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A coder from Limerick saw He could pass off work to OpenClaw So he said, with a wink, "I'll go get a drink." And he left shouting "AI go braugh!"
New MEAP! Evaluation and Alignment, The Seminal Papers
It's a fundamental truth that all software—even AI systems—is broken. AI engineers who can diagnose faults and refine systems to align with business needs are in high demand. Evaluation and Alignment, The Seminal Papers expands the foundational research into judging and adapting AI systems into a collection of practical techniques you can use on the job.
Inside, you'll learn:
BLEU, ROUGE, BERTScore, COMET, and LLM-as-a-judge methods
Detecting and quantifying hallucinations
Aligning AI with RLHF, constitutional AI, and red teaming
Timeless best practices that will apply as models evolve
And much more!
As you trace the progression from surface-level text matching, to semantic similarity, to judgment-based evaluation, you'll build the mental models necessary to choose the right metrics, detect failure modes, and close the loop from evaluation to alignment. You'll employ a "working backwards" methodology that begins with what your system must get right, which directs you to the appropriate evaluation approach. As you internalize the define > evaluate > analysis > align cycle, you'll start making more informed tradeoffs, and expertly balancing helpfulness, safety, and brand voice in your models. [Read more]
Go inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you'll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant. [Read more]
LLM reasoning models have the power to tackle truly challenging problems that require finding the right path through multiple steps. This book demystifies how these complex models work with a simple philosophy: the best way to learn how something works is to build it yourself! You'll begin with a pre-trained LLM, adding and improving its reasoning capabilities in ways you can see, test, and understand. [Read more]
7 chapters of this MEAP are available now, with more to follow soon!
When you need a language model to respond accurately and quickly about a specific field of knowledge, the sprawling capacity of a LLM may hurt more than it helps. This book teaches you to build generative AI models optimized for specific fields. You'll learn to minimize the computational horsepower your models require, while keeping high–quality performance times and output. [Read more]
This book teaches you to design reliable LLM-powered systems by focusing on the concepts, architectures, and design patterns that will stay stable even as models and APIs change. You'll learn to structure prompts, compose modular chains, and build RAG pipelines that ingest documents, split them into chunks, embed them, retrieve the right context, and ground answers to eliminate (or vastly reduce) hallucinations. [Read more]
AI is transforming the world faster than we could have imagined. But how did we get here? AI guru Ilya Sutskever made the bold claim that most of what you need to know about modern AI is captured in 30 seminal research papers on deep learning. In this one-of-a-kind book, AI expert Rich Heimann dives into each of these influential and vitally-important papers, revealing the breakthroughs that shaped Ilya's thinking and the entire AI field. [Read more]
Need a fast, reliable SQL-compliant RDBMS? Just use Postgres! Need to work with geospatial data? Just use Postgres! Handling semi- or non-structured documents? Just use Postgres! Generative AI embeddings? You've got it—just use Postgres! Written for software engineers and database pros, this book shows you how to get the most out of the powerful PostgresSQL database. [Read more]
LLM-powered AI agents are the next leap in applied AI, capable of reasoning and collaboration to achieve even complex, multi-step goals. Using new protocols like MCP and A2A, agents can use software tools, retrieve relevant knowledge, and adapt to feedback. This book guides you step by step in creating an AI agent from the ground up, with clear, detailed explanations you can follow to build your own custom assistants! [Read more]
Put the power of deep learning in your hands! This new edition of the bestseller includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python. [Read more]
Agents turn LLMs into autonomous tools capable of executing on tasks and plans. Multi-agent systems use protocols like MCP and A2A to upgrade the power of a single AI agent with both a collaborative AI team. In this book, you'll learn how to construct one of these dynamic, powerful, and effective systems from the ground up. [Read more]
3 chapters of this new MEAP are available now, with more to follow soon!
When DeepSeek started making waves in January 2025, it sounded too good to be true. How could a generative AI model get such incredible performance with such low training and operation costs? In this guide, you'll find out exactly how DeepSeek works by recreating a laptop-scale version of this cutting-edge model yourself! [Read more]
Manning Online Pro Annual subscription—Just $199.99!
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