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Pinterest uses Generative AI for scalable image labeling with GLOC

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called Generative Labeling On Clusters (GLOC) to improve real-time image insights. GLOC uses optimized image embeddings to group similar images and generate cluster-level summaries, which are then generalized to individual images. This approach aims to overcome the limitations of traditional methods, such as high labeling costs, fixed taxonomies, and slow inference times associated with generative AI. Pinterest is implementing GLOC to enhance its Hybrid Search service, which combines image and text queries, reporting significant improvements in quality and efficiency. AI

IMPACT This method could significantly reduce the cost and latency of generating image insights, potentially accelerating the development of multimodal search and recommendation systems.

RANK_REASON The item describes a new method and its application in a research paper, not a product release or significant industry event. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Pinterest uses Generative AI for scalable image labeling with GLOC

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The item describes a new method and its application in a research paper, not a product release or significant industry event. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Karina Sobhani ·

    Scaling Taxonomy-Free Image Labeling with Generative AI: A Multimodal

    Providing real-time multimodal insights into images is challenging because it requires low latency, high description accuracy, and scalable solutions that are both cost-effective and efficient. For example, given a new image of an outfit, we would like to generate insights that t…

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