What is artificial narrow intelligence (ANI)?
In 1956, a group of scientists led by John McCarthy, a young assistant-professor of mathematics, gathered at the Dartmouth College, NH, for an ambitious six-week project: Creating computers that could “use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.”
The project kickstarted the field that has become known as artificial intelligence (AI). At the time, the scientists thought that a “2-month, 10-man study of artificial intelligence” would solve the biggest part of the AI equation.
What is the difference between general AI and narrow AI?
Different types of narrow AI technologies
The narrow AI techniques we have today basically fall into two categories: symbolic AI and machine learning.
Machine learning comes in many different flavors. Deep learning... Deep learning is especially good at performing tasks where the data is messy, such as computer vision and natural language processing.
Reinforcement learning,... problems that must be solved through trial-and-error such as robotics.
Why narrow AI?
What comes after narrow AI?
Cognitive scientist Gary Marcus proposes to create hybrid AI systems that combing rule-based systems and neural networks.
Richard Sutton, computer scientist and the co-author of a seminal book on reinforcement learning, believes that the solution to move beyond narrow AI is to continue to scale learning algorithms.
Deep learning pioneer Yoshua Bengio... system 2 deep learning algorithms will be able to perform some form of variable manipulation without the need to have integrated symbolic AI components.
Yann LeCun, another deep learning pioneer, spoke of self-supervised learning at this year’s AAAI Conference.
How do we know if we have moved past narrow AI?
See the full story here: https://bdtechtalks.com/2020/04/09/what-is-narrow-artificial-intelligence-ani/