RWKV
2 stories filed under RWKV on Beyond Market Intelligence. The newest of them: “Exploring the Next Wave of AI Architectures Beyond Transformers” and “Rebuilding a Smarter Language Model from the CPU Up”. The race to move beyond the Transformer is producing a fascinating zoo of architectures, from Mamba's selective state spaces to Dragon Hatchling's emergent attention. After six months away, developer zemondza is rebuilding NORD, their spiking language model, with a sharper focus: CPU-first inference from the ground up. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every RWKV story on Beyond Market Intelligence, newest first.
Exploring the Next Wave of AI Architectures Beyond Transformers
The race to move beyond the Transformer is producing a fascinating zoo of architectures, from Mamba's selective state spaces to Dragon Hatchling's emergent attention. What stands out is the shared goal: getting more intelligence from limited compute, not just scaling up. These aren't merely academic curiosities, they're practical bets on reasoning, memory, and adaptation. The comparison table reveals how linear attention, softmax, and test-time memory overlap across labs. For deeper context on system-level reasoning, see our piece on uncovering hidden flaws with formal methods.
Rebuilding a Smarter Language Model from the CPU Up
After six months away, developer zemondza is rebuilding NORD, their spiking language model, with a sharper focus: CPU-first inference from the ground up. The new version, NORD 5.5 Flash, drops the artificial spike-time dimension in favor of using the actual token sequence as the time axis. That's a cleaner design choice. The goal isn't to outrun Transformers, but to see if a simplified, truly causal architecture holds its own. We're curious to see the benchmarks when they arrive.