Big Technology Podcast Generative AI 101: Tokens, Pre-training, Fine-tuning, Reasoning — With Dylan Patel
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Apr 23, 2025 
Dylan Patel, Founder and CEO of SemiAnalysis, specializes in semiconductor and generative AI research. He dives into how generative AI operates, breaking down the roles of tokens, pre-training, and fine-tuning. The discussion highlights the leap in reasoning capabilities thanks to human feedback, and the efficiency breakthroughs from companies like DeepSeek. Patel also addresses the growing race for colossal AI data centers and speculates on what GPT-5’s hybrid training could achieve. This conversation is a must-listen for anyone curious about the future of AI!
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Tokens as Multi-Dimensional Embeddings
- Tokens are chunks of words converted into multi-dimensional vectors representing nuanced meanings and relationships.
- Models learn these embeddings to capture complex differences, like gender contrasts between "king" and "queen."
Pre-training and Attention Mechanism
- Pre-training teaches models to predict the next token by learning from vast amounts of internet text.
- Attention mechanisms enable models to contextually relate every word, improving prediction accuracy based on surrounding text.
From Memorization to Generalization
- Pre-training builds a broad understanding before fine-tuning models on specific tasks or values.
- Models evolve from memorization to generalization to robustly understand language patterns.