Human users tend to use unstructured natural language (e.g., “I’m in a rush, find me a reliable one, money is no object”), while the server-side game engine (PQTS) can only parse structured economic parameters (e.g.,is_urgent=True). A massive communication gap exists between the two.
R&D Significance
Acts as the “translator” and “edge computing node” for human-machine interaction. Offloading computational pressure to the client side (User Agent) not only protects user privacy but also significantly enhances the efficiency of the server-side macro routing.
Use Cases
Running on the user’s end (local device or dedicated gateway), it utilizes lightweight NLP or LLMs to parse the user’s true intent in real-time, translating it into a structured Context tagged with risk tolerance, budget sensitivity, etc.
Achieved Results
In interactive Demo tests, the algorithm successfully captured “hidden economic commands” from user inputs with ultra-low latency, seamlessly triggering server-side bidding strategies. It realized the ultimate vision of “Natural Language as Code, Natural Language as Transaction.”