Engineering Sovereign LLMs: From Data to Deployment Build, Train, Optimize, Secure, and Deploy Large Language Models Under Full Infrastructure Control Engineering Sovereign LLMs: From Data to Deployment is an advanced engineering handbook for designing and operating large language models within infrastructure controlled by the organization that builds them. Rather than treating an LLM as a hosted API or a black-box service, this book examines the complete sovereign AI stack — from raw data acquisition and distributed storage to tokenizer engineering, transformer architecture, large-scale training, post-training alignment, quantization, high-performance inference, security, observability, and production deployment.
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Mastering LLM Quantization: Architecture and Code A Comprehensive Engineering Guide to Low-Precision AI, Quantized Inference, GPU Kernels, and Production Deployment Mastering LLM Quantization: Architecture and Code is a comprehensive technical resource for understanding, implementing, optimizing, and deploying quantized large language models. Combining mathematical foundations with practical engineering techniques, this title explores how reduced-precision representations can significantly improve memory efficiency, inference performance, and hardware utilization while preserving model accuracy.
Modern Browser Fingerprinting: Techniques and CodeBuild a Deep Technical Understanding of How Modern Browsers Reveal Device Identity Browser fingerprinting has evolved far beyond cookies. Modern websites can identify devices using hundreds of signals originating from browser internals, graphics hardware, JavaScript runtimes, network protocols, rendering engines, media subsystems, machine learning models, and operating system artifacts. Even when traditional tracking mechanisms are blocked, browsers continue to expose unique characteristics that can be combined into highly stable device identities.
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Mastering AI Agents: Hands-On Production Code is a practical engineering guide to building autonomous AI agent systems from first principles to production-scale infrastructure. The book focuses on the systems, architectures, and implementation patterns required to move beyond conversational LLM applications and build agents that can reason, use tools, maintain state, interact with other agents, execute code, recover from failures, and operate reliably in real-world environments.
Coding CERN: A Technical Developer's GuideExplore the software, computing architectures, data pipelines, and high-performance systems behind modern high-energy physics. CERN is not simply a physics laboratory. It is one of the world's most demanding computing environments — combining extreme data rates, heterogeneous hardware, distributed storage, high-performance networking, real-time processing, large-scale simulation, machine learning, and scientific software engineering.
High-Performance Real-Time Systems in .NET Engineering ultra-low-latency, high-throughput real-time systems with .NET, WebSockets, SignalR, Kestrel, and distributed architectures. Modern real-time applications are expected to maintain persistent connections, process massive event streams, synchronize distributed state, and deliver predictable latency under extreme concurrency.
Advanced Automation: 50-Chapter Master Script Package The Blueprint for Level 5 Autonomous Enterprise InfrastructureAre you ready to move past fragile ad-hoc scripts and engineer true, self-governing technical autonomy? In high-scale enterprise environments, automation is no longer about writing a quick Bash utility to clear a disk partition. It is about building resilient, self-healing systems that operate at a scale where manual intervention is a fundamental failure of design.
The Local AI Stack: Building a Sovereign Machine Learning Workstation with Hyper-V, WSL2, and GPU Virtualization Renting GPU time from AWS costs more than the GPU. Every prompt you send to a cloud API is a prompt someone else logs. If your ML work runs on hardware you don't own, on a network you don't control, then you don't own your ML work.
Advanced IBM Quantum Computing and Qiskit Architecture: A Strategic Briefing Executive SummaryThe current landscape of quantum computing has shifted from a circuit-centric focus to a workload-centric ecosystem. The modern Qiskit architecture is designed to bridge the gap between idealized mathematical abstractions and the noisy, physical reality of IBM’s superconducting processors (such as the Eagle, Osprey, and Condor).
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Turn AI into a reliable incident-response copilot for Kubernetes. This SmartBook shows you how to combine the speed of AI with the precision of kubectl and jq, so you can investigate production issues faster, verify every claim, and respond with confidence under pressure.
Dive Deep into the Peak of .NET Performance. To truly optimize, you must understand the hardware and the runtime. From benchmarking basics to low-level mastery—reshape the way you write C#.
Master Python through 72 hands-on lessons with 350+ executable code examples. Each example includes QR codes for instant mobile access and live execution—learn by doing, not just reading. From "Hello World" to advanced patterns, this interactive guide transforms beginners into confident Python developers.