NGALUOPE & TUFUNGA 'ILO (TI)

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We can look at technology from a few angles:

1. By Function:
    
   • Communication: Internet, smartphones, social media
      
   • Transportation: Cars, trains, airplanes, electric scooters
      
   • Medicine: MRI machines, robotic surgery, vaccines
      
   • Energy: Solar panels, nuclear power, batteries
      

1. By Type:
    
   • Information Technology (IT): Software, networks, AI
      
   • Biotechnology: Genetic engineering, CRISPR
      
   • Nanotechnology: Tiny machines at the molecular level
      
   • Industrial Technology: Factories, automation, robotics
      

1. By Era:
    
   • Ancient: Fire, wheel, bronze tools
      
   • Industrial: Steam engines, electricity, telegraphs
      
   • Modern/Digital: Computers, smartphones, AI, IoT

 AI, or Artificial Intelligence, is a branch of computer science that focuses on creating machines or software that can perform tasks that normally require human intelligence. This includes things like learning, reasoning, problem-solving, understanding language, recognizing patterns, and even making decisions. 

a. Narrow AI (Weak AI):

• Designed for a specific task.
   
• Examples: ChatGPT, Siri, recommendation systems on Netflix or Amazon, self-driving car software.
   

b. General AI (Strong AI):

• Would have human-level intelligence across a wide range of tasks.
   
• Example: AI that can reason, learn, and plan like a human. (We don’t have this yet.)
   

c. Superintelligent AI:

• Hypothetical AI that surpasses human intelligence in all areas.
   
• Mostly in theory/future speculation.

AI often relies on these core techniques:

• Machine Learning (ML): Systems learn patterns from data rather than being explicitly programmed.
   
• Deep Learning: A type of ML using neural networks inspired by the human brain. Useful for image recognition, speech, and natural language processing.
   
• Natural Language Processing (NLP): Lets machines understand and generate human language (like me!).
   
• Computer Vision: Allows machines to see and interpret images or video.
   
• Reinforcement Learning: AI learns by trial and error to maximize rewards, often used in robotics and games.