1												14
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5																				15
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		7		13
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Across

1. The carbon emissions produced by data centers that store and process massive amounts of data for AI applications.

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

3. 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.

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

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

6. A type of artificial intelligence that attempts to simulate human thought processes and decision-making.

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

8. A field of study that uses statistical algorithms to enable a machine to improve its performance on a specific task.

9. A type of machine learning algorithm modeled after the structure of the human brain, capable of learning complex patterns and relationships.

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

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

12. Machine learning models that can generate new and original content, such as images, texts, or music.

Down

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

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

15. An optimization algorithm that mimics the process of natural selection.

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

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