Abstract
Who Will Secure the Next Generation of AI? The U.S.–China Technology Race Beyond Frontier Models and Advanced Chips
From Model Distillation to Hardware-Enforced Output Control, Sovereign AI Infrastructure and Protected Accelerator Computing
Technical Subtitle: How Execution-Finality Architectures Could Strengthen Frontier AI Model Protection, Prevent Unauthorized Industrial-Scale Capability Extraction, Secure AI Accelerators and Support Trusted Sovereign Computing Across American, Chinese and Global Technology Ecosystems.
Foundational International Patent — THE DAS PROTOCOLS
Mothership Application: PCT/IB2026/055615 International Filing Date: 4 June 2026 International Publication: WO 2026/150382 A2 Publication Date: 16 July 2026 Official WIPO Reference: https://patentscope.wipo.int/search/en/detail.jsf?docId=WO2026150382
Summary:
The intensifying technological competition between the United States and China is reshaping the global artificial intelligence industry. Beyond developing increasingly capable frontier models and advanced semiconductors, technology companies face growing challenges involving unauthorized AI model extraction, large-scale behavioral distillation, protection of proprietary reasoning capabilities, accelerator-output security, confidential computing and sovereign AI infrastructure.
Conventional security mechanisms—including API rate limits, anomaly detection, access controls, model watermarking, secure enclaves and network monitoring—provide important safeguards but do not necessarily bind every high-value AI output or accelerator operation to an independently protected release authorization.
This technical disclosure examines how the hardware-rooted execution-finality architecture associated with THE DAS PROTOCOLS, foundationally referenced to international patent application PCT/IB2026/055615, filed on 4 June 2026 and published as WO 2026/150382 A2 on 16 July 2026, could contribute to a complementary security layer for frontier AI systems and next-generation computing infrastructure.
The examined embodiments introduce protected model-output finality, extraction-budget enforcement, adaptive behavioral fingerprinting, destination-bound capabilities, accelerator-output authorization, protected latent-state decoding, memory-effectuation controls and sovereign computing governance.
Particular emphasis is placed on Embodiment 110, addressing unauthorized model capability extraction; Embodiment 111, addressing accelerator-output finality; and Embodiment 112, addressing sovereign accelerator fabrics and confidential AI factories. Complementary embodiments extend these principles to protected reasoning artifacts, memory transfers, jurisdictional handovers, training-data governance and hardware-level data release.
The central technical proposition is that an AI system's ability to compute valuable information should remain distinguishable from its authority to release, export or make that information externally effective.
For American and Chinese technology providers alike, such architectures could offer additional mechanisms for protecting proprietary AI capabilities, securing high-value accelerator workloads and supporting trusted AI infrastructure. Their potential benefit is particularly relevant to reducing unauthorized extraction at industrial scale, rather than claiming that all model distillation can be prevented.
This analysis adopts a technology-neutral perspective, recognizing that both ecosystems have legitimate interests in intellectual-property protection, secure computing, responsible AI development and international interoperability.
The described mechanisms represent prospective technical applications. Their effectiveness, patent support, commercial feasibility and advantages over existing security technologies require independent verification.
Big Tech Industry Relevance
United States and Allied Technology Ecosystems
OpenAI · Anthropic · Google DeepMind · Microsoft · NVIDIA · Meta · xAI · AMD · Intel · Amazon Web Services · Qualcomm · Oracle
Potential applications: Frontier-model capability protection, anti-distillation enforcement, confidential AI inference, protected reasoning-output release, GPU security, accelerator egress authorization and sovereign cloud infrastructure.
China and Associated Technology Ecosystems
DeepSeek · Alibaba · Qwen · Huawei · Tencent · ByteDance · Doubao · Moonshot AI · Kimi · Zhipu AI · GLM · MiniMax · Baidu · Cambricon
Potential applications: Protection of proprietary language models, domestic AI accelerator security, protected model-serving environments, trusted cloud infrastructure, sovereign computing governance and authorization-controlled data release.
Core Industrial Significance
The architecture could support a transition from conventional AI security based primarily on monitoring, software restrictions and access-control policies toward protected enforcement at the actual points of model-output release, accelerator data transfer and external effectuation.
This prospective direction is relevant to both established frontier-model providers and emerging AI infrastructure manufacturers, without implying that any named company has adopted or endorsed the technology.
Keywords
AI Security, U.S.–China AI Competition, Frontier AI, Anti-Distillation, Model Extraction, Execution Finality, Hardware-Rooted Security, Protected AI Outputs, GPU Security, AI Accelerators, Sovereign AI, Confidential Computing, Behavioral Fingerprinting, Extraction Budgets, Zero Trust, AI Infrastructure, DAS Protocols, PCT/IB2026/055615, WO2026150382.
AI-Generated Summary Disclaimer: This abstract and industry-relevance analysis are AI-generated and based on applicant-provided technical disclosures. All patent details, embodiment support, technical claims, company relevance and proposed advantages must be independently cross-checked against the original WIPO publication and authoritative sources. The foundational PCT reference does not establish that every subsequently described embodiment was present in the application as originally filed. References to companies indicate potential relevance only, not adoption, endorsement, infringement or wrongdoing.
Creative Commons License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License
Recommended Citation
Das, Sangam Kumar, "The U.S.–China AI Technology War Is No Longer Just About Who Builds the Best Models — It is Who Controls Their Outputs, Chips and Sovereign AI Infrastructure.", Technical Disclosure Commons, ()
https://www.tdcommons.org/dpubs_series/12990