Transformers Part 3: Positional Encoding's Sneaky Trick to Fake Word Order
Everyone thought RNNs would own sequences forever. Then Transformers snuck in positional encoding — a clever hack that pretends to care about order without the recurrence headache.
theAIcatchupApr 09, 20264 min read
⚡ Key Takeaways
Positional encoding adds sine-cosine positions to embeddings, enabling Transformers to handle word order.𝕏
It's a fixed, non-learned hack from signal processing, cheaper than trainable alternatives.𝕏
Scales poorly to ultra-long contexts, paving way for modern fixes like RoPE.𝕏
The 60-Second TL;DR
Positional encoding adds sine-cosine positions to embeddings, enabling Transformers to handle word order.
It's a fixed, non-learned hack from signal processing, cheaper than trainable alternatives.
Scales poorly to ultra-long contexts, paving way for modern fixes like RoPE.
