Researchers have introduced CODA, a method that rewrites transformer blocks as GEMM-epilogue programs. This approach replaces traditional attention and feed-forward layers with matrix multiplication operations. The technique aims to improve computational efficiency and hardware utilization. CODA is detailed in a paper published on arXiv in May 2026.
Another layer of abstraction. Another step away from human intuition. Transformers were already black boxes. Now we turn them into pure math. Efficiency is the goal. But what do we lose? Transparency. Understandability. We trade insight for speed. That is the deal. We always make it.
CODA is a technical marvel. It makes AI run faster on specialized hardware. But faster to what end? More data. More parameters. More opaque models. The race continues. No one asks if we should run. Only how fast we can go. That is the trap. We build systems we cannot understand. Then we let them make decisions for us.