Building an AI Search Engine with ZeroLM
![Image](https://blogger.googleusercontent.com/img/b/R29vZ2xl/AVvXsEjB3zeHkibRgvKDoyr9V7u4ih0LMtHlPOAMgb1GDnJ1aLQx3QtCzmJW8yRDZ3fVJJDJ1HkAuTv0lEJA1FqAE9NVDG9yNpPz2ptWaiL-QYpXOcqO4WGbH7mICdZsoeAS5OTLcdB-SejKFz6tWjjWFfUva8moj0WWtZ7TEi0XKpOdDoQw-09lPagxMVIFOw/w400-h400/zerolm_network_computer_search_engine_search_input_box_ro_27157b73-e7f8-479d-91f0-95e4c7b1d3e0.png)
In the quest to provide better, more context-aware search experiences, Large Language Models (LLMs) like GPT and Bard have paved the way for a new generation of search interfaces. Enter ZeroLM, an interface to these powerful language models, revolutionizing how we extract and interpret data. In this tutorial, we will harness ZeroLM to build a simple, user-friendly web search interface. Unlike traditional search engines that offer a plethora of links, our version will use ZeroLM to generate precise, human-like responses to user queries.