training and backprop

Behind the Scenes of ChatGPT: How Language Models Actually Work

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Language models turn text into numbers, learn how those numbers relate, and then predict the next token with astonishing accuracy using transformer networks that focus attention on the most relevant parts of the context.​ Tokens, embeddings, and context Transformers and self‑attention Layers that build meaning Training: predicting the next token Inference and decoding Going beyond … Read more

From Neural Networks to Chatbots: The Core Concepts of AI Explained

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AI systems turn data into predictions, decisions, and language by learning patterns in numbers; the journey from neural nets to chatbots adds layers: representation (embeddings), sequence modeling (transformers), alignment (tuning with feedback), and grounding (retrieval) so outputs are useful, safe, and verifiable.​ AI, ML, and deep learning Neural networks in one page Embeddings: turning meaning … Read more