>In the MoE approach, different "experts" or portions of the model are selected for different parts of the input data. The selection of which experts to use can be influenced by several factors, including the specific content of the input data, the order in which data is processed in a batch, and possibly even minor variations in the internal state of the model.
>This "expert selection" process introduces a level of stochasticity, or randomness, into the model's operation. For example, if you process the same input data twice in slightly different contexts (e.g., as part of different batches), you might end up consulting slightly different sets of experts, leading to slightly different outputs.
>In the MoE approach, different "experts" or portions of the model are selected for different parts of the input data. The selection of which experts to use can be influenced by several factors, including the specific content of the input data, the order in which data is processed in a batch, and possibly even minor variations in the internal state of the model.
>This "expert selection" process introduces a level of stochasticity, or randomness, into the model's operation. For example, if you process the same input data twice in slightly different contexts (e.g., as part of different batches), you might end up consulting slightly different sets of experts, leading to slightly different outputs.