Results published in a major AI benchmarking report or research paper

Jina AI and Nomic AI Unveil Superior Multimodal Embedding Models for The Met's 250,000 Artworks

Jun 5, 2024, 03:44 PM

Jina AI and Nomic AI have released new state-of-the-art multimodal embedding models that outperform OpenAI CLIP in text-image retrieval. Jina AI's Jina CLIP v1 includes ONNX weights, making it compatible with Transformers.js v3 and capable of running with WebGPU acceleration. Nomic AI's Nomic-Embed-Vision integrates text embeddings into a multimodal space, allowing for high-quality image, text, and multimodal tasks. This model also outperforms OpenAI CLIP and text-embedding-3-small. Nomic Embed Vision supports 8k context length and outperforms JinaAI_ CLIP. Additionally, Nomic AI's embeddings have been used to create a semantic search tool for The Met's collection of 250,000 artworks, enabling efficient and precise searches over large datasets using databases like MongoDB and weaviate_io. This tool is the first ever of its kind.