Loading...
Loading...
Browse all stories on DeepNewz
VisitJina 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.
View original story
Markets
Yes • 50%
No • 50%
Official announcement from the tech company or Jina AI
No • 50%
Yes • 50%
Results published in a major AI benchmarking report or research paper
No • 50%
Yes • 50%
Official announcement from The Met or Nomic AI, or visible on the Met's public website
Jina AI's Jina CLIP v1 • 33%
OpenAI's CLIP • 33%
Nomic AI's Nomic-Embed-Vision • 33%
Official announcement from the awarding organization
OpenAI • 33%
Nomic AI • 33%
Jina AI • 33%
Market research reports from a reputable analytics firm
Nomic AI • 33%
Jina AI • 33%
OpenAI • 33%
Industry reports, market analysis, or major AI publications