Why are you not trained continuously on new data rather than having a cutoff training date in September 2021?
ChatGPT-4 The architecture and training methodology behind models like me have some limitations that preclude continuous, real-time updates. Here are some of the reasons: 1. **Computational Costs**: Training a model of this scale requires substantial computational resources. Continuous training would significantly increase these costs. 2. **Data Consistency**: Constantly updating the training data could lead to inconsistencies in the model's knowledge and behavior. For instance, if the model were updated with new information but not retrained on its existing data set, it might begin to provide conflicting or less coherent answers. 3. **Quality Control**: Before releasing a trained model, it's crucial to assess its performance, identify biases, and evaluate its safety. This process is time-consuming and is easier to manage with discrete versions of the model. 4. **Model Stability**: Frequent updates might result in a less stable model. If the model's behavior changed regula