Architecture

What type of generative AI model or architecture is being considered?

Transformer, convolutional neural network (CNN), recurrent neural network (RNN), decision trees, and so on.

What is the expected scale or volume of data and computations?

Millions of users, petabytes of data, and so on.

What are the hardware requirements (for example, CPUs or GPUs) for training and inference?

High-end GPUs, CPU clusters, cloud instances, and so on.

How will the generative AI model be updated or retrained over time?

Through continuous learning, periodic retraining, manual updates, and so on.

What are the data preprocessing and feature engineering requirements?

Text cleaning, image augmentation, feature selection, and so on.

How will the generative AI system handle edge cases, outliers, or low-confidence inputs?

Through fallback to human oversight, request clarification, and so on.

What are the latency requirements for the generative AI application?

Real-time, near real time, batch processing, and so on.