Tag: Accuracy Trade-Off

The deployment of autonomous AI agent swarms has undergone a fundamental architectural shift: the transition from pre-training scaling laws to test-time compute scaling laws. Historically, model capability was expanded almost exclusively by scaling parameters and pre-training dataset size. During inference, standard autoregressive foundation models operated with a fixed computational expenditure per output token, forcing the […]