[AINews] Death of Params: Z.ai CEO Jie Tang on GLM 5.3 and the new Post-training Scaling Law

Latent Space · 1 month ago · 18 ● 3 sources

Prof Jie Tang argued that parameter count alone is not enough to predict model capability and said GLM 5.3’s gains come mainly from RL on long-horizon, production-like environments rather than bigger models. He highlighted that advanced skills can require carrying causal chains of 20+ inference steps without losing the thread. The takeaway is that scaling focus shifts toward post-training data quality, effective compute, and environment design (including RL reward/verification), not just parameter size.