The Robot Challenge: Course Introduction

Flashcards covering key vocabulary terms and concepts from the 'Robot Challenge' lecture notes, focusing on the complexities of vision, common sense, and the reverse-engineering approach to understanding the mind.

Computer Strengths

Easily performs tasks that humans find difficult, such as beating a master chess player or multiplying large numbers.

Computer Weaknesses

Has difficulty performing tasks that humans find easy, such as navigating a crowded field, picture recognition, or walking on two legs.

Robot's-Eye View (Cinematic vs. Actual)

In movies, often uses cinematic conventions like fish-eye or crosshairs for human viewers, but is no help to the machine itself.

Robot Vision Data

Appears as an array of numbers, where each number represents the brightness of one of millions of light-sensitive patches in the visual field.

Visual System Challenge (Object Boundaries)

The difficulty for a robot's visual system to locate where an object ends and the backdrop begins, given the world is a mosaic of tiny shaded patches, not cartoon-like bold lines.

'Rule of Thumb' (for Visual System)

A potential solution for the visual system to locate object boundaries by looking for adjacent abrupt changes in numbers representing brightness, although this method is not always effective.

Snow or Coal Dilemma

The challenge of differentiating objects based on their perceived lightness or darkness, which is complicated by the brightness or dimness of the light illuminating the object, making simple numerical interpretation unreliable.

Factors Affecting Light on Retina

The amount of light hitting a spot on the retina depends on both how pale or dark the object is and how bright or dim the light illuminating the object is.

Camera vs. Human Visual System

Cameras often struggle to render realistic images under varying illumination (e.g., outdoor scenes as 'milk,' indoor scenes as 'mud'), whereas the human visual system excels at distinguishing object color despite illumination changes.

Harmony of Vision

The spectacular neural achievement of reconciling how the world looks with how the world truly is, allowing us to perceive consistent object properties despite varying sensory input.

Common Sense (in AI/Robotics)

The ability of an intelligent being to categorize objects and apply knowledge from similar past encounters, rather than treating every object as novel.

Categorization Challenge

The difficulty in programming a set of precise criteria to define members of a category (like 'bachelor') because real-world examples often defy strict definitions.

Tacit Knowledge

Facts we implicitly know but were never explicitly taught, which form a crucial part of human common sense but are not easily cataloged in a database.

Rules of Common Sense (AI difficulty)

The inherent difficulty in setting down a small list of core truths and deduction rules that can guide a robot's behavior, especially considering the need to compute both direct and indirect (side) effects of actions without infinite predictions.

Consciousness-Raising (Robot Design)

The process of designing robots, which highlights the incredible complexity and sophistication of our human mental lives, making us appreciate what we often take for granted.

Illusion of Simplicity

The false impression that our mental processes, like moving limbs or perceiving the world, are simple, when in reality they are the result of highly complex 'neural wizardry.'

Mind (Computational View)

A system of organs of computation designed to solve problems, including understanding and outmaneuvering objects, animals, plants, and other people.

Psychology as Reverse-Engineering

An approach to psychology that seeks to figure out what a machine (the mind) was designed to do, analogous to analyzing a product to understand its function and components, rather than designing it from scratch (forward-engineering).

Darwin's Contribution (to Reverse-Engineering the Mind)

Showed how 'organs of extreme perfection and complication,' including the mind, arise from the evolution of replicators over immense spans of time, laying the foundation for understanding the mind's design through evolution.