Unlike the vast, publicly available corpora used for pretraining, there is no centralized, high-quality data commons for posttraining. This lack of shared, curated datasets for instruction tuning and alignment presents a growing challenge for the industry.
HOW THIS AFFECTS YOU
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researcherThe absence of a data commons may lead to fragmented benchmarks and evaluation difficulties.
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founderProprietary posttraining datasets may become a primary competitive moat as public pretraining data saturates.