转自：国际商报 □ 本报记者 刘旭颖 走进2025年中国国际服务贸易交易会的电信、计算机和信息服务专题展区，最直观的感受是机器人几乎 成为每个展台的必备展示项目。 在京东展台，忽闪着萌萌大眼的机器狗边露出羞红脸蛋儿边展示身上"买智能机器人上京东"的文字；过 道上，一位外国参观者正和一个身穿孙悟空迷你京剧装的机器人"较劲"，无论参观者怎么推搡，机器人 都只是稳稳地后退几步再走上前递出手中的金箍棒，这个机器人实际上应用于陪伴、教育领域；在机器 人展位，在世界人形机器人运动会上取得冠军的机器人们集中亮相，身上挂着的奖牌格外闪亮。另一 侧，有的机器人在打太极拳，还有医疗领域的机器人在展示微操。 电信、计算机和信息服务专题展区不仅展示了各种机器人，还有应用于诸多领域的AI大模型。 走进中国铁塔展台，一座高耸的模型塔最先映入眼帘。据展台工作人员介绍，中国铁塔自成立以来，有 力地应对了台风、地震、洪涝等各类自然灾害期间的应急通信。在北京"23·7"特大暴雨期间，中国铁塔 迅速响应，并高质量开展灾后重建工作，在山区等易受灾区域建设应急抗灾超级基站，即使在断电断光 缆情况下，也能提供通信保障。"此外，中国铁塔还建设了气象铁塔站 ...

Core Viewpoint - TaoAvatar is a breakthrough 3D digital human technology developed by Alibaba's Taobao Meta Technology team, enabling real-time rendering and AI dialogue on mobile and XR devices, providing users with a realistic virtual interaction experience [1][8]. Group 1: Technology Overview - TaoAvatar utilizes advanced 3D Gaussian splatting technology to create lifelike full-body avatars that capture intricate facial expressions and gestures, as well as details like clothing folds and hair movement [8]. - The technology significantly reduces the cost and increases the efficiency of digital human modeling, facilitating large-scale applications [9]. - MNN-TaoAvatar is an open-source 3D digital human application that integrates multiple leading AI technologies, allowing natural voice interaction with digital humans on mobile devices [10]. Group 2: Performance Metrics - The application runs efficiently on mobile devices, with key performance metrics for various models as follows: - ASR (Automatic Speech Recognition): Model size 281.65M, RTF: 0.18 - LLM (Large Language Model): Model size 838.74M, pre-fill speed: 165 tokens/s, decode speed: 41.16 tokens/s - TTS (Text-to-Speech): Model size 1.34GB, RTF: 0.58 - A2BS (Audio-to-BlendShape): Model size 368.71MB, RTF: 0.34 - NINIR (Rendering Output): Model size 138.40MB, rendering frame rate: 60 FPS [16][17][18]. Group 3: Development and Optimization - MNN-TaoAvatar is built on the MNN engine, which supports various algorithm modules, enhancing the performance of AI applications in real-time scenarios [23][30]. - The MNN-LLM module demonstrates superior CPU performance, with pre-fill speed improved by 8.6 times compared to llama.cpp and decoding speed improved by 2.3 times [34]. - The MNN-NNR rendering engine employs optimizations such as data synchronization and scheduling to ensure efficient rendering, achieving smooth output at 60 FPS even with lower frequency updates [40][45]. Group 4: Hardware Requirements - Recommended hardware for MNN-TaoAvatar includes devices with Qualcomm Snapdragon 8 Gen 3 or equivalent CPU, at least 8GB of RAM, and 5GB of storage for model files [51].