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Questions and Answers
What role did Alan Turing play in the development of artificial intelligence?
What was a significant outcome of Arthur Samuel's achievements in AI?
Which programming language was created by John McCarthy for AI research?
During what period did the term 'AI winter' occur?
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What is a recognized application of deep learning?
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What distinguishes Machine Learning from Rule-based Systems in AI?
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Which application is NOT associated with Rule-based Expert Systems?
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What characterizes Deep Learning compared to classical Machine Learning?
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How does Machine Learning improve its accuracy in classification tasks?
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What is one main limitation of Rule-based Systems compared to Machine Learning?
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In the context of AI, what is meant by the term 'intelligent behavior'?
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What is a primary function of a Rule-based Expert System in medical diagnosis?
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Which statement correctly describes the relationship between data and machine learning?
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What was a significant factor that caused the decline in interest in AI during the AI winter?
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What advancement in AI was particularly noted for allowing computers to learn from their mistakes?
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Which decade is associated with the first autonomous vehicle built by a Stanford student?
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What was a consequence of the AI Winter in the 1980s?
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During which period did deep learning achieve significant breakthroughs?
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What trend characterized the AI Boom described in the content?
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What type of systems became more popular during the AI Boom due to their independent decision-making capabilities?
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Which of the following was NOT a characteristic of the AI Winter?
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Study Notes
Definition of Artificial Intelligence
- AI involves simulating intelligent behaviors in computers to perform tasks like reasoning, decision-making, and problem-solving without human intervention.
Types of Artificial Intelligence
- Machine Learning (ML): Programs learn patterns from exposure to data over time without explicit programming.
- The performance of ML algorithms improves as they receive more data, enhancing their ability to identify patterns.
Rule-Based Expert Systems
- Rule-based systems utilize pre-programmed rules to mimic expert decision-making in specific fields, such as:
- Medical Diagnosis: Systems diagnose based on symptoms and medical history.
- Fraud Detection: Systems identify fraudulent transactions through analysis of transaction data.
Deep Learning
- A subset of machine learning that utilizes deep neural networks to analyze data.
- Mimics human brain functioning, requiring substantial amounts of data to train effectively.
- Automatically determines significant data representations without human intervention.
Breakthroughs in AI
- Natural Language Processing: Involves understanding and processing human language.
- Computer Vision: Enables machines to interpret and classify visual data, such as image recognition.
Historical Context
- AI has experienced various hype cycles, characterized by alternating periods of excitement and disillusionment.
- 1950s: Alan Turing introduces the Turing Test; Arthur Samuel develops an independent learning checkers program.
- 1960s-70s: Early algorithms and the establishment of expert systems emerge.
- 1980s: AI experiences "AI Winter" due to failed expectations and funding cuts.
Growth and Decline
- Initial enthusiasm for AI led to notable developments, including the first autonomous vehicle at Stanford.
- Lack of significant advances caused reduced government funding and interest in AI research.
AI Boom
- Renewed interest in AI during the late 1990s and early 2000s was propelled by breakthroughs in deep learning and increased funding.
- Technologies evolved that allowed systems to learn from mistakes, improving independent decision-making.
AI Winter
- A period characterized by reduced public and private investment due to high costs associated with AI development and insufficient returns on investment.
- Collapse of LISP-based hardware market attributed to competition from more affordable and capable alternatives like IBM and Apple.
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Description
This quiz delves into the fundamentals of Artificial Intelligence, explaining its significance in computer science and its capacity to perform tasks that normally require human intelligence. Test your understanding of key concepts and applications of AI.
