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New MEAP! GPU Programming with Triton
Until recently, writing GPU kernels for LLM training and inference meant learning low-level programming tools like CUDA and C++. Triton, an open-source, Python-based DSL created by OpenAI, bridges the gap between high-level machine learning frameworks and low-level GPU programming. Triton is built into PyTorch 2 and backed by NVIDIA, Intel, AMD, and Red Hat.
In GPU Programming with Triton, author Harshwardhan Fartale introduces Triton’s innovative block-level programming model that replaces the tedious manipulation of low-level threads required by CUDA. Written for the latest
hardware and LLMs, this book teaches GPU programming and Triton together, in Python, by profiling real workloads, identifying bottlenecks, and understanding why each optimization (coalescing, tiling, shared memory, reductions, and fusion) actually works! [Read more]
4 chapters of this new MEAP are available now with more to follow soon!
AI systems using large models like GPT or Gemini can produce impressive results across an astounding range of subjects and domains. In areas like clinical coding, legal contract review, financial due diligence, fraud detection, compliance monitoring, and other specialized business or technical disciplines, however, broad general ability is far less important than efficient output that can be trusted, audited, and controlled.
Building Specialized AI Systems puts working code in front of you and walks through practical implementations step by step. Complete real-
world projects connect these techniques from design to deployment, showing how specialized models can be applied to practical industry problems and giving you reusable patterns for your own AI systems. Along the way, you'll work with the modern fine-tuning ecosystem, including open-source and commercial platforms and tools used to train, evaluate, deploy, and operate specialized language models. [Read more]
3 chapters of this new MEAP are available now with more to follow soon!
New MEAP! Clean Applications with Hexagonal Architecture
Modern architectural styles like “hexagonal,” “clean,” and “onion” all share a straightforward principle: business logic should sit at the center of your software, free of frameworks, databases, user interfaces, and external services. The tricky bit comes when you start putting these ideas into practice when you’re refactoring a legacy enterprise mudball, implementing microservices, or building a “modulith” in Spring. Clean Applications with Hexagonal Architecture: Building maintainable microservices and modular monoliths guides you from the hexagonal architecture at the core of modern enterprise software to its practical implementation with examples in Java and Spring Boot.
If you’ve ever stared at a class and asked “where does this code belong?” Clean Applications with Hexagonal Architecture ends the guesswork. Author Enrique Medina Montenegro shows you how to take advantage of an architecture that gives every class exactly one reason to exist and one place to live. You’ll learn to handle input ports, an orchestrating application layer, a domain layer with enforced invariants, and output ports to infrastructure. Finally, you’ll assemble the full structure, then lock it down with ArchUnit rules, and extend this foundation into modular monoliths and microservices. [Read more]
6 chapters of this new MEAP are available now with more to follow soon!
A hands-on guide to designing and building effective digital twins. In it, you’ll build a home-scale digital twin from the ground up. You’ll start with a framework for gathering requirements to ensure that what you deliver is perfectly suited to your needs. You’ll then work through the complete project step-by-step—from setting up sensors, to handling hardware, to working with embedded software. [Read more]
Bestselling author Jungjun Hur and AI expert Younghee Song guide you through creating a complete research assistant agent framework. You’ll learn how agents function under the hood—all without hidden abstractions, black boxes, or framework lock-in. You will implement each piece as you develop a mental model of how agents really work. [Read more]
Written for everyone! Following engaging illustrations and step-by-step guidance, you'll start creating AI applications from the very first chapters. Use prompt engineering to create a healthy recipe generator, use RAG to build automated customer support chatbots, craft marketing assistants that know brand guidelines, and even design a web-enabled financial researcher—all using free low-code tools like Langflow and KNIME. [Read more]
Vanilla Web >> Chapter 10, “Navigation” & Chapter 11, “Building a Router” >> Chart a course through the coordination between the URL, the browser, the server, and the application, as you foray into the topic of navigation and routing, which is usually approached as a client-side concern but is broader than that in real-world web projects.
practical guide are now available, along with a glowing foreword from Angie Jones, VP of Developer Experience at the Agentic AI Foundation! Want to discover additional sources of context that enable agent behavior? You’re covered. Interested in the discipline of selecting, writing, compressing, and isolating context? You’ve got it. Ready to delve into the mechanisms that keep the core context components aligned with the application objective? Analyze the governance and operational components? Get a practical view of context engineering in one of its most important application domains? Check, check, and check. It’s all there and much more too. So, go ahead and have a crash-course weekend, or take it slower knowing the next chapter is there for you as soon as you’re ready. The choice is yours!
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