Artificial Intelligence Fundamentals

What is AI?

• Artificial Intelligence (AI) refers to the development of computer systems that can perform tasks that typically require human intelligence, such as:
  • Learning
  • Problem-solving
  • Reasoning
  • Perception

Types of AI:

• Narrow or Weak AI: Designed to perform a specific task, such as:
  • Virtual assistants (e.g., Siri, Alexa)
  • Image recognition systems
  • Language translation software
• General or Strong AI: Aims to match human intelligence, with the ability to:
  • Understand
  • Learn
  • Apply knowledge across a wide range of tasks
  • Reason and make decisions like humans
• Superintelligence: Far surpasses human intelligence, with the potential to revolutionize or threaten humanity

AI Techniques:

• Machine Learning: A type of AI that enables machines to learn from data and improve their performance over time
  • Supervised learning
  • Unsupervised learning
  • Reinforcement learning
• Deep Learning: A subset of machine learning that uses neural networks to analyze data
  • Convolutional Neural Networks (CNNs)
  • Recurrent Neural Networks (RNNs)

AI Applications:

• Natural Language Processing (NLP): Enables computers to understand, interpret, and generate human language
• Computer Vision: Allows computers to interpret and understand visual information from the world
• Robotics: Combines AI with robotics to create autonomous systems that can perform tasks that typically require human intelligence

AI Challenges and Risks:

• Job Displacement: AI may automate jobs, leading to unemployment
• Bias and Discrimination: AI systems can perpetuate biases and discrimination if not designed carefully
• Privacy and Security: AI systems can compromise privacy and security if not designed with safeguards
• Existential Risk: The possibility of superintelligent AI posing an existential risk to humanity