Inside AI, Video Edition

Video description

In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.

Separate AI truth from AI hype, and learn how to put this powerful technology to work.

In Inside AI AI professor and entrepreneur Dr. Akli Adjaoute puts AI in perspective, with informed insights from 30 years spent in the field. His book lays out a pragmatic blueprint that every leader can utilize to drive innovation with artificial intelligence.

In Inside AI you’ll learn how to:

  • Gain insight into diverse AI techniques and methodologies
  • Learn from both successful and failed AI applications
  • Identify the capabilities and limitations of AI systems
  • Understand successful and failed uses of AI in business
  • See where human cognition still exceeds AI
  • Bust common myths like AI’s threat to jobs and civilization
  • Manage AI projects effectively

Inside AI takes you on a journey through artificial intelligence, from AI’s origins in traditional expert systems all the way to deep learning and Large Language Models. There’s no hype here—you’ll get the grounded, evidence-based insights that are vital for making strategic decisions and preparing your business for the future.

About the Technology
Artificial Intelligence enthusiasts promise everything from human-like collaboration on everyday tasks to the end of work as we know it. Is AI just a flash in the pan, or can it really transform how you do business? This intriguing book sifts through the hype and separates the truth from the myths, with clear advice on what AI can—and can’t—achieve.

About the Book
Inside AI provides a clear-headed overview of modern artificial intelligence, including the recent advances of Generative AI and Large Language Models. Its accessible and jargon-free explanations of leading AI techniques showcase how AI delivers tangible advantages to businesses. Both inspiring and practical, this book provides a proven framework for developing successful AI applications.

What's Inside
  • Insights from successful and failed AI applications
  • A survey of AI techniques and methodologies
  • Bust common AI myths
  • Manage AI projects effectively

About the Reader
For anyone seeking grounded insights into AI’s capabilities, including business leaders and decision makers.

About the Author
Akli Adjaoute is the founder of multiple AI-related companies. He served as an adjunct professor at the University of San Francisco and as Scientific Committee Chair and Head of the AI department at EPITA.

The technical editor on this book was Richard Vaughan.

Provides valuable insights gained from applying AI in high-stakes, mission-critical applications.
- Raymond Kendall, Honorary Secretary General of INTERPOL

A labor of love. Readers will love it.
- Ajay Bhalla, President of Cyber & Intelligence Solutions, Mastercard

With clarity and generosity, Akli Adjaoute makes you understand what AI is and what it is not. Delightful, and also invaluable.
- Patrick Pérez, Kyutai

A framework for how to think about AI, and its transformational impact on every person in the world. It is powerful in its simplicity.
- Karen Webster, PYMNTS

Table of contents

  1. foreword
  2. preface
  3. Chapter 1. The rise of machine intelligence
  4. Chapter 1. The AI revolution
  5. Chapter 1. Error-prone intelligence
  6. Chapter 1. Chatbots
  7. Chapter 1. Looking ahead
  8. Chapter 1. Summary
  9. Chapter 2. AI mastery: Essential techniques, Part 1
  10. Chapter 2. Expert systems
  11. Chapter 2. Case-based reasoning
  12. Chapter 2. Fuzzy logic
  13. Chapter 2. Genetic algorithms
  14. Chapter 2. Summary
  15. Chapter 3. AI mastery: Essential techniques, Part 2
  16. Chapter 3. Decision trees for fraud prevention
  17. Chapter 3. Artificial neural networks
  18. Chapter 3. Deep learning
  19. Chapter 3. Bayesian networks
  20. Chapter 3. Unsupervised learning
  21. Chapter 3. So, what is artificial intelligence?
  22. Chapter 3. Summary
  23. Chapter 4. Smart agent technology
  24. Chapter 4. Summary
  25. Chapter 5. Generative AI and large language models
  26. Chapter 5. Large language models
  27. Chapter 5. ChatGPT
  28. Chapter 5. Bard
  29. Chapter 5. Humans vs. LLMs
  30. Chapter 5. AI does not understand
  31. Chapter 5. Benefits of LLMs
  32. Chapter 5. LLM limits
  33. Chapter 5. Generative AI and intellectual property
  34. Chapter 5. Risks of generative AI
  35. Chapter 5. LLMs and the Illusion of Understanding
  36. Chapter 5. Summary
  37. Chapter 6. Human vs. machine
  38. Chapter 6. Human vision vs. computer vision
  39. Chapter 6. Summary
  40. Chapter 7. AI doesn’t turn data into intelligence
  41. Chapter 7. Lack of generalization
  42. Chapter 7. Summary
  43. Chapter 8. AI doesn’t threaten our jobs
  44. Chapter 8. Summary
  45. Chapter 9. Technological singularity is absurd
  46. Chapter 9. The truth about the evolution of robotics
  47. Chapter 9. Merging human with machine?
  48. Chapter 9. Science fiction vs. reality
  49. Chapter 9. Summary
  50. Chapter 10. Learning from successful and failed applications of AI
  51. Chapter 10. AI misuse
  52. Chapter 10. AI failures
  53. Chapter 10. How to set your AI project up for success
  54. Chapter 10. AI model lifecycle management
  55. Chapter 10. Guiding principles for successful AI projects
  56. Chapter 10. Summary
  57. Chapter 11. Next-generation AI
  58. Chapter 11. Sampling
  59. Chapter 11. Elimination of irrelevant attributes
  60. Chapter 11. Data coherence
  61. Chapter 11. Lack of bias in data and algorithms
  62. Chapter 11. Feature engineering
  63. Chapter 11. Technique combination
  64. Chapter 11. Unsupervised learning
  65. Chapter 11. AI factory
  66. Chapter 11. Quality Assurance
  67. Chapter 11. Prediction reliability
  68. Chapter 11. Effective data storage and processing
  69. Chapter 11. Deployability and interoperability
  70. Chapter 11. Scalability
  71. Chapter 11. Resilience and robustness
  72. Chapter 11. Security
  73. Chapter 11. Explicability
  74. Chapter 11. Traceability and monitoring
  75. Chapter 11. Privacy
  76. Chapter 11. Temporal reasoning
  77. Chapter 11. Contextual reasoning
  78. Chapter 11. Causality inference
  79. Chapter 11. Analogical reasoning and transferability
  80. Chapter 11. Personalization
  81. Chapter 11. Sustainable AI
  82. Chapter 11. Adaptability
  83. Chapter 11. Human–machine collaboration
  84. Chapter 11. Summary
  85. Appendix A Tracing the roots: From mechanical calculators to digital dreams
  86. Appendix B Algorithms and programming languages
  87. Appendix B. Programming languages
  88. epilogue

Product information

  • Title: Inside AI, Video Edition
  • Author(s): Akli Adjaoute
  • Release date: April 2024
  • Publisher(s): Manning Publications
  • ISBN: None