AI, or artificial intelligence, is software that mimics the human brain.
AI can learn how to perform specific tasks by processing a huge amount of similar examples. It can also continuously adapt to new inputs and improve its abilities over time. All without humans having to get involved.
It's useful to think of AI as a mechanical brain.
Just as the human brain processes sensory information and uses it to make decisions about how our body should act, AI decides what the device or devices it powers should do next based on the inputs it receives. The difference is that, instead of smells, sights, touch, and taste, AI processes text, audio, and code.
AI's main practical application is machine learning — a process in which human trainers feed data to the AI so it can master new skills.
In machine learning, AI "reads" the data and tests its understanding of it, iterating and improving over time. This is very similar to the way humans acquire knowledge.
Machine learning can train AI to do an extremely wide range of things — from recognizing human speech and engaging in conversation using natural language, to driving a vehicle, playing games, and composing music.
AI can also be deployed in many different ways: in software, in electronic devices, and even in everyday items like speakers, refrigerators, and cars.
English mathematician and cryptographer Alan Turing is credited with being the first scientist to explore artificial intelligence. In 1950, he devised an experiment, called the Turing Test, to determine whether computers could think like humans.
Turing concluded that, since humans use logic and the information that's available to them to solve problems and make decisions, there was no reason why computers couldn't do the same.
Over the next 70-odd years, many scientists continued Turing's pioneering work, including American John McCarthy — the man who coined the term "artificial intelligence". But computers' limited memory and processing power meant progress was painfully slow.
The technology only became truly feasible in the 1990s, when computers improved enough to support the sophisticated algorithms and machine learning techniques AI requires.
Once computing technology caught up, AI made huge strides in a relatively short period of time. In 1997, a supercomputer called Deep Blue beat world chess champion Gary Kasparov. And, in 2016, another AI beat a human at Go — an ancient Chinese game that has far more possible moves and relies a lot more on intuition than chess does.
Today, we have AI-powered personal assistants — Siri, Alexa, Cortana, Google Assistant — self-driving cars, and AI that can help diagnose diseases and assist during surgical procedures. And deep learning models, such as GPT, can "understand" human speech and text — including ambiguous or unclear words — and formulate appropriate responses in natural, human-sounding language.
Want to know more?
This is the paper that started it all. Alan Turing lays out his reasoning for why artificial intelligence is possible and explains how to build AI machines and test their intelligence.
While AI has many compelling use cases, it also raises some serious ethical issues. This article explores key dilemmas, including the potential for bias and misuse, as well as the most burning question of all — will AI lead to mass unemployment?
AI is one of the most exciting technological developments of our time, because it has the potential to solve significant challenges and create many new opportunities.
In customer service, for instance — an area where the sheer workload means firms often struggle to meet expectations — AI can take care admin much more efficiently, tackle run-of-the-mill requests, and free up customer service reps so they can stop chasing their tails and focus on what matters most: surprising and delighting customers.
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