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...an Open Source Library, for quantum computing and AI-orchestrated educational repository hosted on GitHub. MACROSLOW is a source for guides, tutorials, and templates to build qubit based systems in 2048-AES security protocol (CONCEPT). Designed for decentralized unified network exchange systems (DUNES) and quantum computing utilizing QISKIT/QUTIP/PYTORCH based qubit systems. It enables secure, distributed infrastructure for peer-to-peer interactions and token-based incentives without a single point of control, supporting applications like Decentralized Exchanges (DEXs) and DePIN frameworks for blockchain-managed physical infrastructure harnessing Qubit based systems and networks. All Files and Guides are designed and optimized for quantum networking and legacy system integrations, with qubit logic. Also includes Hardware guides included for quantum computing based systems (NVIDIA, INTEL, MORE).
PyTorch for machine learning and SQLAlchemy databases for robust data management. Sync them together with Advanced .yaml and .md files for configuration and documentation. Enabling for Multi-stage Dockerfile deployments for scalable setups and $custom web3 .md wallets and tokenization for flexible, secure transactions.
MACROSLOW provides a collection of tools and agents for developers to fork and build upon as boilerplates and OEM templates
DUNES serves as the baseline minimalist SDK. DUNES offers a set of 10 core files for building a hybrid Model Context Protocol (MCP) server with MAML processing and MARKUP Agent functionality. It enables quantum-distributed workflows with verifiable OCaml-based algorithms, hybrid multi-language orchestration (Python, Qiskit), and integration with MCP servers.
CHIMERA 2048 is a quantum-enhanced, maximum-security API gateway for MCP servers, powered by NVIDIA’s advanced GPUs. Featuring four CHIMERA HEADS—each a self-regenerative, CUDA-accelerated core with 512-bit AES encryption—it forms a 2048-bit AES-equivalent security layer.
Hybrid Cores: Two heads run Qiskit for quantum circuits (<150ms latency), and two use PyTorch for AI training/inference (up to 15 TFLOPS). Quadra-Segment Regeneration: Rebuilds compromised heads in <5s using CUDA-accelerated data redistribution.
MAML Integration: Processes .maml.md files as executable workflows, combining Python, Qiskit, OCaml, and SQL with formal verification via Ortac. Security: Combines 2048-bit AES-equivalent encryption, CRYSTALS-Dilithium signatures, lightweight double tracing, and self-healing mechanisms. NVIDIA Optimization: Achieves 76x training speedup, 4.2x inference speed, and 12.8 TFLOPS for quantum simulations and video processing.
CHIMERA 2048 supports scientific research, AI development, security monitoring, and data science, with deployment via Kubernetes/Helm and monitoring through Prometheus.
The GLASTONBURY 2048 Suite SDK is a qubit based medical and science research library that accelerates AI-driven robotics and quantum workflows, leveraging NVIDIA’s Jetson Orin and Isaac Sim.
MAML Scripting: Routes tasks via MCP to CHIMERA’s four-headed architecture (authentication, computation, visualization, storage). PyTorch/SQLAlchemy: Optimizes neural networks and manages sensor data for real-time control. NVIDIA CUDA: Accelerates Qiskit simulations for trajectory and cooling optimization in ARACHNID and other applications. Applications: Autonomous navigation, robotic arm manipulation, and humanoid skill learning, optimized for CUDA-enabled GPUs.
PROJECT ARACHNID, the Rooster Booster, is a quantum-powered rocket booster system designed to enhance SpaceX’s Starship for triple-stacked, 300-ton Mars colony missions by December 2026. Integrated with the DUNES SDK, ARACHNID features eight hydraulic legs with Raptor-X engines, 9,600 IoT sensors, and Caltech PAM chainmail cooling, orchestrated by quantum neural networks and MAML workflows.
The DUNES SDK leverages NVIDIA’s hardware ecosystem for robotics, AI, and quantum-classical computing. It supports: Jetson Orin (Nano, AGX Orin): Up to 275 TOPS for edge AI, enabling real-time robotics/IoT with sub-100ms latency. A100/H100 GPUs: Up to 3,000 TFLOPS for AI training, quantum simulations, and data analytics. Isaac Sim: GPU-accelerated virtual environments for robotics validation, reducing deployment risks by 30%. cuQuantum SDK/CUDA-Q: Quantum algorithm simulation with 99% fidelity for quantum key distribution and variational algorithms. Guides cover hardware setup, CUDA/Tensor Core optimization, and integration with DUNES’ .MAML.ml pipelines for secure, quantum-resistant workflows.
MARKUP Agent: Modular PyTorch-SQLAlchemy-FastAPI micro-agent for Markdown/MAML processing. Introduces Reverse Markdown (.mu) syntax for error detection, digital receipts (e.g., word mirroring like "Hello" to "olleH"), shutdown scripting, recursive ML training, quantum-parallel processing, and 3D ultra-graph visualization with Plotly. Supports API endpoints, Docker deployment, and use cases like MAML validation and workflow integrity for ARACHNID’s quantum workflows.
BELUGA Agent: Bilateral Environmental Linguistic Ultra Graph Agent for extreme environments. Fuses SONAR/LIDAR data via SOLIDAR™ into quantum-distributed graph databases, optimized for NVIDIA Jetson platforms and DGX systems. Applications: subterranean exploration, submarine operations, IoT devices, and ARACHNID’s sensor fusion.
Sakina Agent: Adaptive reconciliation agent for conflict resolution in multi-agent systems. Handles data harmonization, ethical decision-making, and bias mitigation in federated learning, running on NVIDIA Jetson Orin for human-robot interactions like assistive caregiving.
Chimera Agent: Hybrid fusion agent combining classical and quantum data streams into unified models, using NVIDIA CUDA-Q and cuQuantum for quantum-enhanced machine learning. Achieves 89.2% efficacy in novel threat detection with adaptive reinforcement learning. Supports cross-domain simulations like ARACHNID’s interplanetary dropship coordination.
Infinity TOR/GO Network: Ensures anonymous, decentralized communication for robotic swarms, IoT systems, and quantum networks, leveraging Jetson Nano and DGX systems. A concept network under development using the TOR and GO file systems for lightweight seamless emergency backup networks and data storage.
MACROSLOW 2048-AES introduces the MAML (Markdown as Medium Language) protocol, a novel markup language for encoding multimodal security data. It features:
.MAML.ml Files: Structured, executable data containers validated with MAML schemas
Dual-Mode Encryption: 256-bit AES (lightweight, fast) and 512-bit AES (advanced, secure) with CRYSTALS-Dilithium signatures
OAuth2.0 Sync: JWT-based authentication via AWS Cognito
Reputation-Based Validation: Customizable token-based reputation system
Quantum-Resistant Security: Post-quantum cryptography with liboqs and Qiskit
Prompt Injection Defense: Semantic analysis and jailbreak detection
Markdown as Medium Language: A protocol that extends the Markdown (.md) format into a structured, executable container for agent-to-agent communication.
.maml.md: The official file extension for a MAML-compliant document. MAML Gateway: A runtime server that validates, routes, and executes the instructions within a MAML file.
Desgined for MCP (Model Context Protocol): A protocol for tools and LLMs to communicate with external data sources. MAML is the ideal format for MCP servers to return rich, executable content.
Examples of Front Matter: The mandatory YAML section at the top of a MAML file, enclosed by ---, containing machine-readable metadata.
Examples of Content Body: The section of a MAML file after the front matter, using structured Markdown headers (##) to define content sections.
Features Signed Execution Ticket: A cryptographic grant appended to a MAML file's History by a MAML Gateway, authorizing the execution of its code blocks.
a library to empower developers to create secure, oauth 2.0 compliant applications with a focus on quantum-resistant, adaptive threat detection.
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