To find the latest market cap of the top 10 AI stocks, we need to:
1. Generate a subquery to get the latest market cap data for each AI stock.
2. Join the `stockindustries` table with the `price_data` table to access both industry classification and financial data.
3. Filter for companies classified as AI by checking the `artificialIntelligence` field in the `stockindustries` table.
4. Use a subquery to select the latest market cap data for each company, ensuring we're working with the most recent data available.
5. Order the results by market cap in descending order to find the top 10 companies.
6. Limit the results to 10 to get the top companies.
7. Avoid common errors such as division by zero by not performing any division operations.
8. Minimize unnecessary subqueries by directly joining the necessary tables and filtering based on the AI classification.
9. Group the results by company symbol to avoid duplicates.
10. Use the `MAX` function within the subquery to ensure we're selecting the maximum (most recent) date available for the market cap data.
Now I will generate the query:
{
  "sql": "SELECT si.symbol, si.name, pd.date, pd.marketCap FROM `my_project.my_dataset.stockindustries` si JOIN `my_project.my_dataset.price_data` pd ON si.symbol = pd.symbol WHERE si.artificialIntelligence = TRUE AND pd.date = (SELECT MAX(date) FROM `my_project.my_dataset.price_data` WHERE symbol = si.symbol) ORDER BY pd.marketCap DESC LIMIT 10"
}