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Inhaltsangabe
The Physics of AI
Book I establishes the technical foundation of the series. It examines artificial intelligence not as abstraction or narrative, but as a physical and computational system governed by constraints, trade-offs, and measurable behaviors.
The book begins at the substrate: data, representation, optimization, and statistical learning. It dissects classical machine learning, neural networks, deep architectures, and large-scale model training through the lens of systems behavior rather than hype. Core concepts such as feature engineering, dimensionality, variance, overfitting, convergence, entropy, and generalization are treated as structural forces — not metaphors.
Rather than presenting algorithms as isolated tools, The Physics of AI frames them as dynamic processes operating within constraint envelopes:
• Loss landscapes and optimization geometry
• Convergence trajectories and reproducibility variance
• Scaling laws and computational trade-offs
• Representation compression and information bottlenecks
• Drift, distribution shift, and model decay
• Event-driven orchestration in production systems
• Monitoring as sampled observation of a changing substrate
The text emphasizes that AI systems are not static artifacts but evolving, probabilistic structures interacting with real-world data streams. Their behavior emerges from training dynamics, infrastructure constraints, and deployment feedback loops.
This volume does not yet prescribe governance or regulation. Instead, it establishes the mechanical reality upon which governance must be built. Without understanding how models converge, degrade, generalize, or fail, oversight becomes superficial.
Book I therefore serves as the technical bedrock for the entire series. It defines the system physics that later volumes will govern, audit, and ethically evaluate.
It is not a speculative treatment of intelligence.
It is an analysis of machine behavior under constraint.
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Paperback. Zustand: new. Paperback. The Physics of AIBook I establishes the technical foundation of the series. It examines artificial intelligence not as abstraction or narrative, but as a physical and computational system governed by constraints, trade-offs, and measurable behaviors.The book begins at the substrate: data, representation, optimization, and statistical learning. It dissects classical machine learning, neural networks, deep architectures, and large-scale model training through the lens of systems behavior rather than hype. Core concepts such as feature engineering, dimensionality, variance, overfitting, convergence, entropy, and generalization are treated as structural forces - not metaphors.Rather than presenting algorithms as isolated tools, The Physics of AI frames them as dynamic processes operating within constraint envelopes: - Loss landscapes and optimization geometry- Convergence trajectories and reproducibility variance- Scaling laws and computational trade-offs- Representation compression and information bottlenecks- Drift, distribution shift, and model decay- Event-driven orchestration in production systems- Monitoring as sampled observation of a changing substrateThe text emphasizes that AI systems are not static artifacts but evolving, probabilistic structures interacting with real-world data streams. Their behavior emerges from training dynamics, infrastructure constraints, and deployment feedback loops.This volume does not yet prescribe governance or regulation. Instead, it establishes the mechanical reality upon which governance must be built. Without understanding how models converge, degrade, generalize, or fail, oversight becomes superficial.Book I therefore serves as the technical bedrock for the entire series. It defines the system physics that later volumes will govern, audit, and ethically evaluate.It is not a speculative treatment of intelligence.It is an analysis of machine behavior under constraint. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9798250463676
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