Unverified50% confidenceOpinionExact time
The outputs of large models are probabilistic and context-dependent, making control far more difficult than with ordinary programs.
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9/26/2026
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UnverifiedBecause the output of large models is probabilistic, the same input may produce different results across different runs.79% similarUnverifiedThe system automatically selects the appropriate model at runtime based on the nature of the task, automatically switching to a more capable or more cautious model when facing high-risk or highly complex problems.77% similarUnverifiedAutoregressive model inference must be executed strictly in serial; generating each token requires one complete forward pass, which is an important structural reason for the high cost of large model inference.76% similarUnverifiedIn large model inference, generating each token requires reading all model weights from video memory, meaning the speed bottleneck is fundamentally a data movement problem rather than a computation problem.76% similarUnverified大模型本质上是一个包含海量参数的复合函数，训练过程是通过反向传播算法调整参数使输出接近期望结果75% similar
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