Understanding GPT Mechanics
The encoder-decoder architecture of large language models, like GPT, relies on multi-head attention and feedforward networks to generate text outputs from prompts. By predicting the best next token based on learned patterns from extensive training data, these models perform thousands of attention operations to create coherent responses. The sheer scale of data and complexity behind these models highlights the fascinating yet intricate nature of AI text generation.In this clip
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AI Today Podcast: Generative AI Series: Generative AI & Large Language Models (LLMs) – How Do They Work?
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