AI Introduction: Cognitive Computing and Human Decision Making

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What is the primary advantage of cognitive computing over conventional computing?

It can process large volumes of unstructured data to find insights. (correct)

It can recognize spoken language with perfect accuracy.

It has faster processing speeds for numerical calculations.

It can learn and improve itself over time through machine learning.

Which of the following is NOT one of the four steps in human decision making that cognitive computing aims to mirror?

Optimization (correct)

Evaluation

Observation

Interpretation

How does cognitive computing gain an understanding of context, which is lacking in speech recognition?

By analyzing the grammatical structure of sentences.

By using deep learning algorithms to recognize patterns.

By breaking down sentences into their relational components.

All of the above. (correct)

What is a key advantage of cognitive computing over conventional computing?

It can learn and adapt based on interactions and experiences. Signup and view all the answers

Which of the following examples is NOT provided as an illustration of cognitive computing's potential applications?

A software developer writing a new program. Signup and view all the answers

What is the main difference between Artificial Intelligence and Machine Learning?

Artificial Intelligence simulates intelligent behavior while Machine Learning focuses on data analysis. Signup and view all the answers

What distinguishes Deep Learning from Machine Learning?

Deep Learning involves layered Neural Networks, while Machine Learning uses complex rules-based algorithms. Signup and view all the answers

Why is Data Science important in extracting insights from large amounts of data?

Data Science helps identify patterns, draw inferences, and extract meaning from extensive datasets. Signup and view all the answers

What is the primary characteristic of Neural Networks in Artificial Intelligence?

Neural Networks consist of computing neurons that learn to make decisions over time. Signup and view all the answers

Which statement best describes the relationship between Big Data, Artificial Intelligence, and Data Science?

Big Data can involve Artificial Intelligence and Data Science to analyze significant amounts of data. Signup and view all the answers

How do Machine Learning models differ from rule-based algorithms in problem-solving?

Machine Learning models learn from data examples, unlike rule-based algorithms that follow predefined rules. Signup and view all the answers

What is the key characteristic of Deep Learning algorithms when it comes to learning?

Deep Learning algorithms continuously learn and improve accuracy over time by evaluating decision outcomes. Signup and view all the answers

What distinguishes Big Data from regular data processing methods?

Big Data refers to significant amounts of unstructured data that require specific artificial intelligence algorithms for analysis. Signup and view all the answers

AI Introduction: Cognitive Computing and Human Decision Making

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Questions and Answers

What is the primary advantage of cognitive computing over conventional computing?

Which of the following is NOT one of the four steps in human decision making that cognitive computing aims to mirror?

How does cognitive computing gain an understanding of context, which is lacking in speech recognition?

What is a key advantage of cognitive computing over conventional computing?

Which of the following examples is NOT provided as an illustration of cognitive computing's potential applications?

What is the main difference between Artificial Intelligence and Machine Learning?

What distinguishes Deep Learning from Machine Learning?

Why is Data Science important in extracting insights from large amounts of data?

What is the primary characteristic of Neural Networks in Artificial Intelligence?

Which statement best describes the relationship between Big Data, Artificial Intelligence, and Data Science?

How do Machine Learning models differ from rule-based algorithms in problem-solving?

What is the key characteristic of Deep Learning algorithms when it comes to learning?

What distinguishes Big Data from regular data processing methods?

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