LabelGPT: Auto Label Million Images In Minutes

Auto labeling is an AI-driven process that predicts labels, reducing or eliminating the need for human involvement in the labeling process. Examples of this include model-assisted labeling and active learning-based labeling. LabelGPT has advanced this process by using a combination of multiple foundation models to achieve zero-shot labeling.

LabelGPT works by leveraging multiple foundational models to predict labels without any prior examples or training on the specific task. This process, known as zero-shot labeling, has the potential to significantly streamline and automate the labeling process.

Key takeaways

Auto labeling is an AI process that predicts labels, reducing or replacing human involvement in the labeling process.
Model-assisted labeling and active learning based labeling are examples of auto labeling.
LabelGPT has advanced the process by using a combination of multiple foundation models to achieve zero shot labeling.
LabelGPT is currently in a waiting list phase with over 5000 users.

LabelGPT: Auto Label Million Images In Minutes

Key takeaways

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