Artificial Intelligence

In a world of infinite AI-generated text, fluency is no longer a credential—trust is. Learn how to engineer "signal" into your technical writing and build an authoritative presence that algorithms can't replicate. This is the definitive practitioner’s guide for publishing in the AI era.

Most books about ChatGPT explain the magic. This one shows you the math. Inside Large Language Models, Volume I takes a curious beginner from "what is an LLM" to a complete, trained GPT, with nothing more than high-school algebra, a working laptop, and a willingness to read carefully. Every formula is walked through by hand. Every line of code comes with a plain-English explanation. By the end you will have built, trained, and run your own transformer from scratch, and you will know exactly what is happening inside. No PhD or Data Science required. No prior machine learning needed. Just curiosity and a calculator.

Stop being a data-entry clerk for a machine that never sleeps and start leading your own digital workforce. The CEO of One is the definitive roadmap for reclaiming your time and human advantage by shifting from an exhausted "User" to a high-powered "Director." Learn to command your personal army of AI agents and master the Agentic Era before it masters you.

Master the "Last Mile" of AI engineering to ship world-class apps to the App Store. Optimize the Neural Engine, manage thermal limits, and conquer the Jetsam mechanism. Navigate iOS 18 privacy manifests and implement premium monetization with StoreKit 2. Transform stochastic AI models into deterministic, compliant, and highly profitable products.

Build a "Second Brain" for your apps by mastering SwiftData, CloudKit synchronization, and persistent AI memory. Implement hardware-accelerated vector search and HNSW indexing for lightning-fast retrieval of semantic embeddings. Architect thread-safe, GDPR-compliant data layers using Swift 6 actors and advanced privacy-preserving strategies. Scale from local prototypes to production-grade distributed intelligence with definitive Apple ecosystem blueprints

Master AI integration on Apple platforms by bridging Swift 6 with OpenAI, LangChain, and autonomous agents. Build high-performance RAG pipelines using hardware-accelerated vector math and persistent local semantic memory. Architect thread-safe, real-time apps with strict concurrency, intelligent function calling, and efficient token streaming. Move from basic API calls to production-grade intelligence with the definitive guide for modern Apple developers.

Navigate the architectural discontinuity of the Foundation Model Era with this comprehensive guide designed for professionals sitting at the intersection of technology and leadership. Master the intersection of technical precision and strategic oversight through the RACE framework, robust ethical principles, and the operational realities of MLOps. From the legal mandates of the EU AI Act to the emerging risks of agentic AI, this guide empowers you to lead AI transformation with intention and accountability.

Master the definitive fusion of Swift 6 and Spatial AI to architect the future of visionOS. Leverage LiDAR, Core ML, and real-time hand tracking to build apps that truly understand reality. From persistent world-locking to RealityKit ECS, implement the blueprints of professional 3D engineering. Go beyond basic windows—design immersive, intelligent experiences ready for the visionOS App Store.

Stop building chatbots and start building agents that interact directly with the Android OS. Master Gemini Nano and AICore to architect autonomous systems that see, think, and take action. Implement production-ready Tool Calling, Screen Awareness, and the ReAct loop using Kotlin 2.x. Move beyond the API call—embrace the Agentic Era and build the future of mobile intelligence.

Master high-performance Edge AI by orchestrating NPUs, GPUs, and DSPs for real-time mobile intelligence. Run complex models at 60 FPS using advanced quantization, weight pruning, and NDK optimization. Leverage Kotlin 2.x and zero-copy pipelines to build battery-efficient and thermally stable AI features. The definitive engineering guide for shipping the "last mile" of AI deployment on modern Android SoCs.

AI can write code faster than any human can review it. That changes the economics of engineering, but not what engineering is for. The bottleneck has moved from building to judging —and judgment cannot be prompt-engineered into a system designed for cheap proposals.

Most books about ChatGPT explain the magic. This one shows you the math. Inside Large Language Models, Volume I takes a curious beginner from "what is an LLM" to a complete, trained GPT, with nothing more than high-school algebra, a working laptop, and a willingness to read carefully. Every formula is walked through by hand. Every line of code comes with a plain-English explanation. By the end you will have built, trained, and run your own transformer from scratch, and you will know exactly what is happening inside. No PhD or Data Science required. No prior machine learning needed. Just curiosity and a calculator.

A practical handbook for building deterministic, auditable AI pipelines with safety gates, capability profiles, audit trails, telemetry and production deployment patterns.

The era of cloud-only AI is over. Transition from calling remote APIs to building on-device brains using Gemini Nano, local LLMs, and private RAG pipelines.Master the hardware orchestration and Kotlin architecture needed for privacy, zero latency, and production-grade mobile intelligence.Stop being just a developer—become an Android AI Engineer and lead the 2026 mobile revolution today!