The article examines how SpaceX’s software teams—covering flight control, enterprise information systems, ground launch‑pad software, and avionics testing—use a diverse tech stack to ensure real‑time reliability, illustrating that rockets rely on both fuel and code to reach orbit.
The paper introduces a real‑time controllable, multi‑objective re‑ranking framework for Taobao’s feed recommendation that combines actor‑critic reinforcement learning with hypernetworks to instantly adjust objective weights, handling diverse media and cold‑start constraints while delivering higher click‑through, diversity, and cold‑start ratios with only 20‑25 ms latency.
This article presents a comprehensive study of a controllable multi‑objective re‑ranking model for Taobao's information‑flow recommendation, detailing the challenges of complex feed scenarios, three modeling paradigms (V1‑V3), an actor‑critic reinforcement learning framework with hypernet‑generated weights, and extensive online evaluation results.
The Hierarchically Constrained Adaptive Ad Exposure (HCA2E) framework treats each user request as a knapsack item and uses a hierarchical greedy‑plus‑beam‑search optimization with a preservation‑order strategy to jointly maximize platform revenue and user experience while respecting global and per‑request ad‑placement constraints, achieving near‑optimal performance and stable, scalable results in extensive offline and online feed‑advertising experiments.
This article systematically introduces NetEase's edge computing implementation, covering its architecture, core modules such as Hub, Compute Engine, and Edge Services, the cloud‑edge collaboration mechanisms, and detailed industrial and campus use cases demonstrating real‑time control, data privacy, and AI integration.
