Advances in Smart Knowledge Computing

This book explores the evolution of computing beyond current AI paradigms, with a particular emphasis on the potential of knowledge to be used to develop more intelligent, adaptive, and potentially conscious systems. This book has three elements:

First, moving beyond "Narrow AI" and data-centric paradigms were investigated.The book likely discusses the inherent limitations of current "narrow AI", despite impressive performance in specific tasks, interpretability, reasoning capabilities, and true understanding.

Second, the modelling and uses cases were explored. The book would explore advanced methods for representing knowledge and performing logical or probabilistic reasoning over that knowledge.

Third, provide the applications and impact of post-AI. The book provides with details of smart knowledge computing which can lead to more informed, explainable, and robust decision-making in complex real-world scenarios.

In essence, this presents itself as a forward-looking investigation into how intelligence might be constructed by combining the capacity of data processing with explicit knowledge representation and advanced reasoning.

Dives into the world of Smart Knowledge Computing Explores how machines can reason, learn, and extract insights from vast amounts of data Presents an Interdisciplinary approach to AI and Knowledge Management

Inhalt

Exploring the Data Balance Effect: Artificial Neural Network Classification on Rodent Tuber's Liquid Chromatography Mass Spectrometry Data.- Explainable Edge AI for Transparent and Accessible Telemedicine Diagnostics .- Insights and Recommendations for Earthquake
Logistics in Indonesia: Analyzing Twitter (X) Data.- Machine Learning Models for Early Prediction of Student Success and Dropout in Higher Education.- Predicting Stock Price Movements Using the RNN-MGU Model.- etc..