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AutoSynthData: Generating Training Data for Enterprise Agents
TL;DR
AutoSynthData is a tool developed by ServiceNow CoreAI that generates training data for enterprise agents by identifying and addressing their weaknesses. It creates tailored tasks based on a model's failures and a teacher model's successes, enhancing the agent's performance in specific environments.
✦ Why It Matters
Implement AutoSynthData to enhance your enterprise agents' performance by generating targeted training tasks.
Key Takeaways
- Utilize AutoSynthData to generate tailored training tasks.
- Focus on specific capability gaps identified in your models.
- Ensure tasks are feasible, realistic, and challenging for effective training.
- Regularly evaluate model performance to guide future training data generation.
How It Works
AutoSynthData generates training tasks by analyzing the failures of a target model and the successes of a stronger teacher model. It creates tasks that are grounded in the agent's operating environment, ensuring they are feasible and realistic.
The process involves generating core samples based on capability specifications and then expanding these into novel variants, all while maintaining rigorous quality checks to ensure the tasks are executable and provide useful training signals.