1 Understanding artificial intelligence: an introduction, history, and foundations
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P Sonawane
Abstract
Mankind has evolved and defined its intelligence as one’s own mental capability to learn, to reason and to solve a problem, empirically. Likewise, artificial intelligenceartificial intelligence (AI) created by modern humans is a revolutionizing technology that enables machines to mimic human intelligence. Alan TuringAlan Turing, a pioneer of introducing AI simulation in 1950 laid an odyssey that culminated in an advent of ChatGPTChatGPT. Thus, this chapter is focused on understanding AI that has now expanded in all sectors of the civilized world in today’s technological era. Referring to the 1956 DartmouthDartmouth conference, the chapter provides a framework for evaluating the history and milestones in AI evolution. Here, conceptualizing and understanding deep learningdeep learning and machine learning have been addressed and vividly described. Furthermore, the following chapter aims to explore the various applications of AI into various sectors along with its future prospects in research related to microbial dynamics.
Abstract
Mankind has evolved and defined its intelligence as one’s own mental capability to learn, to reason and to solve a problem, empirically. Likewise, artificial intelligenceartificial intelligence (AI) created by modern humans is a revolutionizing technology that enables machines to mimic human intelligence. Alan TuringAlan Turing, a pioneer of introducing AI simulation in 1950 laid an odyssey that culminated in an advent of ChatGPTChatGPT. Thus, this chapter is focused on understanding AI that has now expanded in all sectors of the civilized world in today’s technological era. Referring to the 1956 DartmouthDartmouth conference, the chapter provides a framework for evaluating the history and milestones in AI evolution. Here, conceptualizing and understanding deep learningdeep learning and machine learning have been addressed and vividly described. Furthermore, the following chapter aims to explore the various applications of AI into various sectors along with its future prospects in research related to microbial dynamics.
Chapters in this book
- Frontmatter I
- Dedication V
- Preface VII
- Contents IX
- 1 Understanding artificial intelligence: an introduction, history, and foundations 1
- 2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI 25
- 3 Cellular image classification and identification of genetic variations using artificial intelligence 47
- 4 Artificial intelligence in bacterial staining and cell counting 65
- 5 Use of artificial intelligence in the prediction of microbial species 79
- 6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions 97
- 7 AI in food production and processing: applications and challenges 125
- 8 Artificial intelligence in microbial food safety 153
- 9 AI in plant growth promotion and plant disease management 183
- 10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology 207
- 11 Artificial intelligence in diagnostics 229
- 12 Artificial intelligence in bacterial culture plate images 263
- 13 Prediction of antimicrobial activity using artificial intelligence 281
- 14 Artificial intelligence and MALDI-TOF MS 313
- 15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare 337
- 16 Reimagining perfusion bioreactors with artificial intelligence 357
- Index 381
Chapters in this book
- Frontmatter I
- Dedication V
- Preface VII
- Contents IX
- 1 Understanding artificial intelligence: an introduction, history, and foundations 1
- 2 Basics of machine learning (ML) and deep learning (DL), secondary data source and training, application and AI tools, challenges, and future perspectives of AI 25
- 3 Cellular image classification and identification of genetic variations using artificial intelligence 47
- 4 Artificial intelligence in bacterial staining and cell counting 65
- 5 Use of artificial intelligence in the prediction of microbial species 79
- 6 Transformative AI applications in environmental microbiology: pioneering research and sustainable solutions 97
- 7 AI in food production and processing: applications and challenges 125
- 8 Artificial intelligence in microbial food safety 153
- 9 AI in plant growth promotion and plant disease management 183
- 10 Role of artificial intelligence (AI) and machine learning (ML) in disease forecasting and disease epidemiology 207
- 11 Artificial intelligence in diagnostics 229
- 12 Artificial intelligence in bacterial culture plate images 263
- 13 Prediction of antimicrobial activity using artificial intelligence 281
- 14 Artificial intelligence and MALDI-TOF MS 313
- 15 Artificial intelligence in clinical microbiology: regeneration of diagnostics techniques using GANs and reinforcement learning for drug discovery and development in human welfare 337
- 16 Reimagining perfusion bioreactors with artificial intelligence 357
- Index 381
