Understanding AI and Algorithms

What is the definition of Artificial Intelligence (AI)?

• Artificial Intelligence (AI) is the ability of machines to perform physical tasks without human intervention.

• Artificial Intelligence (AI) is the process of programming computers to follow strict rules without learning from experience.

• Artificial Intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems.

• Artificial Intelligence (AI) refers to the use of algorithms to analyze data without any human-like reasoning.

Who is considered the father of AI?

• Herbert Simon

• Alan Turing

• Marvin Minsky

• John McCarthy

In which year was the term 'Artificial Intelligence' first coined?

• 1972

• 1980

• 1965

• 1956

What are the main types of AI?

• Deep Learning Models

• Narrow AI, General AI, Superintelligent AI

• Artificial Neural Networks

• Machine Learning Algorithms

How do algorithms relate to AI?

• AI operates independently of algorithms and data processing.

• Algorithms are irrelevant to decision-making in AI.

• Algorithms are fundamental to AI as they provide the methods for data processing and decision-making.

• Algorithms are only used in traditional programming, not AI.

What is machine learning in the context of AI?

• Machine learning is a type of hardware used in AI systems.

• Machine learning is a subset of AI that enables systems to learn from data and improve their performance over time.

• Machine learning is a method for storing data in AI systems.

• Machine learning is a programming language for AI development.

Can you name a famous AI program from history?

• Microsoft's Cortana

• Google's Assistant

• Apple's Siri

• IBM's Deep Blue

What role did the Turing Test play in AI development?

• The Turing Test is a method for measuring the speed of computer processors.

• The Turing Test was primarily focused on machine learning algorithms.

• The Turing Test was developed to evaluate hardware performance in computing.

• The Turing Test played a crucial role in AI development by establishing a standard for assessing machine intelligence and inspiring research in natural language processing and human-computer interaction.

What is the difference between supervised and unsupervised learning?

• Supervised learning requires no data; unsupervised learning requires all data.

• Supervised learning is faster than unsupervised learning; unsupervised learning is slower.

• Supervised learning is only for classification tasks; unsupervised learning is only for regression tasks.

• Supervised learning uses labeled data; unsupervised learning uses unlabeled data.

How has AI evolved over the decades?

• AI has always relied solely on human intuition.

• AI is only used in gaming and entertainment.

• AI development has stagnated since the 1980s.

• AI has evolved from symbolic systems to machine learning and deep learning, leading to advanced applications in various fields.