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Moravec’s Paradox: Explained in five levels of difficulty with practical examples

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Summary

Moravec's Paradox is an observation by AI and robotics researchers that reasoning requires very little computational resources while sensorimotor and perception skills require enormous computational resources. This concept was articulated by Hans Moravec and others, and is considered a guiding principle in the development of modern robotics. Chelsea Finn, Assistant Professor in Computer Science and Electrical Engineering at Stanford University, explains the concept in five different levels of difficulty to a child, teen, college student, grad student, and expert. The example of picking up a penny is used to demonstrate the difficulty in programming a robot to recognize and complete a task easily done by humans. Solutions to this paradox are explored, such as offering structure and support to the robot, or training robots with prior learnings from data and offline sources. It is concluded that robots are better at completing higher level tasks like playing chess than simpler tasks, and will likely accompany humans instead of replacing them.

Q&As

What is Moravec's Paradox?
Moravec's Paradox is an observation by artificial intelligence and robotics researchers that reasoning requires very little computation while sensorimotor and perception skills require enormous computational resources.

How does Moravec's Paradox contradict traditional assumptions?
Moravec's Paradox is contrary to traditional assumptions that robots can easily reverse-engineer human skills.

What is the difference between what robots are trained to do and what they are asked to do?
The difference between what robots are trained to do and what they are asked to do is the generalisation gap, wherein there is a difference between what the robot is trained to do and the new thing it is asked to do.

How can robots better learn new tasks?
Robots can better learn new tasks by offering structure and support to the robot, acquiring prior learnings about the world and interaction from previous data and even offline data, and training perception and action components in sync with each other.

What are some of the challenges observed in relation to Moravec's Paradox?
Some of the challenges observed in relation to Moravec's Paradox are that robots have been really good at understanding and overcoming hard problems but have found easier problems difficult to tackle, and that the oldest human skills are largely unconscious and thus appear to be effortless, making them difficult to reverse-engineer.

AI Comments

👍 This article does a great job of explaining Moravec’s paradox in an easy-to-understand way for readers of all ages and levels of expertise.

👎 This article does not provide any practical solutions for how to address Moravec’s paradox.

AI Discussion

Me: It's about Moravec's Paradox and how artificial intelligence and robotics researchers have observed that reasoning requires very little computation while sensorimotor and perception skills require enormous computational resources. It explains the concept in five different levels of difficulty.

Friend: Interesting. What are some of the implications of this article?

Me: Well, the article is a reminder that robots can do some tasks more efficiently than humans, but they can also struggle with tasks that seem simple to humans. It also implies that if we want robots to be able to do more complex tasks, we have to invest more time and energy into programming them. Additionally, there are a lot of implications for the future of robotics. We may have to rethink how robots are designed and developed in order to take advantage of their abilities and minimize their struggles.

Action items

Research and explore the concept of Moravec’s paradox further to gain a better understanding of the implications of this phenomenon.
Experiment with AI-powered tools to gain a better understanding of the challenges associated with Moravec’s paradox.
Develop a project to explore the potential of AI-powered tools to overcome the challenges associated with Moravec’s paradox.

Technical terms

Moravec’s Paradox: A phenomenon offering observations surrounding the abilities of AI-powered tools, especially robots. It is an observation by artificial intelligence and robotics researchers that reasoning requires very little computation while sensorimotor and perception skills require enormous computational resources.
Perception Action Loop: The process of a robot perceiving an object and then taking action to interact with it.
Generalisation Gap: The difference between what a robot is trained to do and the new thing it is asked to do.
Skill Transfer Style of Learning: A method of training robots to learn new tasks by acquiring prior learnings about the world and interaction from previous data and even offline data.
Abstraction: The process of simplifying a complex system or concept by reducing or abstracting away details.