Useful Links
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
Future Directions and Emerging Trends
Multimodal AI Systems
Cross-Modal Understanding
Vision-Language Models
Audio-Visual Models
Text-Audio-Visual Integration
Unified Multimodal Architectures
Single Model Approaches
Modality-Agnostic Designs
Cross-Modal Transfer
Autonomous AI Agents
Agentic Capabilities
Planning and Reasoning
Tool Use and Integration
Environment Interaction
Multi-Agent Systems
Agent Collaboration
Distributed Problem Solving
Emergent Behaviors
Model Efficiency and Optimization
Compression Techniques
Model Quantization
Knowledge Distillation
Pruning Methods
Efficient Architectures
MobileNets for Edge
Sparse Transformers
Mixture of Experts
Hardware Optimization
Custom AI Chips
Neuromorphic Computing
Quantum Computing Applications
Advanced Capabilities
Reasoning and Logic
Symbolic Reasoning
Causal Inference
Mathematical Problem Solving
Long-Term Memory
Persistent Memory Systems
Episodic Memory
Continual Learning
Meta-Learning
Learning to Learn
Few-Shot Adaptation
Transfer Learning Enhancement
Research Frontiers
Interpretability and Explainability
Attention Visualization
Feature Attribution
Mechanistic Interpretability
Robustness and Reliability
Adversarial Robustness
Out-of-Distribution Generalization
Uncertainty Quantification
Human-AI Collaboration
Interactive AI Systems
Human-in-the-Loop Learning
Augmented Intelligence
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13. Economic and Social Impact
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1. Introduction to Generative AI