Domestic AI Systems Advance Toward Secure and Controllable Foundation

People's Daily reported that advancing artificial intelligence requires building upon an independent, controllable, secure, and trusted technical foundation. Whether a system operates stably, keeps data safe, bases its determinations on evidence, and allows traceability when issues arise determines if artificial intelligence can deliver value at scale. Achieving independent control ensures initiative in technological development by coordinating chips, frameworks, models, and practical applications. Recent collaborative innovations across domestic software and hardware sectors have established full-pipeline large model training and inference powered entirely by domestic computing power, creating favorable conditions for building an internationally competitive large model ecosystem. Security and reliability must also be embedded directly into product designs and business processes. Systems require clear definitions detailing which data can be retrieved, which operations need manual confirmation, which judgments demand review by qualified professionals, and how to trace unexpected problems back to their sources. In practical deployments, the iFLYTEK smart medical assistant has expanded to cover more than 800 districts and counties domestically. Rather than replacing doctors, the system assists diagnoses and flags risks using clear evidence-based medicine, while educational implementations support homework grading and student performance tracking under strict information protection.

Adapting tools to complex environments, such as factory workers running equipment or surgeons conducting operations via voice commands, demands resolving interference from background noise, regional dialects, and multiple speakers. Integrating perception, interaction, models, and physical terminals transforms conversational tools into effective workplace assistants.