arXiv:2607. 07901v1 Announce Type: cross Abstract: Private blockchain networks run with fixed node configurations that cannot adapt to changing workload conditions.
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The paper investigates when adding a second AI component—an AI supervisor—benefits network‑fraud decision making. Using a role‑aware Decider‑Supervisor framework with blockchain auditability, the authors evaluate four configurations combining centralized ML, federated meta‑models, and large language model variants. Results show that only specific setups (e.g., DS‑4 Base in extreme high‑fraud scenarios) reduce errors, while most supervised configurations either underperform or add operational burden.
arXiv:2607. 20700v1 Announce Type: cross Abstract: The operation of blockchain is governed by consensus algorithms (CA).
The paper reviews 194 papers on using artificial intelligence to optimize data center energy use, coding 63 of them. It finds that most control studies validate only in simulation, none consider water withdrawal or embodied carbon, and savings estimates overlap across methods, preventing ranking. The authors propose CLEAR‑DC, a framework that links control and workload demand through elasticity, reports net benefits, and records energy, carbon, water, embodied share, and validation venue.
arXiv:2607. 24773v1 Announce Type: new Abstract: Managing cloud infrastructure efficiently, especially in environments of large cloud providers or hyperscalers, requires optimizing the use of physical resources to minimize costs and maximize performance.
arXiv:2512. 13666v2 Announce Type: replace-cross Abstract: The security and decentralization of Proof-of-Work (PoW) have been well-tested in existing blockchain systems.
arXiv:2606. 02958v1 Announce Type: cross Abstract: Cross-organization language-model adaptation increasingly faces hard governance constraints: in many deployments, device-level model state-parameters, activations, optimizer state, and per-device updates-cannot be exported outside an administrative boundary.