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1. Machine learning software that acts autonomously on a user's behalf.
2. The use of nanoscale materials and devices to create electronic components and circuits with higher efficiency and performance.
3. An optimization algorithm that mimics the process of natural selection.
4. A type of machine learning algorithm that uses principles of evolution to generate solutions to complex problems.
5. A field of study that uses statistical algorithms to enable a machine to improve its performance on a specific task.
6. A branch of cryptography that uses principles of quantum mechanics to secure communication.
7. Explainability is the ability to provide understandable explanations or justifications for the decisions and outcomes generated by an AI system.
8. A field of artificial intelligence that enables computers to interpret and understand the visual world, including images and videos.
9. The manipulation and control of matter on an atomic, molecular, and supramolecular scale, which plays a significant role in DNA computing.
10. The carbon emissions produced by data centers that store and process massive amounts of data for AI applications.
11. Computing that harnesses the principles of quantum mechanics to carry out computations.
12. The technique of enclosing nanoparticles or other substances within a protective shell for improved stability and controlled release.
13. A collection of instructions or operations designed to be executed on a quantum computer in order to solve particular problems.
14. The potential loss of jobs as AI systems become more capable and automated processes replace human labor.