Unverified60% confidenceFactExact time
Deterministic systems given the same input always produce the same output, whereas deep learning-based AI systems are inherently probabilistic systems that may produce different outputs from the same input due to factors such as temperature parameters and random seeds.
2
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60%
Confidence
Long-term
Relevance
9/4/2026
First Seen
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Related Claims
UnverifiedIn computer science, a deterministic system specifically refers to a system that, given the same input, always produces the same output, which is fundamentally different from neural network models that rely on probabilistic sampling.80% similarUnverifiedCode cells yield the same result every time they are executed under a fixed random seed, whereas a pure 'prompt → result' approach introduces the non-determinism of large models.74% similarVerifiedThe randomness of AI large language model outputs stems from the temperature parameter and sampling strategy; when generating each token, the model is essentially performing probabilistic sampling.74% similarUnverifiedIn the parameter spectrum of AI programming tools, temperature controls output randomness, context window determines the amount of visible information, and effort controls depth of thinking.72% similarUnverifiedThe retry and checkpoint mechanisms of traditional distributed systems are built on the assumption that the same input produces the same output, whereas each step of an agent's reasoning may branch differently due to sampling temperature, context window changes, or differences in what external tools return.72% similar
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