Memory efficiency is one of the biggest bottlenecks for scaling LLMs, so a 114× reduction is genuinely significant. This piece from Towards Data Science breaks down the techniques enabling "infinite context" without proportional memory costs Worth a read if you're curious about the architecture innovations making longer context windows practical.
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