While text-to-SQL demonstrations appear to be solved, their accuracy plummets when applied to real-world enterprise databases. This significant drop is not due to the language model's intelligence but rather challenges in structure, safety, and correctness. The series will explore seven specific obstacles that current systems face, arguing that a successful approach requires providing the model with a schema map, clearly delineating deterministic from generated outputs, and maintaining data locality. AI
IMPACT Highlights critical limitations of current Text-to-SQL systems on complex enterprise data, suggesting a need for architectural shifts beyond simple model improvements.
RANK_REASON The article discusses limitations and benchmarks of a specific AI capability (Text-to-SQL) rather than a new model release or product launch. [lever_c_demoted from research: ic=1 ai=1.0]
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