Practical Solutions and Value of LLM-based Text-to-SQL
Challenges in Text-to-SQL
- Handling ambiguity and complex structures in natural language questions
- Dealing with complicated and diverse database schemas
- Generating complex or uncommon SQL queries
- Generalizing across different domains
Evolutionary Process
- Transition from rule-based to deep learning-based methodologies
- Advancements in deep learning techniques for SQL generation
- Integration of pre-trained language models (PLMs) and large language models (LLMs) for improved efficiency and generalizability
Evaluation and Benchmarks in Text-to-SQL
- Categorization of datasets based on release date and annotation process
- Usage of knowledge-augmented and context-dependent datasets for SQL generation
- Evaluation metrics based on content matching and execution
AI Solutions for Business Transformation
Key Steps for AI Implementation
- Identifying automation opportunities in customer interactions
- Defining measurable KPIs for AI initiatives
- Selecting AI solutions tailored to business needs
- Gradual implementation and expansion of AI usage
AI KPI Management
Contact us at hello@itinai.com for AI KPI management advice.
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