🚀 Exploring Adversarial AI in Travel Planning
In an era where AI often misses the mark, our latest experiment seeks to revolutionize travel planning. Current AI models struggle, achieving just a 10% success rate in complex travel scenarios. This shortcoming arises from their reliance on data without real-world validation.
Key Features:
- Two Opposing Philosophies: Our model pits agents against each other—one favoring deep exploration and the other prioritizing efficiency.
- Verification with Google Places API: Each suggestion is cross-checked for real-time data such as opening hours, walking distances, and ratings.
- Community Feedback Requested: We’re at an early stage and eager for insights from fellow enthusiasts.
Is grounding LLM outputs against structured APIs the way forward?
💬 Join the conversation and share your thoughts! Comment below if you’ve explored similar approaches or want to dive deeper into AI advancements in travel. Your engagement could spark the next breakthrough!
