Artificial intelligence (AI) refers to computer systems that can perform tasks that typically require human intelligence such as visual perception, speech recognition, and decision-making. The concept dates back to ideas like “thinking machines” in the 1950s but has seen huge breakthroughs recently.

At its core, AI leverages machines to mimic cognitive functions like learning patterns from experiences, reasoning through logic, or handling complex optimization puzzles. This differs from traditional computing which simply executes rote programming instructions at high speeds without adapting. By ingesting training data like images, texts, sounds or sensor recordings, related algorithms self-improve at processing future real-world sensory inputs.

Modern AI branches into narrow AI and general AI. Narrow AI focuses individual algorithms on excelling at singular tasks like recommending purchases, transcribing speech, spotting tumors in radiology scans or defeating grandmasters at chess. Though displaying intelligence, narrow AI systems remain confined to their domain without flexible reasoning.

In contrast, hypothetical general technology aims to develop multifaceted systems with the cross-domain adaptability to replicate the full span of human cognition. But we are likely still decades away from creating broadly intelligent machines that match or exceed human-level thought complexity. Ongoing advances in computational power, neural system architectures, algorithm efficiency and training methodology continue marching towards the still distant goal.

Already, present-day narrow AI empowers many convenient consumer conveniences like virtual assistants, language translation apps, facial recognition on smartphones, personalized media feeds and autopilot systems in vehicles. Meanwhile in sectors like finance and healthcare, AI drives everything from detecting credit card fraud to diagnosing diseases earlier than human clinicians.

Looking ahead this century, pioneers envision AI accelerating scientific discoveries, revolutionizing transportation through autonomous vehicles, or even synthesizing creative arts like music, writing and inventions. Yet thought leaders including scientists, entrepreneurs and policymakers also caution that without foresight into the societal risks, the technology could exacerbate economic inequality or geopolitical tensions instead. Guiding AI toward benefiting humanity remains an ongoing challenge requiring ethical evolution in parallel with innovation.