Generative AI in C++: Coding Transformers by David Spuler (.ePUB)+

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Generative AI in C++: Coding Transformers and LLMs by David Spuler
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Overview: Do you know C++ but not AI? Do you dream of writing your own AI engine in C++? From beginner to advanced, this book covers the internals of AI engines in C++, with real source code examples and research paper citations. As a programmer, your job is to harness the power of your AI platform and offer it up to your many users in top-level features. Whether your AI project is about writing sports content or auto-diagnosing X-ray images, your work as an AI developer is based on fundamentally the same architecture. And to do this at a scale that matches the capability of your workhorse models, you need a programming language to match its power. I’ll give you three guesses which one I recommend. C++ is on the inside of all AI engines. Whereas Python is often on the outside wrapping around the various models, C++ is always closer to the machine and its hardware. PyTorch and Tensorflow have lots of Python code on the top layers, but the grunt work underneath runs in highly optimized C++ code. The main advantage of C++ is that it is super-fast, and has low-level capabilities, that makes its operations close to those of the hardware instructions. This is a perfect match, because AI engines need to run blazingly fast, with hardware-acceleration integrations direct to the GPU to handle literally billions of arithmetic calculations. And yet, C++ is also a high-level programming language with support for advanced features like classes and modularity, so it’s great for programmer productivity.
Genre: Non-Fiction > Tech & Devices

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