AI in 15 Minutes or Less
Contents
Introduction
What AI is
AI stands for artificial intelligence, which is the competency of a computer or a robot to perform not strictly pre-programmed tasks. Normally animals perform such tasks. They include (a) obtaining data through listening, reading, and graphic recognition, (b) processing data through its analysis and synthesis, and (c) representing the processed results through documents, speech, or behavior such as driving.
Performing of "not strictly pre-programmed tasks" requires at least one specific capacity known as learning. Learning is a process of autonomous acquiring new or modifying existing data. Learning is a feature of humans and other animals. Some debate whether plants are able to learn.
AI is built on machine learning (ML), in which a computer or robot acquire new data autonomously, meaning without a programmer or another system's command. ML can be considered as a separate area of studies within AI.
Why AI is important
How AI changes the world
Give some examples of AI applications in various domains, such as health, education, entertainment, etc.
What AI is not
Applications of AI
Narrow
- Narrow AI is designed for specific tasks,
Narrow AI, also known as Weak AI, refers to artificial intelligence systems that are designed and trained for a specific task or a narrow set of tasks. Unlike general artificial intelligence, which would possess the ability to understand, learn, and perform any intellectual task that a human being can, narrow AI is limited to a predefined function.
Narrow AI systems excel at performing well-defined and specific tasks, such as image recognition, language translation, speech recognition, and playing board games like chess or Go. These systems are not capable of generalizing their knowledge or skills to perform tasks outside their designated scope.
In contrast to narrow AI, general AI would have the capability to understand and adapt to a wide range of tasks, similar to the cognitive flexibility of a human being. As of now, we have not achieved general AI, and most AI applications in use today are examples of narrow or specialized AI.
General
general AI, which can learn and perform any task that humans can. AI is a rapidly evolving field that has many applications and challenges in the modern world.
General AI, or Artificial General Intelligence (AGI), refers to a type of artificial intelligence that possesses the ability to understand, learn, and apply knowledge across a broad range of tasks at a level comparable to human intelligence. Unlike narrow AI, which is designed for specific tasks, general AI would have the capacity for cognitive functions similar to those of a human being.
Key characteristics of General AI include:
Cognitive Flexibility: The ability to understand and adapt to various types of tasks without the need for explicit programming.
Learning and Reasoning: General AI would be capable of learning from experience, reasoning through problems, and making decisions based on acquired knowledge.
Problem Solving: The ability to tackle complex problems and find solutions in a manner similar to human problem-solving.
Adaptability: General AI would be able to apply knowledge gained in one domain to another, showcasing adaptability and versatility.
Achieving General AI is a significant and complex challenge, as it requires the development of algorithms and systems that can mimic the broad spectrum of cognitive abilities found in humans. As of my last knowledge update in January 2022, we have not yet achieved true General AI, and most AI systems in use are specialized or narrow AI designed for specific applications. Researchers and scientists continue to explore ways to advance AI capabilities and work toward the goal of achieving General AI in the future.
AI Concepts
Introduce some key AI concepts, such as machine learning, deep learning, neural networks, natural language processing, computer vision, etc. Explain how they work and what they can do.
AI Implementations
Show some demonstrations of AI implementations, such as generative AI, chatbots, image recognition, speech synthesis, etc. Explain how they are built and what challenges they face.
AI Ethics
Discuss some ethical issues related to AI, such as bias, privacy, accountability, transparency, etc. Explain why they matter and how they can be addressed.
Conclusion
Summarize the main points of the training, highlight the benefits and limitations of AI, and encourage the participants to explore more AI resources and opportunities.
Courses
(1) Artificial Intelligence Fundamentals Certificate | ISACA. https://www.isaca.org/credentialing/artificial-intelligence-fundamentals-certificate. (2) 18 Best Free AI Training Courses for 2023: Build Skills Now - Tech.co. https://tech.co/news/best-free-ai-training-courses. (3) Generative AI for Everyone | Coursera. https://www.coursera.org/learn/generative-ai-for-everyone. (4) Introduction to Artificial Intelligence (AI) | Coursera. https://www.coursera.org/learn/introduction-to-ai. (5) How to Learn Artificial Intelligence: A Beginner’s Guide. https://www.coursera.org/articles/how-to-learn-artificial-intelligence.
