£83.99
£83.99
While Transformers dominate AI, State Space Models (SSMs) challenge their supremacy with a leaner, more efficient approach. This book uniquely combines theoretical depth with practical insights, showing how SSMs excel at long-range dependencies and scalability to redefine AI.
This book offers a timely exploration of an emerging AI paradigm. While Transformers have dominated the AI landscape, State Space Models (SSMs) challenge their supremacy with a leaner, more efficient approach to sequence modeling. This book uniquely combines theoretical depth with practical insights, presenting a compelling case for why SSMs could redefine the future of AI applications. Readers will gain a deep understanding of SSM architecture, from its mathematical foundations to its implementation in critical domains like health care. The book also highlights how SSMs excel in handling long-range dependencies and runtime scalability, providing a significant edge in real-world applications. Unlike other titles that focus exclusively on Transformers or Recurrent Neural Networks (RNNs), this book positions SSMs as a bridge between traditional models and cutting-edge innovations. By addressing both the benefits and challenges of SSMs, it caters to researchers, AI practitioners, and industry leaders looking to stay ahead in the evolving landscape of sequence modeling.
This book explores the latest research in education design for virtual and augmented reality. Using numerous studies and examples, it will help the reader gain a better understanding of the nature of these realities and their applications in theory and practice.
This book offers an integral view of human speech behavior, uniting biology, linguistics, math, and AI. It explores neural networks and microelectronics for speech recognition, text-to-speech synthesis, and dialogue systems. For a broad professional audience.
This book explores how artificial intelligence (AI) interprets behavioral patterns and their influence on personality. It discusses AI’s uses, from controlling diseases to modern personality analysis, and its challenges. Perfect for data scientists, academics, and students.
Using real-world cases, this book illustrates how to handle volatile financial time series data. Learn to apply statistical, machine learning, and deep learning techniques with R and Python to build robust predictive models and construct profitable investment portfolios.
This book explores artificial intelligence through the unique lens of art, showing how we can engage with AI without being subjugated by it. Each chapter begins with a work of art to guide the reader through philosophical keywords like “author,” “memory,” and “human.”
This book proposes a neural network for structural information analysis. Inspired by the human brain, this approach reconstructs a model of the world to interpret behaviour and enables automatic semantic analysis of text, constructing a semantic portrait from any stream.
This book uses real-world cases to show how to analyse volatile financial time series with statistical analysis, machine learning, and deep learning. Learn to build predictive models to forecast stock prices and construct profitable portfolios using Python and R.
With demand for mobility growing and infrastructure limited, Intelligent Transportation Systems (ITS) are essential. This book presents the ingredients of good ITS not from a technology perspective, but from a business, management, and policy view, with real-life case studies.
A surge of interest in post-editing, the oldest form of human-machine cooperation for translation, is fundamentally changing the industry. This volume compiles work by researchers, developers, and practitioners on this essential, evolving practice.
This book looks beyond buzzwords for the ground truth in how technology can enhance education. It makes a strong case for how innovations like immersive virtual reality, accessible Hollywood technology, and the metaverse can create a new frontier for future-focused learning.
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