Chinese researchers did it again! Moonshot AI proved that 95% of attention computation is completely wasted.. They’ve open-sourced the exact attention mechanism powering Kimi's long context.. and it's 16x faster. It’s called MoBA (Mixture of Block Attention). Every time you feed an AI a massive prompt, every token desperately tries to look at every single token that came before it. The math scales quadratically ($O(N^2)$). It’s like reading a 500-page book and re-reading the entire thing from word one every single time you want to understand a new sentence. Moonshot looked at this waste and said: No. Instead of forcing full, brute-force attention across everything, MoBA applies the principles of Mixture of Experts (MoE) directly to the attention layer. How it works: • It chops the context history into discrete blocks. • A lightweight dynamic gating mechanism lets each query token instantly "vote" and route only to the specific blocks that actually matter. • It achieves up to 95% sparsity on long contexts without sacrificing performance. The results are staggering: It maintains full-attention accuracy on 1-million-token contexts while slashing massive compute overhead. We are watching the structural efficiency barrier of long-context AI get smashed in real-time. While Western labs argue about how to afford million-token context windows, Moonshot open-sourced the blueprint to make them radically cheap.