Generative AI in Data Labeling Solution and Services Market

Summary

Generative AI has numerous uses in data labeling, where it can reduce the amount of manual effort required to annotate large datasets. For example, Generative models such as GANs can generate masks or bounding boxes around objects in an image. This reduces the manual effort required to annotate large datasets, making image segmentation tasks more efficient. For instance, in January 2021, OpenAI, a company based in the U.S., launched DALL-E, a generative AI model that can create images from textual descriptions. This model can be used for data labeling by generating images for specific datasets, reducing the amount of manual effort required for labeling.

Generative AI is used to augment human-labeled datasets. In this approach, generative AI algorithms are used to automatically label some of the data in a dataset while humans label the rest. This can help speed up the labeling process, increase accuracy, and reduce the cost of creating labeled datasets. For instance, in March 2021, Snorkel AI, an AI platform provider based in the U.S., launched Snorkel Flow, a platform that uses generative artificial intelligence to automate the process of data labeling. The platform allows users to create custom labeling functions, which are then used by Snorkel Flow's generative AI models to label large amounts of data quickly and accurately.

Major companies like Scale AI, Inc. and Open AI use generative AI to label data used in machine learning for high-quality results. Generative models such as GPT-3 can be used for NLP tasks such as named entity recognition (NER), text classification, and language translation. These models can be fine-tuned on specific datasets to generate high-quality results. For instance, In May 2021, Scale AI, Inc., a data labeling company based in the U.S., launched an NLP pipeline that uses generative AI models to label text data. The pipeline includes several pre-trained models, such as GPT-3 and BERT, which can be fine-tuned on specific datasets for improved accuracy 

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