Overview
Artificial intelligence, or AI, is the use of computers to simulate human intellectual abilities. Its history dates back to the 1940's when Alan Turing proposed that intelligent machines could be created through code. Today it is one of the most transforming technologies that has emerged in our society and continues to evolve exponentially. There are countless opportunities for AI in all industries including healthcare, safety, agriculture, transportation and more.
Artificial Intelligence is the newest buzzword of our time. With each passing day, Artificial Intelligence progresses leaps and bounds to new levels of intelligence. And one cannot help but wonder why this topic is so important? To answer that question, we have to go back in history and understand how it all started.
Thus, let's look at the history of Artificial Intelligence. This will not be an in-depth analysis but a brief overview of the techniques and technologies behind AI which led to its evolution.
A Brief History of AI
- 1956
The term “artificial intelligence” is coined at a Dartmouth conference and AI is founded as an academic discipline.
- 1956–1974
The golden years of AI enjoy government funding in promising, logic-based problem-solving approaches.
- 1974–1980
Overly high expectations coupled with the limited capacities of AI programs leads to the first “AI winter”, with reduced funding and interest in AI research.
- 1980–1987
The rise of knowledge-based expert systems brings new successes and a change in the focus of research and funding toward this form of AI.
- 1987–1993
The second “AI winter” starts with the sudden collapse of the specialized hardware industry in 1987. The AI hype brings with it negative perceptions by governments and investors, as expert systems show their limitations and prove expensive to update and maintain.
- 1993–2011
Optimism about AI returns and increases. New successes are marked with the help of increased computational power and AI becomes data-driven. In 1997, IBM’s DeepBlue beats world champion Kasparov at chess. In 2002, Amazon uses automated systems to provide recommendations. In 2011, Apple releases Siri and IBM Watson beats two human champions at the TV quiz Jeopardy.
- 2012–today
Increased availability of data, connectedness and computational power allow for breakthroughs in machine learning, mainly in neural networks and deep learning, heralding a new era of increased funding and optimism about the AI potential. In 2012, Google driverless cars navigate autonomously and in 2016 Google AlphaGo beats a world champion in the complicated board game Go.
The future of AI and the opportunities it brings
The growth in computing power and connectedness, which enables large volumes of data to be compiled and shared, has opened up many new opportunities for AI technologies, which are in turn reinforced by the greater availability, systematic collection of and access to data.
The impact of AI technologies on humans is likely to be profound. Martin Ford, author of The Rise of the Robots, thinks many workers will have to become skilled in different areas, while employers and governments will have to address how best to deal with the loss of employment and growing inequality. “In the next 10 to 20 years,” he predicts, “the jobs that will be most vulnerable to automation will be those that are routine and predictable. If what you do is encapsulated in data, at some point it’s a pretty good bet that there will be an AI that can do that kind of work.”
Source: WIPO
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