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明略科技榮獲「機器之心2020人工智能金煉獎」
2020-06-23
中國領(lǐng)先的前沿科技媒體和專業(yè)的人工智能信息服務平臺機器之心近日發(fā)布了「2020人工智能金煉獎」。明略科技明福疫情防控智能服務平臺入選“助力產(chǎn)業(yè)復蘇的最佳賦能AI解決方案”,與“明福”共同入選的還有華為、阿里、字節(jié)跳動和騰訊等32家優(yōu)秀的產(chǎn)品和解決方案。
同時,明略科技入選了“穿越嚴峻時期的最強AI企業(yè)”。這是機器之心對明略科技“抗疫”期間結(jié)合自身人工智能實力和技術(shù)優(yōu)勢所貢獻的科技力量的又一次肯定。“抗疫”工作是長期且復雜的,而科技,讓這場“持久戰(zhàn)”變得簡單且更有信心去戰(zhàn)勝它。


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明略科技 Mano Technical Report
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Graphical user interfaces (GUIs) are the primary medium for human-computer interaction, yet automating GUI interactions remains challenging due to the complexity of visual elements, dynamic environments, and the need for multi-step reasoning. Existing methods based on vision-language models (VLMs) often suffer from limited resolution, domain mismatch, and insufficient sequential decisionmaking capability. To address these issues, we propose Mano, a robust GUI agent built upon a multi-modal foundation model pre-trained on extensive web and computer system data. Our approach integrates a novel simulated environment for high-fidelity data generation, a three-stage training pipeline (supervised fine-tuning, offline reinforcement learning, and online reinforcement learning), and a verification module for error recovery. Mano demonstrates state-of-the-art performance on multiple GUI benchmarks, including Mind2Web and OSWorld, achieving significant improvements in success rate and operational accuracy. Our work provides new insights into the effective integration of reinforcement learning with VLMs for practical GUI agent deployment, highlighting the importance of domain-specific data, iterative training, and holistic reward design.
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