Which technique is often used to handle scalability in machine learning models?
- Dimensionality Reduction
- Ensemble Learning
- Feature Engineering
- Reinforcement Learning
Dimensionality Reduction techniques, like Principal Component Analysis (PCA) or t-Distributed Stochastic Neighbor Embedding (t-SNE), are often used to handle scalability. They reduce the number of features while retaining essential information, making large datasets more manageable for machine learning models.
The concept of "_______" in AI systems deals with ensuring that the AI does not perform any unsafe or unintended actions.
- AI Alignment
- AI Compliance
- AI Governance
- Ethical AI
The concept of "AI Governance" is essential in AI systems to ensure that they adhere to ethical and legal principles, and they don't perform actions that are unsafe or unintended. It involves oversight and control mechanisms to guide AI behavior responsibly.
Which of the following is a common technical challenge in developing AI systems?
- Color Schemes
- Data Quality
- Typography
- User Interface Design
Data Quality is a common technical challenge in AI development because the quality of data directly impacts the performance and accuracy of AI models. Clean, relevant, and well-structured data is essential for training AI systems effectively.
In the context of privacy-preserving AI, what is the primary purpose of homomorphic encryption?
- To anonymize user identities.
- To perform computations on encrypted data without decryption.
- To protect data during transmission.
- To securely store data in the cloud.
The primary purpose of homomorphic encryption is to enable computations on encrypted data without the need for decryption. This is crucial for privacy-preserving AI as it allows data to remain encrypted while still being useful for analysis and processing.
The Chinese Room Argument, which challenges the concept of strong AI, was proposed by philosopher _______.
- Alan Turing
- John Searle
- Marvin Minsky
- Ray Kurzweil
The Chinese Room Argument was proposed by philosopher John Searle in 1980. It argues that simply running a computer program cannot give a machine a "mind" or consciousness, challenging the idea of strong artificial intelligence.
Which international organization has set guidelines for the development and use of AI technologies globally?
- International Monetary Fund (IMF)
- North Atlantic Treaty Organization (NATO)
- United Nations (UN)
- World Health Organization (WHO)
The United Nations (UN) has been actively involved in setting guidelines and discussions on AI technologies to ensure they are developed and used in a way that is safe, ethical, and aligned with global interests. Other organizations may have their roles but are not as central to AI governance.
How does a "language model" assist in the functionality of NLP?
- It extracts named entities from a text.
- It identifies the sentiment of a text.
- It provides a statistical model for understanding grammar and sentence structure.
- It translates text from one language to another.
A "language model" assists in NLP by providing a statistical framework for understanding the grammar, sentence structure, and context of a given text. Language models, like BERT or GPT-3, enable tasks like text generation, sentiment analysis, and language understanding.
You are tasked with implementing an NLP system that can understand and generate responses in multiple languages for a customer support chatbot. How would you approach this to ensure accurate and contextually relevant responses across different languages?
- Use a single language model for all languages.
- Develop separate language models for each language.
- Use machine translation for language conversion.
- Rely on manual translation for important languages.
The correct approach is to develop separate language models for each language. This allows the system to understand and generate contextually relevant responses in each language, as different languages have unique grammatical structures and nuances.
Which of the following is an example of a safety measure in AI system design?
- Increasing complexity without testing.
- Providing no user documentation.
- Regularly updating AI software.
- Removing all error handling in AI code.
Regularly updating AI software is an essential safety measure in AI system design. Updates often include bug fixes, security enhancements, and improvements in AI performance. Keeping AI systems up to date helps mitigate vulnerabilities and ensures their safe and efficient operation.
What is another term often used to refer to Narrow AI?
- General AI
- Singular AI
- Strong AI
- Weak AI
Another term often used to refer to Narrow AI is "Weak AI." Weak AI is designed to handle specific tasks or problems and does not possess general human-like intelligence.