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JD Retail Technology
JD Retail Technology
May 19, 2025 · Artificial Intelligence

How JD’s Omniforce Boosts Large Model Efficiency with Cloud‑Edge Collaboration

The JD Exploration Institute paper introduces Omniforce, a human‑centered, cloud‑edge collaborative AutoML system that uses model distillation, dynamic data governance, Bayesian‑optimized training, and edge deployment to cut large‑model training costs by 70% and improve inference speed by 30%, powering the JoyBuild platform for broader AI adoption.

AI EfficiencyAutoMLJoyBuild
0 likes · 6 min read
How JD’s Omniforce Boosts Large Model Efficiency with Cloud‑Edge Collaboration
JD Tech
JD Tech
May 15, 2025 · Artificial Intelligence

How JD’s Omniforce Cuts Large‑Model Training Cost by 70% and Boosts Inference Speed 30%

The paper "Omniforce" from JD Exploration Research Institute presents a cloud‑edge collaborative AutoML system that uses model distillation, data governance, Bayesian training optimization, and cloud‑edge cooperation to reduce large‑model training costs by 70% and improve inference efficiency by an average of 30%, offering a reusable technical paradigm for scalable AI deployment.

AI EfficiencyJoyBuildcloud‑edge computing
0 likes · 6 min read
How JD’s Omniforce Cuts Large‑Model Training Cost by 70% and Boosts Inference Speed 30%