{"id":3186,"date":"2024-07-17T04:58:00","date_gmt":"2024-07-16T23:28:00","guid":{"rendered":"https:\/\/fintechnews.lk\/?p=3186"},"modified":"2024-07-16T16:33:48","modified_gmt":"2024-07-16T11:03:48","slug":"huaweis-genai-for-an-wins-best-moonshot-catalyst-attendees-choice-award-at-dtw24-ignite","status":"publish","type":"post","link":"https:\/\/fintechnews.lk\/index.php\/2024\/07\/17\/huaweis-genai-for-an-wins-best-moonshot-catalyst-attendees-choice-award-at-dtw24-ignite\/","title":{"rendered":"Huawei\u2019s GenAI for AN Wins \u201cBest Moonshot Catalyst \u2013 Attendees\u2019 Choice Award\u201d at DTW24-Ignite"},"content":{"rendered":"\n

During TM Forum’s annual Digital Transformation World<\/a> (DTW), Huawei, in collaboration with China Mobile, was honored with the “Best Moonshot Catalyst-Attendees’ Choice Award” for their pioneering “GenAI for AN” project. Presented by TM Forum, the Catalyst Awards acknowledge telecom operators and their partners for their contribution to industry innovation. The awards serve as a testament to the ground-breaking work that drives digital transformation in the industry by showcasing best practices.<\/p>\n\n\n\n

The landscape of network architecture has rapidly evolved with the introduction of cloud-native technologies and full convergence, leading to increased complexity and O&M challenges. To address these issues, Huawei and China Mobile have pioneered the use of generative artificial intelligence (genAI) to revolutionize network O&M. This technology significantly improves O&M efficiency, reduces costs, and propels autonomous networks from L3 to L4.<\/p>\n\n\n\n

In a milestone advancement for the core network, Huawei and China Mobile, Zhejiang unveiled the industry’s first multi-modal large model tailored for core network O&M, alongside the ICN Master solution based on the large models. This solution is powered by digital assistants and digital experts. Unlike traditional O&M methods relying on expert experience and multiple tools, this solution integrates seamlessly into operators’ workflows for service rollout, troubleshooting, and complaint handling, revolutionizing interaction modes, O&M processes, system capabilities, and integration approaches. The result is a significant cost reduction and efficiency improvement for operators.<\/p>\n\n\n\n

Illustrating the profound impact of this advancement, the process of complaint handling, which previously required seasoned experts with extensive experience, has now been streamlined through automation. Tasks such as classification, basic analysis, and signaling analysis are automated, enabling the completion of analysis results and ticket filling within a mere 5 minutes. This automation has drastically reduced complaint ticket handling time from 13 to 5 hours, demonstrating remarkable efficiency gains.<\/p>\n\n\n\n

The success of “GenAI for AN” stands as a pivotal benchmark project for global operators seeking to embrace large models. Looking ahead, Huawei remains committed to further exploring the application of genAI in O&M with operators worldwide, with a dedication to launching more intelligent solutions that will facilitate and expedite the digital-intelligent transformation for global operators.<\/p>\n\n\n\n

Image caption: ——- Huawei’s GenAI for AN Wins “Best Moonshot Catalyst – Attendees’ Choice Award”<\/p>\n","protected":false},"excerpt":{"rendered":"

During TM Forum’s annual Digital Transformation World (DTW), Huawei, in collaboration with China Mobile, was honored with the “Best Moonshot Catalyst-Attendees’ Choice Award” for their pioneering “GenAI for AN” project. Presented by TM Forum, the Catalyst Awards acknowledge telecom operators and their partners for their contribution to industry innovation. The awards serve as a testament to the […]<\/p>\n","protected":false},"author":1,"featured_media":3187,"comment_status":"open","ping_status":"open","sticky":true,"template":"","format":"standard","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_uf_show_specific_survey":0,"_uf_disable_surveys":false,"footnotes":""},"categories":[7],"tags":[],"class_list":["post-3186","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-technology"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t