Fundamentals of AI Flashcards

1
Q

What is AI?

A

Development of computer systems or software that can perform tasks that typically require human intelligence

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2
Q

What is weak AI?

A

An AI that can perform one specific task (chatgpt, siri)

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3
Q

What is strong AI?

A

An AI that can perform a variety of functions (self driving cars)

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4
Q

What is the turing test?

A

A test which determines if a machine is considered intelligent.
- Human Interrogator puts questions to both humans and machine
- If the interrogator cannot distinguish the answers from the machine and humans 30% of the time then the machine is considered intelligent (or behaves intelligently)

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5
Q

Give an example of a turing test in real life

A

Online games and chatrooms
AI art generators

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6
Q

What is the chinese room experiment?

A
  • The question if a machine is intelligent or just behaves intelligently
  • Room with a person who does not understand Chinese, they have a rule book which describes how to respond to Chinese characters with other Chinese characters
  • Person outside of room inputs Chinese, person inside uses rule book to find Chinese characters to form a response, produces an output in Chinese.
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7
Q

Give an example of the Chinese room experiment?

A

Google translate

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8
Q

What are the responsibilities we have to do as programmers to maintain ethical AI

A
  • Privacy and security of data
  • Bias and fairness
  • Transparency
  • Accountability
  • Safety
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9
Q

What are the limitations of AI ?

A
  • Limited understanding of the world
  • Difficulty distinguishing facts and opinions
  • Lack of creativity and originality
  • Lack of common sense
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10
Q

What can we do to face the challenges AI presents?

A
  • Collaborative effort between developers
  • Improving GenAI’s algorithms to implement fairness, represent the real world in models and remove biases in data.
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11
Q

What is a transformer?

A

A large language network with hunderds and thousands of parameters

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12
Q

How does chatgpt work?

A

It uses a large language model (specifically a transformer)
- Pre-trained with unsupervised learning on large texts to predict next words
- Fine-tuned with supervised learning for specific tasks

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