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.
Quotes
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
- foreword
- preface
- Chapter 1. The rise of machine intelligence
- Chapter 1. The AI revolution
- Chapter 1. Error-prone intelligence
- Chapter 1. Chatbots
- Chapter 1. Looking ahead
- Chapter 1. Summary
- Chapter 2. AI mastery: Essential techniques, Part 1
- Chapter 2. Expert systems
- Chapter 2. Case-based reasoning
- Chapter 2. Fuzzy logic
- Chapter 2. Genetic algorithms
- Chapter 2. Summary
- Chapter 3. AI mastery: Essential techniques, Part 2
- Chapter 3. Decision trees for fraud prevention
- Chapter 3. Artificial neural networks
- Chapter 3. Deep learning
- Chapter 3. Bayesian networks
- Chapter 3. Unsupervised learning
- Chapter 3. So, what is artificial intelligence?
- Chapter 3. Summary
- Chapter 4. Smart agent technology
- Chapter 4. Summary
- Chapter 5. Generative AI and large language models
- Chapter 5. Large language models
- Chapter 5. ChatGPT
- Chapter 5. Bard
- Chapter 5. Humans vs. LLMs
- Chapter 5. AI does not understand
- Chapter 5. Benefits of LLMs
- Chapter 5. LLM limits
- Chapter 5. Generative AI and intellectual property
- Chapter 5. Risks of generative AI
- Chapter 5. LLMs and the Illusion of Understanding
- Chapter 5. Summary
- Chapter 6. Human vs. machine
- Chapter 6. Human vision vs. computer vision
- Chapter 6. Summary
- Chapter 7. AI doesn’t turn data into intelligence
- Chapter 7. Lack of generalization
- Chapter 7. Summary
- Chapter 8. AI doesn’t threaten our jobs
- Chapter 8. Summary
- Chapter 9. Technological singularity is absurd
- Chapter 9. The truth about the evolution of robotics
- Chapter 9. Merging human with machine?
- Chapter 9. Science fiction vs. reality
- Chapter 9. Summary
- Chapter 10. Learning from successful and failed applications of AI
- Chapter 10. AI misuse
- Chapter 10. AI failures
- Chapter 10. How to set your AI project up for success
- Chapter 10. AI model lifecycle management
- Chapter 10. Guiding principles for successful AI projects
- Chapter 10. Summary
- Chapter 11. Next-generation AI
- Chapter 11. Sampling
- Chapter 11. Elimination of irrelevant attributes
- Chapter 11. Data coherence
- Chapter 11. Lack of bias in data and algorithms
- Chapter 11. Feature engineering
- Chapter 11. Technique combination
- Chapter 11. Unsupervised learning
- Chapter 11. AI factory
- Chapter 11. Quality Assurance
- Chapter 11. Prediction reliability
- Chapter 11. Effective data storage and processing
- Chapter 11. Deployability and interoperability
- Chapter 11. Scalability
- Chapter 11. Resilience and robustness
- Chapter 11. Security
- Chapter 11. Explicability
- Chapter 11. Traceability and monitoring
- Chapter 11. Privacy
- Chapter 11. Temporal reasoning
- Chapter 11. Contextual reasoning
- Chapter 11. Causality inference
- Chapter 11. Analogical reasoning and transferability
- Chapter 11. Personalization
- Chapter 11. Sustainable AI
- Chapter 11. Adaptability
- Chapter 11. Human–machine collaboration
- Chapter 11. Summary
- Appendix A Tracing the roots: From mechanical calculators to digital dreams
- Appendix B Algorithms and programming languages
- Appendix B. Programming languages
- epilogue
Product information
- Title: Inside AI, Video Edition
- Author(s):
- Release date: April 2024
- Publisher(s): Manning Publications
- ISBN: None
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