Ask ChatGPT to estimate the carbs in your lunch. Now ask it again. And again. Five hundred times. You’d expect the same answer each time. It’s the same photo, the same model, the same question. But you won’t get the same answer. Not even close — and the differences are large enough to cause a
Technically, you can get the same answer twice from an LLM, but only when you control the full input. When a model is being run, a random seed/hash is applied to the input. If you run the model locally you could force the seed to always be the same so that you would always get the same answer for a given question.
Barely. Even with the code and seeds, it’s still a struggle to do that. There’s plenty of questions from people running pytorch and tensorflow models that can’t reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You’ll never get deterministic output from those.
Technically, you can get the same answer twice from an LLM, but only when you control the full input. When a model is being run, a random seed/hash is applied to the input. If you run the model locally you could force the seed to always be the same so that you would always get the same answer for a given question.
Barely. Even with the code and seeds, it’s still a struggle to do that. There’s plenty of questions from people running pytorch and tensorflow models that can’t reproduce results. Maybe you isolate enough variables that consecutive runs actually produce the same output, but the study is about commercial models. You’ll never get deterministic output from those.