在人工智能与边缘计算深度融合的今天，将AI模型高效部署于终端设备已成为产业智能化的关键。本文将分享基于米尔MYD-LR3576边缘计算盒子部署菜品识别安卓Demo的实战经验。该设备凭借其内置的强劲瑞芯微RK3576芯片，为视觉识别模型提供了充沛的本地AI算力，成功将“智慧识菜”的能力浓缩于方寸之间，充分证明了其作为边缘AI应用坚实载体的卓越性能与可靠性。

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研究结果表明，与「脑腐」相关的认知能力下降，不易通过标准的微调技术得到缓解。即使在进行了大量的指令微调或在高质量对照数据上进行了后期持续预训练之后，模型仍然表现出它们最初接触过的垃圾数据所带来的残留影响。

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