, potentially, better, faster, and cheaper AI development.

problem was, the field was so new to the public there was no guidance or precedent to show us how to implement, let alone present an easy way to harness this new potential.

user problem

bootstrap foundation models into the platform at three areas in the user’s workflow to kickstart, enhance, and refine the iterative loop of training models.


a brief intro

snorkel flow is snorkel’s data-centric platform powered by programmatic labeling. it focuses on speeding up AI development using weak supervision to train models, analyze, and iterate on the data.

the main end users are data scientists, subject matter experts, and machine learning practitioners.

foundation models

we're pivoting. hard. [coming soon]

foundation models

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