Where is Knowledge Stored in AI ? Neural Networks, CNNs, Transformers & RL Explain

Ever wondered where AI actually stores what it learns? In this comprehensive video, we explore how different AI architectures store knowledge:

🧠 Neural Networks - How knowledge is encoded in connection weights
📸 CNNs - Feature detection through learned kernel weights
💬 Transformers - Attention patterns and embedding spaces in LLMs
🎮 Reinforcement Learning - Policies and Q-values for decision making

We'll discover the universal truth that connects all AI: learning means adjusting numerical values to encode patterns. Whether it's a simple neural network or GPT-4 with trillions of parameters, they all store knowledge the same fundamental way.

Perfect for AI/ML engineers, students, and anyone curious about how artificial intelligence really works under the hood.

📚 Topics covered:
- Weight-based learning in neural networks
- Gradient descent and how weights learn
- Convolutional kernels as feature detectors
- Hierarchical feature learning in CNNs
- Transformer attention mechanisms
- Word embeddings and semantic spaces
- LLM parameter scaling
- RL policies and Q-learning
- Deep reinforcement learning

#MachineLearning #DeepLearning #AI #NeuralNetworks

Видео Where is Knowledge Stored in AI ? Neural Networks, CNNs, Transformers & RL Explain канала AI Depth School