Another pretty loud signal that just scale the ba

Another pretty loud signal that “just scale the base model” is plateauing and the real action is: 1. Architected search at inference time 2. Learned long‑term memory that is actually affordable In other words, the meta‑model around the model is starting to matter more than the model size itself. Gemini 3 Deep Think is running parallel hypotheses, specialized “contest mode” variants, tool use, etc., and just brute‑forced ARC‑AGI‑2 to 45.1%. Not magic, just a lot of structured thinking wired into the stack. Titans goes after the other missing piece. Think >2M token neural memory that behaves like MIRAS or an RNN in cost but feels like a transformer in fidelity. So you get long‑term memory without selling your GPU farm on eBay.