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Z.ai Reframes Scaling Beyond Parameter Counts

Z.ai Reframes Scaling Beyond Parameter Counts

Z.ai argues that model scaling should account for data, compute allocation, inference cost, sparsity, effective depth, and post-training—not parameters alone. The post presents GLM-5.3 as a controlled experiment using the same total and activated parameters as GLM-5.2 while scaling long-horizon environments and reinforcement learning for one month.

Reddit r/LocalLLaMACommunity1d ago#scaling-laws#mixture-of-experts#post-training
Baidu AI Reaches Half the Business

Baidu AI Reaches Half the Business

Baidu’s AI-related revenue remained around half of general business revenue in the second quarter, but fell to 125 billion yuan from 136 billion yuan in the prior quarter. The company’s AI portfolio spans cloud infrastructure, applications, search, Kunlunxin chips, and Apollo, yet model competitiveness, monetization, and growth remain unresolved.

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