Understanding AI Evaluation Metrics: Accuracy, Precision, & Recall Explained
A comprehensive guide on the core AI evaluation metrics—accuracy, precision, recall—complete with definitions, formulas, real‑world examples, and practical tips.
Understanding Uncertainty: From Probability to Bayesian Updates and Fuzzy Logic
A deep dive into uncertainty handling techniques—probability, Bayesian inference, and fuzzy logic—highlighting theory, practice, and key differences.
An Overview of Intelligence: Symbolic, Statistical, Embodied, and Hybrid Approaches
Explore symbolic reasoning, data‑driven statistics, embodied interactions, and hybrid models in a single, in‑depth guide. Compare their strengths, weaknesses, and how they converge to advance artificial and natural intelligence.
Computational Creativity: An Introduction to AI‑Driven Innovation
Computational Creativity: An Introduction to AI‑Driven Innovation#
When artificial intelligence starts inventing rather than just analyzing, a new discipline emerges that blends computer science with art, philosophy, and cognitive science—computational creativity.
1. Defining Computational Creativity#
Computational creativity is the sub‑field of artificial intelligence (AI) that seeks to build systems capable of generating novel and valuable content. It extends beyond conventional pattern‑recognition tasks, embracing generative art, music composition, narrative generation, and game design. The field is distinguished by:
Historical Perspectives: 50 Ideas That Shaped Modern Artificial Intelligence
Historical Perspectives – 50 Ideas#
Artificial Intelligence (AI) is a tapestry woven from countless insights, experiments, and philosophical debates that span centuries. Understanding these early “ideas” is critical not only for scholars and practitioners who wish to navigate current debates but also for anyone curious about how our mind‑simulating machines evolved. Below is a curated list of 50 pivotal ideas—grouped into five thematic waves—that collectively formed the foundation of today’s AI landscape.
Logic Theorist: The First AI Program
Logic Theorist: The First AI Program#
The First Machine That Could Deduce Theorems#
1. Setting the Stage: Computing in the 1940s#
- Analog to digital transition: Early mechanical calculators were limited in speed and scope.
- ENIAC and early computers: The Electronic Numerical Integrator and Computer (ENIAC) performed calculations but lacked logical reasoning capabilities.
- Post‑war research: Scientists from IBM, the University of Manchester, and the Massachusetts Institute of Technology (MIT) began exploring programmable machines.
Contextual Insight: By the mid‑1940s, researchers recognized that programs could be stored in memory, giving a machine the ability to perform different tasks—an essential concept for modern AI.