Large language models

Explore the Future of AI-Powered RoboticsDiscover how Artificial Intelligence is transforming robots into intelligent machines capable of learning, seeing, communicating, navigating, and making decisions. Explore Machine Learning, Computer Vision, NLP, Deep Learning, autonomous systems, smart factories, healthcare robots, drones, humanoids, agricultural robotics, ethics, and future trends.

Go beyond basic prompting and learn how to get reliable, high-quality results from Claude Opus 5.5. This practical guide shows you how to structure instructions, manage context, break down complex work and verify outputs across coding, research, analysis, writing and automation.

GPT-6 Astra changes the way prompting works. This practical guide explains what makes it different, why old techniques can fail and how to write prompts that deliver reliable results. Learn how to build, refine and troubleshoot prompts while finding the right balance between control and autonomy.

Go beyond calling transformer libraries and learn what actually happens under the hood. Starting from first principles, this book builds transformers from scratch with NumPy and PyTorch, then takes you through training, optimization and production inference. Along the way, you’ll work through the math, code and practical techniques behind modern transformer systems.

The field manual for solo builders shipping products with autonomous AI agents. Real systems, real receipts, honest limits.

Agentic AI is everywhere, but what does it actually mean? This book cuts through the hype and explains how AI agents work, how they are built and where they can go wrong. Starting from the basics, it gives you a clear, practical understanding of the technology and what it takes to trust an agent in the real world.

Nine small LangGraph agents, each adding one guardrail: PII, financial actions, risk routing, human approval, memory, retrieval, plans, output and cumulative limits. Plain Python, fully tested, no theory.

This book shows you how.What you'll be able to do:Say what one resolved ticket, generated report, or active customer actually costs youFind where the money goes in a real system, in about an hourCut your bill by 40% to 70% without making the product worse, and prove it didn'tStop a code change from tripling your costs before it shipsWalk into a budget meeting with a number and an argument instead of an apologyWhat's inside: sixteen chapters. Measure what you're paying for. Apply six levers, ordered by how much they pay back. Then keep the savings from creeping away, which is the part that decides whether any of this survives the year.

AI is changing how we work, learn and live, but understanding it does not have to be complicated. This practical guide explains how modern AI and LLMs work, what they can do, where they fall short and how to use them effectively without the hype.

Stop guessing at prompts. This visual workbook gives you 50 ready-to-run workflows, command cheatsheets, and debugging checklists for Claude Code, Cursor, and GitHub Copilot — so you can open any page and immediately know what to type.

​A system-first engineering guide to building, deploying, operating, and securing production-grade Kubernetes clusters, cloud-native platforms, and AI inference workloads.

Written for people who never asked to become AI users and now are. Not a tour of the technology, but a practical guide to working with it well — the habits that make good results repeatable, and the judgement to know when to check.

AI models do not have to be huge, slow or expensive. Distilling Intelligence explores how to build smaller models that perform at scale, then secure the APIs that serve them. From compression and distributed serving to extraction attacks, observability and incident response, this book covers what it takes to run AI reliably in the real world.