LLMs Don’t Need Search Engines: They Can Search Their Own Brains

Author(s): MKWriteshere

Originally published on Towards AI.

SSRL Framework Proves AI Models Already Contain the Knowledge They Keep Looking Up

We’ve been training AI to ask Google for answers when we should have been teaching it to remember what it already knows. The implications for AI costs and autonomy are staggering.

The article discusses the findings from researchers at Tsinghua University and Shanghai AI Laboratory, which suggest that large language models can effectively search their internal knowledge instead of relying on external search engines. This breakthrough raises questions about the potential underestimation of what these models already know and the necessity of developing better extraction techniques. It highlights the advantages of internal search systems, which can significantly reduce costs by eliminating the need for external data retrieval while emphasizing the importance of knowing when to trust internal knowledge versus seeking validation from outside sources.

Read the full blog for free on Medium.

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Published via Towards AI