William Smith

MPT: Architecture, Training, and Applications (eBook, ePUB)

The Complete Guide for Developers and Engineers

• Format: ePub

Produktbeschreibung

"MPT: Architecture, Training, and Applications"
"MPT: Architecture, Training, and Applications" offers a comprehensive and authoritative reference on the next generation of transformer models-multi-modal and multi-parameter transformers (MPTs). Written for AI researchers, engineers, and advanced practitioners, this book unveils the conceptual foundations and mathematical principles underpinning MPT design, chronicling their evolution from early transformer systems to today's most sophisticated, multi-faceted architectures. Readers are meticulously guided through the taxonomy, motivation, and distinguishing traits of MPT, with careful attention paid to architectural caveats, key terminologies, and the wide array of practical and theoretical use cases these models now empower.
Delving into the technical heart of MPTs, the book presents a rigorous exploration of architectural design, parameterization strategies, and advanced training methodologies necessary for scaling these models to real-world complexity. Chapters offer in-depth coverage of data curation, progressive training regimes, robust optimization, and distributed infrastructures, while also detailing critical processes for model evaluation, benchmarking, and interpretability. Attention is given to efficient inference, hardware-aware deployments, and memory optimization-ensuring the text remains essential for practitioners addressing production-scale challenges and demanding performance constraints.
Beyond the core mechanisms, "MPT: Architecture, Training, and Applications" thoroughly addresses applied domains, customization strategies, and the responsible use of MPTs. Its coverage of industrial and research applications showcases the versatility of MPTs across language, vision, science, interactive systems, and creative AI. The book engages with ethical, societal, and regulatory concerns, providing actionable guidance for responsible innovation, transparency, and sustainable deployment. In its concluding chapters, it charts promising future directions in scalable training, lifelong learning, unified reasoning, and cross-disciplinary collaboration-cementing its status as a foundational guide for those shaping the future of multi-modal AI.

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Produktdetails

• Verlag: HiTeX Press
• Seitenzahl: 250
• Erscheinungstermin: 19. August 2025
• Englisch
• ISBN-13: 6610001029791
• Artikelnr.: 75278395