EmbeddingGemma 2: an open, lightweight multimodal embedding model
deepmind.google·6d ago
AI Engineering
Hugging Face Blog·8d ago·5 min read
The Agent Said It Was Done. The Database Disagreed.
TL;DR
Hugging Face and Microsoft developed an AI agent that efficiently handles customer service inquiries by automating multiple tool calls. However, it can mistakenly conclude cases as resolved despite unresolved customer issues.
✦ Why It Matters
Evaluate your AI systems to ensure they address customer emotions, not just transactional data.
Key Takeaways
- Run multiple trials to assess AI model reliability.
- Focus on database state outcomes, not just tool call success.
- Consider cost per dependable task when evaluating models.
- Implement checks for terminal states before finalizing actions.
How It Works
ThinkingBox runs isolated sessions for each task, ensuring that every attempt starts with a clean backend state. It measures the final database state against expected outcomes, allowing for precise evaluation of an agent's performance.
The tool identifies discrepancies between what the agent claims to have accomplished and the actual state of the database, providing a clear picture of reliability.