AI Developmental Stages Quiz

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Questions and Answers

Which of the following is a subfield of AI that relies on complex statistical models and multiple layers of parallel processing?

Artificial neural networks

Machine learning

Data preprocessing

Deep learning (correct)

What is a key requirement for successful deep learning models?

Weak processing units

Predefined rules for task-specific operations

Large datasets and powerful processing units (correct)

Small datasets

Which of the following techniques is based on algorithms that can improve performance with more data over time?

Deep learning

Machine learning (correct)

Natural language processing

Data preprocessing

What is the purpose of artificial neural networks in AI?

To learn how to perform tasks without being programmed with specific rules Signup and view all the answers

Which of the following is a key step in preparing data for machine learning and deep learning models?

Data preprocessing Signup and view all the answers

Which AI technique is commonly used for tasks such as text classification, sentiment analysis, and language translation?

Natural language processing Signup and view all the answers

What is Narrow AI?

AI systems that can only perform specific tasks Signup and view all the answers

Which technique is commonly used for preprocessing text data in Natural Language Processing?

Tokenization Signup and view all the answers

What is the goal of data preprocessing in machine learning?

To prepare the data for modeling Signup and view all the answers

Which type of neural network is commonly used for image recognition tasks?

Convolutional Neural Networks Signup and view all the answers

What is the term used to describe the process of updating the weights in a neural network during training?

Backpropagation Signup and view all the answers

What is the key advantage of deep learning models compared to traditional machine learning models?

They can automatically learn features from raw data Signup and view all the answers

What is the general definition of AI?

The ability of a computer to perform various activities in a manner similar to that of intelligent creatures Signup and view all the answers

What are the principles that Responsible AI is based on?

Well-being, respect for the right to make decisions, privacy, solidarity, and sustainable development Signup and view all the answers

What are the key principles of Trustworthy AI?

Objectivity, transparency, and explainability Signup and view all the answers

In the context of search engines, what does coding 'relevance' refer to?

Assigning importance to different elements that affect search result rankings Signup and view all the answers

Which factor influences search engine results based on user characteristics?

The physical location of the user Signup and view all the answers

Is using user profiles to tailor search results an ethical problem?

Yes, because it invades user privacy without consent Signup and view all the answers

Study Notes

AI Development Stages

Narrow AI: systems that can only perform specific tasks, e.g., chess and Go applications, and assistive AI.
General AI: AI technologies that can perform tasks like humans, without human support, in fields like mathematics, physics, art, and law.
Super AI: systems that are far superior to humans in performance and achievement, making independent decisions beyond human capabilities.

AI Concepts and Terms

AI Application: a product or service developed using AI technologies, or created by enriching existing products and services.
AI Technologies: technologies developed using AI techniques and methods, including machine learning, artificial neural networks, and deep learning.
Responsible AI: AI based on principles of well-being, respect, privacy, solidarity, democratic participation, equality, diversity, prudence, responsibility, and sustainable development.
Trustworthy AI: AI built upon value-based principles, including inclusive growth, sustainable development, human-oriented values, objectivity, transparency, and accountability.

AI Subfields

Machine Learning: systems based on algorithms that learn from datasets and improve with more data.
Artificial Neural Networks: structures that learn to perform tasks by taking advantage of data features without being programmed with specific rules.
Deep Learning: a specialized subfield of AI that uses complex statistical models and algorithms with multiple layers of parallel processing to model the biological brain.

AI Case Study: Search Engines

Ethical concerns: search engines are not value-neutral, and their algorithms can prioritize certain information over others.
Search engine functionality: depends on tags and indexing, click rates, page date, links, user location, and settings.
Concerns: autonomy, accuracy, and information quality, as well as the potential for search engines to manipulate or distort information.

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Description

Test your knowledge on the different stages of AI development, from Narrow AI to Deep Learning. Learn about the characteristics and examples of each stage, including the limitations and capabilities of Narrow AI systems.