Geometric Foundations of Artificial Intelligence epub
por Andrew Kiruluta
Descrição do livro
This book presents artificial intelligence as a geometric science of spaces, transformations, and structured possibility. Beginning with Euclidean geometry, high-dimensional spaces, hyperspheres, polytopes, Hilbert spaces, manifolds, and Riemannian geometry, it shows how modern AI systems learn representations, optimize loss landscapes, organize embeddings, generate new data, reason through paths, and act through value-guided trajectories. Extending from transformers and generative models to reinforcement learning, world models, category theory, self-modeling, and AGI, the book argues that the future of artificial intelligence may depend not only on larger models, but on richer internal geometries that are stable, compositional, causal, embodied, and aligned with the structure of reality.
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