I'm curious about whether an AI model trained under the same conditions—using the same code, environment, and dataset—will yield identical outcomes every time. It seems unlikely because there are so many variables in play. But theoretically, if every aspect was perfectly controlled, would the model always produce the same result on each run?
3 Answers
From what I understand, if you set everything using the same seed, it can lead to the same results. However, certain algorithms, like genetic algorithms, have elements of randomness in their processes which could yield different results.
That's actually a great question! The short answer is no, they won't be exactly the same. When you train a model, it starts off in a random state and gets refined over time, so even with the same setup, the randomness can lead to different outcomes.
In theory, yes, the model should provide the same output, though it might not necessarily be the correct answer. As you continue to train it with new data, you'll keep refining your model.
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