How AI Really Thinks: From Latent Space to Gradient Descent (Explained) скачать в хорошем качестве

How AI Really Thinks: From Latent Space to Gradient Descent (Explained)

We often hear that AI "learns" or "hallucinates," but what is actually happening inside the black box? In this video, we deconstruct the architecture of modern Artificial Intelligence to understand the math behind the magic. We move beyond simple metaphors to explore the true mechanisms of digital cognition. In this video, we cover: • Training vs. Inference: Why AI is like a student studying for years (training) vs. taking a final exam (inference). • The "Foggy Mountain": Understanding Gradient Descent and how models minimize errors. • The "Blame Game": How Backpropagation allows neural networks to learn from their mistakes by adjusting billions of parameters. • The Map of Meaning: Visualizing Latent Space and Embeddings—think of it like a supermarket where similar concepts (apples and bananas) are shelved together. • The Transformer Revolution: A look at the "Attention Is All You Need" paper and how Self-Attention changed everything. • The Probabilistic Storyteller: How AI predicts the next word using logits, softmax, and temperature. Stop anthropomorphizing the machine and start understanding the architecture of digital synthesis. Tags: #AI #MachineLearning #DeepLearning #Transformers #NeuralNetworks #Backpropagation #LatentSpace #LLM