AI can be categorized broadly into two types: narrow (or weak) AI and general (or strong) AI. Narrow AI is designed and trained for a specific task, such as facial recognition, internet searches, or driving a car. These systems operate under a limited pre-defined range or context and don't possess general intelligence or consciousness. Most AI applications today, from Siri and Alexa to more sophisticated systems that diagnose diseases, are examples of narrow AI.
On the other hand, artificial general intelligence (AGI) is a theoretical concept where a machine would have the ability to understand, learn, and apply its intelligence broadly across different domains, mimicking human intelligence. AGI would be capable of reasoning, solving problems, making judgments under uncertainty, planning, learning, and integrating these skills toward common goals in a wide range of environments. AGI remains a goal far off on the horizon of AI research.
The foundation of AI includes several disciplines, including computer science, cognitive science, linguistics, psychology, and more. Techniques in AI range from rule-based systems and decision trees to more complex methods like machine learning (ML) and deep learning, which use neural networks to process and learn from large amounts of data.
AI's impact is widespread and growing, touching every sector from healthcare, where it helps with diagnosis and personalized medicine, to finance, autonomous vehicles, and beyond, revolutionizing how we live, work, and interact.
What is AI?
Artificial Intelligence (AI) is a branch of computer science focused on creating systems that can perform tasks typically requiring human intelligence. These tasks include reasoning, learning, perception, problem-solving, language understanding, and creativity. AI technologies enable machines to improve their performance over time-based on experience, much like humans learn from their actions and their environment.