03048nam a22005415i 4500 978-981-97-1291-5 DE-He213 20251030111747.0 cr nn 008mamaa 240326s2024 si | s |||| 0|eng d 9789819712915 978-981-97-1291-5 10.1007/978-981-97-1291-5 doi Q342 UYQ bicssc COM004000 bisacsh UYQ thema Raikov, Aleksandr. author. aut http://id.loc.gov/vocabulary/relators/aut 74072 Photonic Artificial Intelligence [electronic resource] / by Aleksandr Raikov. 1st ed. 2024. Singapore : Springer Nature Singapore : Imprint: Springer, 2024. XVII, 110 p. 14 illus., 12 illus. in color. online resource. text txt rdacontent computer c rdamedia online resource cr rdacarrier text file PDF rda SpringerBriefs in Computational Intelligence, 2625-3712 Introduction -- Impulse Brain? -- Artificial Mind -- Photonic Psychology -- Emotion Recognition -- Photonic Thought -- Soliton’s Semantics -- Subatomic Semantics -- Dark Mind -- Material Synthesis -- Photonic Learning. This book addresses an attempt to create Photonic Artificial Intelligence (PAI) system based on optical technologies, which process signals continuously. PAI could help to overcome digital computer limits and almost zero out the machine learning time and AI inference. It helps to consider feelings, the chaos of thoughts, cognitive activity, and the transcendental states of the human mind in AI systems. The book also discusses new problems such as synthesizing new photonic materials, creating optical control systems, and connecting PAI systems with outside digital computers and holographic memory. The book is aimed at a wide range of readers, including postgraduates and researchers, interested in advanced AI by creating its new paradigm, which can help to overcome traps of traditional AI development. Computational intelligence. 64052 Artificial intelligence. 58441 Photonics. 65750 Optical engineering. 65751 Computational Intelligence. 64052 Artificial Intelligence. 58441 Photonics and Optical Engineering. 65753 SpringerLink (Online service) Springer Nature eBook Printed edition: 9789819712908 Printed edition: 9789819712922 SpringerBriefs in Computational Intelligence, 2625-3712 74073 https://doi.org/10.1007/978-981-97-1291-5 ZDB-2-INR ZDB-2-SXIT 58688 58688