Daily curates a variety of tech resources, tools, tips, and news (5G, big data, cloud computing, AI), aiming to become a go-to popular science encyclopedia for everyone.
The article argues that 5G-A's industrial value lies not in faster network speeds but in embedding connectivity into business processes to enable real-time data assets, closed-loop operations, and AI-driven decisions, requiring integration of network, data, platform, and security capabilities.
This article explains why software supply chain security matters, detailing how risks originate from third-party components, outsourcing, and opaque delivery pipelines, and outlines four critical inventories—systems, suppliers, software components, and risk responses—that organizations must align to achieve traceable, verifiable, and accountable software assets.
This article argues that the real risk of AI agents lies not in their intelligence but in their ability to execute actions, requiring organizations to establish governance frameworks covering identity, permissions, decision boundaries, human oversight, and rollback mechanisms before deploying agents in critical workflows.
The article explains why many threat intelligence platforms generate noise instead of actionable clues, proposing a four-layer operational model (data, matching, judgment, action) and a risk-prioritization framework (exposure, exploitability, impact, actionability) to bridge the gap between raw IOCs and effective security response.
This article argues that unreliable enterprise AI Q&A systems stem from poor knowledge governance — not model limitations — and outlines five essential questions a trustworthy knowledge base must answer: source traceability, version validity, applicability scope, ownership, and error correction loops.
China's 2026 regulation on government mobile apps shifts focus from reducing app counts to enforcing full lifecycle management and clear responsibility across five dimensions — entrance, responsibility, data, security, and experience — to eliminate ineffective digital actions that burden grassroots workers and citizens.
China's new draft national standard for automated network data collection tools shifts focus from technical feasibility to explainable compliance, requiring organizations to define collection boundaries, purpose, impact, and audit trails across the entire data lifecycle, especially for AI training data.
The article argues that traditional vulnerability management assumes accurate asset inventories, but modern dynamic environments create unknown exposure points. Asset exposure surface management continuously discovers external-facing assets, maps ownership, assesses risk context, and aligns remediation with business priority, as emphasized by CISA and NIST frameworks.
This article analyzes how government AI assistants are evolving from simple Q&A tools into controlled process collaborators, examining the layered capabilities required, the critical need for authoritative knowledge governance, risks of formalism, and why the future lies in 'controlled collaboration' agents that reduce friction without replacing human judgment.
The article argues that RPA remains relevant as AI agents emerge, but responsibility boundaries in process automation must be redesigned—combining RPA for stable execution, workflows for state tracking, agents for unstructured reasoning, and humans for critical approvals—to ensure accountability, auditability, and controlled execution in serious business contexts.
