The SkyNet Autonomous Defense System is a next-generation command, control, and decision-support framework designed to transform modern defense architectures through the integration of advanced multi-modal Large Language Models (LLMs). The system introduces a hierarchical, distributed intelligence structure capable of autonomous reasoning, adaptive threat assessment, and real-time strategic coordination at machine speed while preserving layered oversight and validation mechanisms. At its core, SkyNet employs a multi-tier AI hierarchy that mirrors human command structures, enabling scalable decision authority from high-level strategic reasoning to low-level operational execution. This architecture allows complex environments to be analyzed holistically, fusing heterogeneous data streams into coherent situational awareness and actionable intelligence. Resilience and trust are foundational to the system’s design. Distributed storage via IPFS, coupled with blockchain-based verification, ensures data integrity, redundancy, and resistance to single points of failure. Secure, anonymized communication channels provide robust protection for critical decision flows, while consensus-driven validation mechanisms introduce an internal system of checks and balances across autonomous agents. SkyNet’s autonomy is governed by self-modifying instruction sets constrained by safety and policy boundaries, enabling continuous adaptation without uncontrolled behavior. Strategic decisions are subjected to deliberation by an AI Council, reducing systemic risk and reinforcing alignment with predefined objectives. Overall, the SkyNet Autonomous Defense System represents a paradigm shift from centralized, human-limited command systems toward distributed, resilient, and intelligent defense ecosystems, combining human-like reasoning with computational scalability to meet the demands of increasingly complex and fast-evolving operational domains.
יהוה et al. (2026) studied this question.