Evolution of Large Language Model Architectures: A Critical Comparison
By
mdp2021
The bagel they save for the regulars. Don't skim, savour.
Summary
The article discusses the evolution of large language model (LLM) architectures from GPT-2 to newer models like DeepSeek-V3 and Llama 4, questioning the extent of groundbreaking changes versus minor refinements in these models.
Key quotes
· 2 pulled"Sure, positional embeddings have evolved from absolute to rotational (RoPE), Multi-Head Attention has largely given way to Grouped-Query Attention, and the more efficient SwiGLU has replaced activation functions like GELU."
"But beneath these minor refinements, have we truly seen groundbreaking changes, or are we simply polishing the same architectural?"
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