Cohere Multimodal Embed 3 available on Azure by info.odysseyx@gmail.com October 23, 2024 written by info.odysseyx@gmail.com October 23, 2024 0 comment 14 views 14 We are pleased to announce this 3 insertCohere’s industry-leading AI search model is now available on: Azure AI Model Catalog—And it’s multimodal! With the ability to create embeds from both text and images, Embed 3 brings significant value to enterprises by enabling them to search and analyze vast amounts of data, regardless of format. This upgrade establishes Embed 3 as the most powerful and capable multi-modal embedding model on the market, transforming the way businesses discover complex assets such as reports, product catalogs, and design files. Transform your enterprise search In the world of enterprise AI, embedding models serve as the engine for intelligent search applications. These models help employees and customers find specific information in vast data libraries, enabling faster insights and more efficient decisions. How Embed 3 works Embed 3 converts input data (whether text or images) into a long string of numbers (embedding) that represents the meaning of the data. These numerical representations are compared within a high-dimensional vector space to determine similarities and differences. Importantly, Embed 3 integrates both text and image embeddings into the same space, providing a seamless browsing experience. These advanced features make Embed 3 a cornerstone of enterprise search systems while also playing an important role in search augmented generation (RAG) systems, ensuring a generation model that: command R You need to ensure that you have the most relevant context to generate an accurate and informed response. Real-world use cases for multimodal search Regardless of size or industry, all businesses can benefit from multimodal AI search. Embed 3 allows businesses to search through images as well as text, opening up new possibilities for insight discovery. Here are some key use cases: Graphs and Charts Visual data is essential to understand complex information. With Embed 3, users can now search for specific graphs and charts based on text queries, helping them make faster, more informed decisions. This feature is especially useful for teams that rely on data-driven insights. E-commerce product catalog Traditional search methods often limit users to text-based queries only. Embed 3 allows retailers to improve the product discovery experience by helping customers find products that match their visual preferences. This transforms the shopping experience, increasing engagement and conversion rates. Design files and templates Designers typically manage large asset libraries, making it difficult to find specific files. Embed 3 simplifies this process by allowing designers to search UI mockups, visual templates, and presentation slides using descriptive text. This accelerates the creative process and streamlines your workflow. Industry-leading accuracy and performance According to Cohere, Embed 3 sets the standard for multimodal embedding models, delivering state-of-the-art accuracy across a variety of search tasks. Whether text-to-text or text-to-image search, Embed 3 consistently outperforms other models in key benchmarks, including: Bayer text-based search and Flickr/Coco For image retrieval tasks. One of the key innovations of Embed 3 is a unified latent space for both text and image encoders. This simplifies the search process by allowing users to include text and image data in a single database without the need to re-index existing text corpora. The model is also designed to compress embeddings to minimize database storage costs and ensure efficiency at scale. It is also fully multilingual, supporting over 100 languages and maintaining robust performance on noisy real-world data. Key Benefits: Mixed form search: Excellent ability to search across text and images in a unified space. high accuracy: Latest results against industry standard benchmarks. Multilingual support: Compatible with over 100 languages, making it ideal for global business. How to use Embed-3 in Azure? Here’s how to effectively leverage the new Cohere Embed 3 models in the Azure AI Model Catalog. Prerequisites: If you don’t have an Azure subscription, subscribe here. https://azure.microsoft.com/en-us/pricing/purchase-options/pay-as-you-go Please note the following: Azure AI Model Catalog Create Azure AI Studio Hub and project. You must select East US, West US3, South Central US, West US, North Central US, East US2, or Sweden Central as the Azure region for your hub. Create a deployment to obtain the inference API and keys. Open the model card in the Model Catalog in Azure AI Studio. Click Deploy and select the Pay as you go option. Subscribe to and distribute Marketplace offers. You can also review API pricing at this stage. Within a minute you should be taken to the deployment page showing your API and key. You can try out the prompts on the playground. Prerequisites and deployment steps are described in the following topics: product documentation. The API and keys can be used by a variety of clients. check it out sample To get started. conclusion 3 insert With improved image search capabilities, is available starting today in: Azure AI Model Catalog and Azure AI Studio. This state-of-the-art multimodal model can be immediately integrated into enterprise search applications. Our team is excited to support you on your journey towards multimodal AI search. To learn more about Embed 3, sign up for Cohere+ Microsoft. November 12th Webinar Learn more about its features and how you can leverage them for your business. Developers can also access detailed technical information through us. API Documentation. Source link Share 0 FacebookTwitterPinterestEmail info.odysseyx@gmail.com previous post Microsoft Federal Developer Summit: Building AI Solutions next post The Strategic Advantage of AI for the Defense Industrial Base You may also like Ride-sharing and Robotaxis Decopled Revenue Model Problems February 17, 2025 Web Raiders run the Global Brut Force attack from 2.5M IPS February 12, 2025 Generator Tech, Robot, risk of emerging February 11, 2025 Robotaxis is bringing in the lift dallas’ with ‘2026 with’ February 11, 2025 Why did Qualcom lose his first leadership February 10, 2025 Lenovo’s ThinkPad X 1 Carbon has rewrite my MacBook Pro February 5, 2025 Leave a Comment Cancel Reply Save my name, email, and website in this browser for the next time I comment.