What is Artificial Intelligence?

Artificial Intelligence is the broad engineering discipline of constructing computer systems capable of performing cognitive tasks historically associated with biological intelligence, such as visual perception, natural language comprehension, sound synthesis, decision-making, and multi-step reasoning.

Real-World Mental Model

“AI is like "aviation" — it includes gliders, propellers, jet airliners, and rockets. Some use simple aerodynamics; others require rocket engines, but all aim to achieve flight.”

INTERACTIVE ENGINE: AI TAXONOMY

Live Reactive

TAXONOMY LEVEL: FRONTIER

Large Language Models

Scale & Emergent In-Context Reasoning

Autoregressive Transformer networks parameterized by billions to trillions of weights, pre-trained on internet-scale token streams to predict the next token with high fidelity.

Canonical Artifacts:Claude 3.5 Sonnet, GPT-4, Llama 3, Gemini 1.5

Mathematical Formulation:Maximizes log-likelihood: Σ log P(w_t | w_1, ..., w_{t-1}; θ)

CORE PRINCIPLES

What You Must Understand

AI is an overarching field and destination, not a singular algorithm or math formula.

Includes symbolic reasoning, expert rule engines, heuristic search, and statistical machine learning.

Modern AI focuses primarily on empirical representations learned from large datasets rather than hardcoded hand-written logic.

Reference Implementation

// Symbolic Rule-Based AI vs Learned AI
function ruleBasedSentiment(text: string): 'POS' | 'NEG' {
  const positiveWords = ['excellent', 'superb', 'great'];
  return positiveWords.some(w => text.toLowerCase().includes(w)) ? 'POS' : 'NEG';
}

Production Failure Mode

Equating AI solely with generative LLMs like ChatGPT, ignoring 70 years of deterministic algorithms, search trees, and classical ML.