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Launching AI products with Braintrust’s CEO Ankur Goyal
No Priors: Artificial Intelligence | Technology | Startups
Embrace the Shift: Data Infrastructure Needs in AI Era
Data infrastructure must evolve to support the unique demands of AI, requiring a shift from traditional data warehouses designed for ad hoc SQL exploration to more sophisticated systems that leverage embeddings and machine learning models. Advanced companies are using these technologies to efficiently sift through vast amounts of data, such as customer support tickets, to identify underrepresented examples needed for fine-tuning. The traditional approach of relational databases will face disruption, particularly in Online Analytical Processing (OLAP), as the architecture cannot simply accommodate semantic search without significant changes. The debate over vector databases versus traditional databases is less relevant than understanding the new core requirements for data querying in an AI context.
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