IBM Big Data Hub
JANUARY 9, 2024
Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.
O'Reilly on Data
OCTOBER 19, 2021
Feature stores aim to solve the challenge that many data scientists in an organization require similar data transformations and features for their work and labeling solutions deal with the very real challenges associated with hand labeling datasets. Model Development.
Alation
JUNE 28, 2022
Scale effectively: Leverage taxonomies to ensure consistent modeling outcomes when introducing new data sets or changing business demands. Track data lineage: Document data origins, record data transformation and movement, and visualize flow throughout the entire data lifecycle.
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