Hi Rong,

I am VP of product management @ MariaDB. I have a few follow-up questions for 
you:

1. What types of AI models have you seen work well in estimating cardinality 
and ndv and how have you seen them work in production? I think the what-if 
scenarios setup in the correct way could help AI models align to relatively 
well optimized outputs since data can be created to assist in AI training. 
2. What are the limitations of VIDEX simulations in representing real-world 
database workloads that you have seen? What have you seen work relating to 
ensuring that AI models trained on VIDEX data generalize well to production 
environments?
3. Has ByteDance explored using LLMs or other natural language processing 
techniques in conjunction with VIDEX for database optimization tasks? If so, 
what were the outcomes, and are there recommendations for incorporating such 
models into an index automation system?

Thanks
Adam
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