UsefulLinks
Computer Science
Artificial Intelligence
Generative AI
1. Introduction to Generative AI
2. Mathematical and Technical Foundations
3. Machine Learning Fundamentals
4. Core Generative Model Architectures
5. Transformer Architecture and Language Models
6. Text Generation Applications
7. Image and Visual Generation
8. Audio and Speech Generation
9. Development Lifecycle and Best Practices
10. Practical Implementation Tools
11. Ethical Considerations and Responsible AI
12. Legal and Regulatory Landscape
13. Economic and Social Impact
14. Future Directions and Emerging Trends
14.
Future Directions and Emerging Trends
14.1.
Multimodal AI Systems
14.1.1.
Cross-Modal Understanding
14.1.1.1.
Vision-Language Models
14.1.1.2.
Audio-Visual Models
14.1.1.3.
Text-Audio-Visual Integration
14.1.2.
Unified Multimodal Architectures
14.1.2.1.
Single Model Approaches
14.1.2.2.
Modality-Agnostic Designs
14.1.2.3.
Cross-Modal Transfer
14.2.
Autonomous AI Agents
14.2.1.
Agentic Capabilities
14.2.1.1.
Planning and Reasoning
14.2.1.2.
Tool Use and Integration
14.2.1.3.
Environment Interaction
14.2.2.
Multi-Agent Systems
14.2.2.1.
Agent Collaboration
14.2.2.2.
Distributed Problem Solving
14.2.2.3.
Emergent Behaviors
14.3.
Model Efficiency and Optimization
14.3.1.
Compression Techniques
14.3.1.1.
Model Quantization
14.3.1.2.
Knowledge Distillation
14.3.1.3.
Pruning Methods
14.3.2.
Efficient Architectures
14.3.2.1.
MobileNets for Edge
14.3.2.2.
Sparse Transformers
14.3.2.3.
Mixture of Experts
14.3.3.
Hardware Optimization
14.3.3.1.
Custom AI Chips
14.3.3.2.
Neuromorphic Computing
14.3.3.3.
Quantum Computing Applications
14.4.
Advanced Capabilities
14.4.1.
Reasoning and Logic
14.4.1.1.
Symbolic Reasoning
14.4.1.2.
Causal Inference
14.4.1.3.
Mathematical Problem Solving
14.4.2.
Long-Term Memory
14.4.2.1.
Persistent Memory Systems
14.4.2.2.
Episodic Memory
14.4.2.3.
Continual Learning
14.4.3.
Meta-Learning
14.4.3.1.
Learning to Learn
14.4.3.2.
Few-Shot Adaptation
14.4.3.3.
Transfer Learning Enhancement
14.5.
Research Frontiers
14.5.1.
Interpretability and Explainability
14.5.1.1.
Attention Visualization
14.5.1.2.
Feature Attribution
14.5.1.3.
Mechanistic Interpretability
14.5.2.
Robustness and Reliability
14.5.2.1.
Adversarial Robustness
14.5.2.2.
Out-of-Distribution Generalization
14.5.2.3.
Uncertainty Quantification
14.5.3.
Human-AI Collaboration
14.5.3.1.
Interactive AI Systems
14.5.3.2.
Human-in-the-Loop Learning
14.5.3.3.
Augmented Intelligence
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13. Economic and Social Impact
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1. Introduction to Generative AI