Lilly Seeley

How Artificial Intelligence Works

What is AI?

Artificial Intelligence (AI) refers to computer systems that can perform tasks typically requiring human intelligence, such as recognizing patterns, making decisions, and understanding language.

Basic Components of AI

1. Data

AI systems learn from large amounts of data. This data can be text, images, numbers, or any other information that helps the AI understand patterns and relationships.

2. Algorithms

These are mathematical instructions that tell the computer how to process the data and learn from it. Common types include:

• Machine Learning algorithms that improve with experience
• Deep Learning algorithms that use artificial neural networks
• Natural Language Processing for understanding text and speech

3. Neural Networks

Inspired by how the human brain works, these are networks of interconnected nodes (artificial neurons) that process information. Each connection has a weight that determines how much influence one node has on another.

How AI Learning Works

Training Phase

During training, the AI system:

1. Receives input data (like thousands of photos of cats and dogs)
2. Makes predictions or guesses about what it sees
3. Compares its guesses to the correct answers
4. Adjusts its internal parameters to improve accuracy
5. Repeats this process millions of times

Prediction Phase

After training, the AI can:

1. Receive new, unseen data
2. Use its learned patterns to make predictions
3. Provide answers, classifications, or generate new content

Types of AI

Narrow AI

AI designed for specific tasks, like playing chess, recognizing faces, or translating languages. This is what we have today.

General AI

Hypothetical AI that could understand and perform any intellectual task that humans can do. This doesn't exist yet.

Common AI Applications

• Search engines that understand what you're looking for
• Recommendation systems on streaming platforms
• Virtual assistants like Siri or Alexa
• Image recognition in photos
• Language translation
• Autonomous vehicles
• Medical diagnosis assistance

Limitations of Current AI

• Requires large amounts of data to work well
• Can be biased based on training data
• Doesn't truly "understand" like humans do
• Can make mistakes, especially with unusual situations
• Limited to patterns it has seen before