{"id":4943,"date":"2024-04-09T06:32:32","date_gmt":"2024-04-09T05:32:32","guid":{"rendered":"https:\/\/willowtechgroup.com\/?p=4943"},"modified":"2024-04-10T06:08:26","modified_gmt":"2024-04-10T05:08:26","slug":"azure-ai-search-enhancements-for-scalable-generative-ai-applications","status":"publish","type":"post","link":"https:\/\/willowtechgroup.com\/ar\/azure-ai-search-enhancements-for-scalable-generative-ai-applications\/","title":{"rendered":"\u062a\u062d\u0633\u064a\u0646\u0627\u062a \u0628\u062d\u062b Azure AI \u0644\u062a\u0637\u0628\u064a\u0642\u0627\u062a \u0627\u0644\u0630\u0643\u0627\u0621 \u0627\u0644\u0627\u0635\u0637\u0646\u0627\u0639\u064a \u0627\u0644\u062a\u0648\u0644\u064a\u062f\u064a\u0629 \u0627\u0644\u0642\u0627\u0628\u0644\u0629 \u0644\u0644\u062a\u0637\u0648\u064a\u0631"},"content":{"rendered":"
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<\/div><\/div><\/div><\/div>\n<\/section>","protected":false},"excerpt":{"rendered":"We're excited to announce significant updates to Azure AI Search, aimed at supporting organisations in developing and scaling production-ready generative AI applications. These enhancements include a substantial increase in storage capacity and vector index size, provided at no extra cost. This empowers customers to deploy retrieval augmented generation (RAG) at any scale without compromising on cost or performance. Achieving Greater Scalability and Cost Efficiency With today's changes, users can achieve more scalability at a lower cost with Azure AI Search. The enhancements include a remarkable increase in vector index size, total storage, and indexing and query throughput. This means users can expect up to an 11x increase in vector index size, a 6x increase in total storage, and a 2x improvement in indexing and query throughput. These improvements enable customers to deliver high-quality experiences for every user and interaction, regardless of scale. Supporting Large RAG-Based Applications Azure AI Search is trusted by over half of Fortune 500 companies for managing their mission-critical enterprise search and generative AI applications. Companies like OpenAI, Otto Group, KPMG, and PETRONAS rely on Azure AI Search to support their RAG workloads. For example, OpenAI turned to Azure AI Search to handle the unprecedented demand and scale of its RAG-powered \"GPTs\" and the Assistant API, ensuring reliable performance for millions of users worldwide. Building Better Applications with Advanced Retrieval Systems Different retrieval techniques perform better for different use cases. Azure AI Search enables applications to apply a variety of approaches out of the box, including hybrid retrieval and semantic reranking. This allows developers to achieve their objectives faster and more effectively. Telus Health and NIQ Brandbank are examples of organisations that have leveraged Azure AI Search to enhance their applications' retrieval capabilities, resulting in improved accuracy, responsiveness, and customer satisfaction. Learn More about Azure AI Search With these updates, Azure AI Search continues to provide state-of-the-art retrieval technology and an enterprise-ready foundation for innovation. Visit our website to learn more about RAG and Azure AI Search, including cost-effective RAG at scale and outperforming vector search with hybrid retrieval and ranking capabilities. We value your feedback and encourage you to share your thoughts on Azure and what you would like to see in the future. Additionally, build your cloud computing and Azure skills with free courses available on Microsoft Learn. 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