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Understanding LLMs as neural networks trained on text at massive scale
A Large Language Model (LLM) is a neural network trained on massive text data to understand and generate human-like text. The "large" refers to model size (billions of parameters) and training data (trillions of tokens).
Models read tokens, not words:
Good at: Text generation, Q&A, code, analysis, summarization, creative writing
Bad at: Accurate math, up-to-date info, long-term memory, fact verification (hallucination)
text = "Large Language Models are changing the world."
words = len(text.split())
estimated_tokens = int(words * 1.3)
print(f"Words: {words}, Estimated tokens: {estimated_tokens}")