Gated Linear Units explained: the multiplicative valve behind LLaMA and PaLM's SwiGLU FFN
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A standard Transformer feed-forward block is dead simple: Linear -> one fixed nonlinearity -> Linear , where that middle activation (ReLU, GELU) applies the same elementwise curve to every hidden unit. A Gated Linear Unit throws that single activation out and replaces it with a multiplicative valve. Understanding it is the difference between reading a modern LLM's FFN and being baffled by it. Project the input twice, then multiply Instead of one weight matrix, a GLU uses two. W makes a value…
1Key Takeaways
- A standard Transformer feed-forward block is dead simple: Linear -> one fixed nonlinearity -> Linear , where that middle activation (ReLU, GELU) applies the same elementwise curve to every hidden unit.
- A Gated Linear Unit throws that single activation out and replaces it with a multiplicative valve.
- Understanding it is the difference between reading a modern LLM's FFN and being baffled by it.
- Project the input twice, then multiply Instead of one weight matrix, a GLU uses two.
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3Why it matters
Coding AI shifts how fast software ships and how much human review each change needs. DEV — ML reports that a standard Transformer feed-forward block is dead simple: Linear -> one fixed nonlinearity -> Linear , where that middle activation (ReLU, GELU) applies the same elementwise curve to every hidden unit.
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