Artificial Intelligence (AI) Online Test

1. Which type of processing unit is commonly used for inference tasks in deep learning applications?

2. What feature of Python makes it well-suited for developing GANs?

3. Which limitation of AI arises from the challenge of integrating AI systems with existing infrastructure or workflows?

4. Which limitation of AI is related to the challenge of ensuring the security and privacy of sensitive data used by AI systems?

5. Which Python library provides an intuitive and flexible interface for deep learning research and development?

6. Which industry utilizes Artificial Intelligence for predictive maintenance of machinery and equipment to reduce downtime and optimize operations?

7. In fraud detection, what is the primary role of Artificial Intelligence techniques?

8. Which AI application involves using algorithms to analyze financial data, market trends, and historical patterns to make investment decisions and optimize portfolio management?

9. What term refers to the ability of AI systems to automatically improve and adapt their performance over time without explicit programming or human intervention?

10. How can organizations maximize the benefits of human-AI collaboration technology?

11. Which limitation of AI is related to the potential for adversarial attacks to deceive or manipulate AI models?

12. Which industry employs Artificial Intelligence for route optimization, demand forecasting, fleet management, and autonomous vehicles?

13. Which optimization technique is commonly used to train Generative Adversarial Networks (GANs)?

14. Which AI application involves using algorithms to analyze and interpret human behavior, preferences, and interactions with digital systems to personalize user experiences?

15. Which type of memory is used for storing frequently accessed data and instructions to improve CPU performance?

16. In industrial automation, which AI-based approach focuses on improving product quality by analyzing and adjusting manufacturing processes in real-time?

17. What challenge arises from the potential for AI systems to exhibit unintended behaviors or consequences that were not anticipated during development?

18. What role does NumPy play in implementing GANs with Python?

19. Which Python library is often used for building and training deep learning models, including GANs?

20. Which programming language is often used in conjunction with Python for numerical computing and scientific research?

21. Which programming language is often used for developing deep learning models with the PyTorch framework?

22. How does AI contribute to enhancing human capabilities?

23. What challenge arises from the potential for AI systems to make decisions with significant social or ethical implications without human oversight or intervention?

24. In self-driving cars, which AI-based module is responsible for planning the vehicle's trajectory and making decisions about route navigation?

25. Which task is instance segmentation most closely related to?

26. What is one advantage of using Theano for deep learning development?

27. Which AI application involves using algorithms to analyze patient data, medical records, and clinical outcomes to improve healthcare delivery, patient outcomes, and population health management?

28. Which Artificial Intelligence technique is commonly used in fraud detection to assign fraud scores to transactions based on their likelihood of being fraudulent?

29. Which term describes the process in a GAN where the discriminator network is trained to classify between real and fake data samples?

30. What is one advantage of using Python for deep learning development?