tt

The Turing Test

A test that determines whether a machine can exhibit intelligent behavior indistinguishable from humans.

Benefits of AI

Includes advancements in healthcare, automation, data analytics, and increased efficiency.

Creative destruction

The process whereby new innovations replace old technologies and industries.

Ethical decision making in warfare

Concerns about AI's role in combat, including biases and malfunctioning weapons.

Erik Hoel's concern

AI art could devalue human creativity, affecting art as a form of communication.

The Singularity

A hypothetical point where AI surpasses human intelligence, leading to exponential growth.

Exponential growth

Rapid growth characterized by an accelerating rate of increase.

Counterarguments to the Singularity

Potential barriers include diminishing inputs and increasing costs of development.

Symbolic AI

Type of AI based on rule-based logic and explicit programming.

Sub-symbolic AI

Type of AI based on pattern recognition and learning through neural networks.

Perceptron

A machine learning model that processes input data to produce an output.

Hype problem in AI

Blind trust in AI capabilities compared to its actual progress.

Supervised learning

A process where algorithms learn from labeled datasets to predict outcomes.

Neural network

A machine learning model with layers of interconnected nodes for pattern recognition.

Deep Learning

Uses multiple layers of processing to extract higher-level features from data.

Deep Neural Networks

Neural networks with multiple layers learning complex patterns from data.

Back-propagation

A method of adjusting weights to minimize error in neural networks.

Convolutional Neural Networks

Designed for image analysis, leveraging convolution operations for feature extraction.

Unsupervised learning

A learning method where algorithms find patterns without labeled data.

K-means clustering

Groups data into k clusters by minimizing the distance between points and the centroid.

Reinforcement learning

AI method where agents learn through trial and error via rewards and punishments.

Q-table

Data structure in Q-learning that stores state-action values for decision-making.

Explore-Exploit tradeoff

The balance between trying new actions and using known best actions.

Marcus’s 10 Points on AI’s Limits

Highlights AI's struggles with common sense, reasoning, and robustness.

Hybrid models

AI models that combine symbolic reasoning with neural networks for improvement.

Motte and Bailey argument

An argument structure where a strong claim (motte) is supported by a less defensible claim (bailey).

Labor-saving technology

AI technology that often leads to job creation by increasing efficiency and demand.

Economy-wide unemployment

AI's efficiency does not typically cause widespread unemployment due to market adaptations.

Semantic Apocalypse

Concept by Erik Hoel suggesting that AI threatens creative human endeavors.

The Singularity definition

A point at which technological development exceeds historical precedent.

Diminishing returns in Singularity

A phenomenon where growth will not continue at an accelerating rate due to resource limits.

Regression in machine learning

Estimating a numeric value based on learned parameters from data.

Symbolic vs. Sub-Symbolic

Two competing dominant approaches in the history of machine learning.

Expected value of an action

A weighted average of potential outcomes of an action.

Complex object recognition

Can be enhanced by introducing layers into neural networks.

Convolution processes

Involves multiplying values in a receptive field by weights and summing results.

Unsupervised learning types

Main types include clustering and dimensionality reduction.

Goal of K-means Clustering

To identify existing patterns within a dataset.

Q-Table function

Stores results from trial-and-error processes in reinforcement learning.

Marcus on AI flaws

Critiques the lack of generalizability and understanding in current AI approaches.

Marcus's recommendation against AI cessation

He does not support ceasing or defunding AI research.

Building AI model parameters

Marcus advises against merely increasing model parameters without understanding.

Data inefficiency critiques

Refers to AI’s heavy reliance on large datasets for training.

AI's role in healthcare

AI applications leading to improved diagnoses, treatments, and health management.

Automation advantages

AI can take over mundane tasks, freeing humans for more complex activities.

Bias in AI

Concerns about racial biases being inherent in AI decision-making.

AI in warfare

Challenges in ethical decision-making with autonomous weapons.

Human-Machine Symbiosis

Collaborative interaction between humans and AI for improved outcomes.

AI's impact on creativity

Concerns that AI-generated art may devalue human artistic expression.

Growth of neural networks

Utilizes layers to increase the precision and capability of AI learning.

Anomaly detection

An unsupervised learning task that identifies data points that deviate from the norm.

Euclidean distance in clustering

A measure used to determine similarity between data points in clustering algorithms.