1	12						13
			2
						3																15
																		14
									4
					5
6
	7/11
8
	9
10

Across

1. A type of machine learning algorithm that uses principles of evolution to generate solutions to complex problems.

2. AI systems are limited to what they have been trained on and cannot generate truly original ideas or concepts.

3. The potential loss of jobs as AI systems become more capable and automated processes replace human labor.

4. A subfield of artificial intelligence that focuses on creating machines or models capable of generating new content or responses based on existing data or patterns.

5. Using historical data and machine learning algorithms to make predictions about future events or outcomes.

6. AI systems collect and process vast amounts of personal data, raising concerns about privacy and data protection.

7. A field of artificial intelligence that enables computers to interpret and understand the visual world, including images and videos.

8. AI systems often face ethical dilemmas where they have to make decisions that may have moral implications, raising concerns about accountability and responsibility.

9. The ability of machines or AI systems to produce original and creative works, such as art, music, or writing.

10. Machine learning software that acts autonomously on a user's behalf.

Down

11. The reduction in expenses or overhead through the implementation of AI.

12. A type of artificial intelligence that uses a knowledge base and inference rules to solve complex problems in a specialized domain.

13. Vehicles that are capable of operating without human intervention, using sensors and machine learning algorithms to navigate and make decisions.

14. A type of machine learning algorithm that uses layers of neural networks to learn and make predictions from complex data sets.

15. The simulation of human intelligence processes by computer systems.

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