GenAI suffers from data overload, so companies should focus on smaller, specific goals
"There is no AI without data, there is no AI without unstructured data, and there is no AI without unstructured data at scale," said Chet Kapoor, chairman
“There is no AI without data, there is no AI without unstructured data, and there is no AI without unstructured data at scale,” said Chet Kapoor, chairman and CEO of data management company DataStax.
Kapoor was kicking off a conversation at TechCrunch Disrupt 2024 about “new data pipelines” in the context of modern AI applications, where he was joined by Vanessa Larco, partner at VC firm NEA; and George Fraser, CEO of data integration platform Fivetran. While the chat covered multiple bases, such as the importance of data quality and the role of real-time data in generative AI, one of the big takeaways was the importance of prioritizing product-market fit over scale in what really is still the early days of AI. The advice for companies looking to jump into the dizzying world of generative AI is straightforward — don’t be overly ambitious at first, and focus on practical, incremental progress. The reason? We’re really still figuring it all out.
“The most important thing for generative AI is that it all comes down to the people,” Kapoor said. “The SWAT teams that actually go off and build the first few projects — they are not reading a manual; they are writing the manual for how to do generative AI apps.”
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