Humanized AI (HAI), emerging as the next of the AI waves, refers to artificial social beings that are very close to humans in various aspects, beings who are machine-race humans, not digital slaves. Foundation, Architecture, and Prototyping of HAI deploy a novel smalldata approach to vertically explore the spectrum of HAI.
Different from the popular big-data philosophy that is based on the rigid notion that the connotation of each concept is fixed and the same to everyone, this book treats understanding as a process from simple to complex, and uses the similarity principle to effectively deal with novelties. Combining the efficiency of the Behaviorists’ goal-driven approach and the flexibility of a Constructivists’ approach, both the architecture of HAI and the philosophical discussions arising from it are elaborated upon.
Advancing a unique approach to the concept of HAI, this book appeals to professors and students of both AI and philosophy, as well as industry professionals looking to stay at the forefront of developments within the field.
Humanized AI (HAI), emerging as the next of the AI waves, refers to artificial social beings that are very close to humans in various aspects, beings who are machine-race humans, not digital slaves. Foundation, Architecture and Prototyping of Humanized AI deploys a novel small-data approach to vertically explore the spectrum of HAI.
Philosophy of Humanized AI in Plain Language. Humanized AI and its Approaches. Architecture of Humanized AI. Prototyping Agents - Zda and Lia. Appendix: Tutorial to Common Methods for Narrow AI.
Mark Chang, PhD, is the founder of AGInception and an adjunct professor of Biostatistics at Boston University. He is an elected fellow of the American Statistical Association, a co-founder of the International Society for Biopharmaceutical Statistics. He previously held various positions in pharmaceutical companies, including Scientific Fellow, executive Director, and Senior Vice President. He is an adaptive design expert and has extensive knowledge in AI for clinical trials. He has published 12 books on artificial intelligence & machine learning, adaptive clinical trial designs, biostatistics, and scientific principles.
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