The article dissects Claude Code’s Harness layer, detailing its five core components, four‑layer defense strategy, guiding principles, and a step‑by‑step refactoring workflow that together turn a language model into a safe, controllable AI coding partner.
This article highlights two cutting‑edge works from Ant Group’s research team—HAWK, a fixed‑word key decomposition switching accelerator that overcomes hardware challenges for FHE, and FHEFusion, a compiler framework that introduces operator fusion to dramatically speed CKKS‑based DNN inference—showcasing their designs, optimizations, and experimental gains.
The article examines the emerging AI Super Node ecosystem, detailing its core concepts, four‑layer architecture, key enabling technologies, current challenges such as compatibility and energy consumption, and future directions like quantum‑classic hybrids and green low‑carbon designs, illustrating how it overcomes scaling bottlenecks in modern AI deployments.
This article introduces two Ant Group papers selected for NDSS 2025—Rondo, a scalable, reconfiguration‑friendly distributed randomness beacon for blockchain‑type systems, and BumbleBee, a communication‑efficient two‑party inference framework that protects privacy for large Transformer models.
JD Digital Science introduced its fast secure federated learning framework, highlighted two pioneering technologies—a kernel‑based nonlinear federated learning algorithm and a distributed fast homomorphic encryption method—both accepted at KDD 2020, and discussed their industrial applications, privacy benefits, and regulatory relevance.
