Toward Artificial General Intelligence: Deep Learning, Neural Networks, Generative AI

✍ Scribed by Victor Hugo C. de Albuquerque; Pethuru Raj; Satya Prakash Yadav (editors)

• Publisher: De Gruyter
• Year: 2023
• Tongue: English
• Leaves: 424
• Category: Library

✦ Synopsis

Artifi cial Intelligence (AI) has been an exciting fi eld of study and research in educational institutions and research labs across the globe. Technology giants and IT organizations invest heavily on AI technologies and tools with the aim of preciselyautomating a variety of simple as well as complicated business operations acrossindustry verticals. This book covers the latest trends and transitions happening in thefuturistic AI domain. The book also focuses on machine and deep learning (ML/DL)algorithms, which are, undoubtedly, the mainstream implementation technologies ofstate-of-the-art AI systems and services. Also, there are chapters on computer vision(CV) and natural language processing (NLP), the primary use cases and applicationsof AI. The book has well-written chapters for demystifying AI model engineeringmethods. Further on, our esteemed readers can fi nd details on AI model evaluation,optimization, deployment and observability. Finally, the book deals and describesgenerative AI, the latest buzzword in the IT industry.

The book

presents the recent ground-breaking changes taking place in the aspects of AI model building, hosting, running and maintaining in cloud environments,

articulates and accentuates the most recent developments taking place in the

domain of Artifi cial Intelligence,

covers the noteworthy innovations and disruptions towards Generative Artifi cial

Intelligence (Generative AI),

explains the breakthrough innovations and disruptions towards Artifi cial General

Intelligence (AGI)

and delineates an engaging discussion of Natural Language Processing, Neuromorphic Systems and Biometrics.

• Presents the most recent developments taking place in Artificial Intelligence
• Covers the recent shift towards Generative Artificial Intelligence
• Includes a discussion of Natural Language Processing, Neuromorphic Systems and Biometrics

✦ Table of Contents

Preface
Contents
List of authors
About the editors
1 Introduction to artificial intelligence
2 AI technologies, tools, and industrial use cases
3 Classification and regression algorithms
4 Clustering and association algorithm
5 Reinforcement learning
6 Evaluation of AI model performance
7 Methods of cross-validation and bootstrapping
8 Meta-learning through ensemble approach: bagging, boosting, and random forest strategies
9 AI: issues, concerns, and ethical considerations
10 The future with AI and AI in action
11 A survey of AI in industry: from basic concepts to industrial and business applications
12 The intelligent implications of artificial intelligence-driven decision-making in business management
13 An innovative analysis of AI-powered automation techniques for business management
14 The smart and secured AI-powered strategies for optimizing processes in multi-vendor business applications
15 Utilizing AI technologies to enhance e-commerce business operations
16 Exploring the potential of artificial intelligence in wireless sensor networks
17 Exploring artificial intelligence techniques for enhanced sentiment analysis through data mining
18 Exploring the potential of artificial intelligence for automated sentiment
19 A novel blockchain-based artificial intelligence application for healthcare automation
20 Enhancing industrial efficiency with AI-enabled blockchain-based solutions
Index