define the following computer science terms\n1. diffusion models\n2. prompt engineering\n3. catastrophic…

Brief Explanations:

1. Diffusion Models: Generative models that transform noise into data - like images through a reverse - diffusion process.
2. Prompt Engineering: Crafting effective prompts to get desired outputs from language models.
3. Catastrophic Forgetting: Neural networks forgetting old knowledge when learning new information.
4. Few - shot Learning: Learning tasks with only a few examples.
5. Neural Radiance Fields: Represent 3D scenes as neural networks for rendering.
6. Zero Trust Architecture: Assumes no user or device is trustworthy by default.
7. Homomorphic Encryption: Allows computations on encrypted data without decryption.
8. Supply Chain Attack: Attack exploiting vulnerabilities in software or hardware supply chains.
9. Credential Stuffing: Using stolen usernames and passwords to access accounts.
10. Sandboxing: Isolating software to prevent it from affecting the system.
11. Bloom Filter: Probabilistic data structure for testing set membership.
12. Hashgraph: Distributed ledger technology for consensus.
13. Federated Learning: Training models across multiple decentralized devices.
14. Gradient Clipping: Limiting the magnitude of gradients to prevent exploding gradients.
15. Backpropagation Through Time: Training recurrent neural networks over sequences.
16. Infrastructure as Code: Managing infrastructure via code.
17. Blue - Green Deployment: Deployment strategy with two identical environments.
18. Observability: Ability to understand the internal state of a system.
19. Container Orchestration: Automating deployment, scaling, and management of containers.
20. Immutable Infrastructure: Infrastructure that is replaced instead of modified.
21. WebAssembly: Binary - format instruction set for web browsers.
22. Progressive Web App: Web app with app - like features.
23. Edge Computing: Processing data at the edge of the network.
24. Digital Twin: Virtual representation of a real - world entity.
25. Quantum Supremacy: Quantum computers outperforming classical computers on specific tasks.

Answer:

1. Generative models using reverse - diffusion.
2. Crafting prompts for language models.
3. Forgetting old knowledge on new learning.
4. Learning with few examples.
5. 3D scene neural network representation.
6. No - trust - by - default architecture.
7. Computation on encrypted data.
8. Supply chain exploitation attack.
9. Using stolen credentials.
10. Software isolation.
11. Probabilistic set membership structure.
12. Distributed ledger consensus tech.
13. Decentralized model training.
14. Limiting gradient magnitude.
15. RNN training over sequences.
16. Code - based infrastructure management.
17. Two - environment deployment.
18. Understanding system internal state.
19. Automated container management.
20. Replaceable infrastructure.
21. Web browser binary instruction set.
22. App - like web app.
23. Network - edge data processing.
24. Virtual real - world entity.
25. Quantum computer superiority.