📮 Maildrop 03.09.24: Keeping LLM data fresh: a constant challenge
The things to know about AI | Tools for the next generation of enterprises in the AI era
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LLMs require a steady stream of accurate, recent internet information to excel at problem-solving
LLMs have made significant strides in recent years, demonstrating impressive capabilities in text generation, translation, and coding tasks.
However, their performance relies heavily on the quality and quantity of data they are trained on.
LLMs require a steady stream of accurate, recent internet information to excel at problem-solving. At some point, LLMs' ability to provide accurate, up-to-date information is compromised.
The challenge of keeping LLMs data fresh is a battle against the relentless tide of time and the ever-evolving digital landscape.
To accelerate the training and deployment of new models, teams must understand the critical importance of data in their pipelines and acknowledge the difficulty of finding it.
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