I’ve encountered similar performance issues with Google’s AI Studio. After investigating, I found that the slowdown is often related to the complexity of the AI models being run and the server load. To mitigate this, I’ve had success by breaking down larger tasks into smaller, more manageable chunks and running them sequentially.
Additionally, scheduling resource-intensive tasks during off-peak hours has significantly improved responsiveness. If you’re still facing difficulties, consider exploring alternative platforms like Azure ML Studio or AWS SageMaker, which offer comparable features and often provide more consistent performance for AI development work.