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LLM

AI-Powered Search: The Future of Information Retrieval

As Google's search quality has declined in recent years, competitors like Bing have managed to catch up, offering comparable search results. However, being on par with Google is not enough to create a true "Google-killer" that would attract a significant portion of users. The rise of large language models (LLMs) like ChatGPT and Claude has led to a decrease in search traffic for Google, as users can now get answers to certain questions directly from these AI assistants. Nevertheless, LLMs have limitations, such as making mistakes and lacking trustworthiness, preventing them from completely replacing traditional search engines.

The Concept

A potential Google-killer would combine the best aspects of LLMs and search engines. Instead of simply providing an answer, it would deliver structured responses with each argument backed by its source(s). This approach differs from current LLMs, which do not have access to the sources that led to their answers. It also diverges from retrieval-augmented generation (RAG) systems that search the web and use LLMs to summarize the answer. The proposed concept would first generate an answer using AI and then cite the relevant sources.

Implementation

To create this Google-killer, a new architecture would need to be developed that can provide an LLM-like experience while being source-based. This would require a search engine without a traditional index or snippets, relying instead on AI to generate answers and cite sources. The AI would need to be trained on a vast amount of data to provide accurate and trustworthy responses, while also having the ability to identify and retrieve the sources that support its arguments.

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