GenAI poster child is a 100-story-tall baby with simple infrastructure but extreme demands
When OpenAI launched GPT-4 in March last year, it was coy about the model's size and what went into making it. Nonetheless, the current focus of AI-obsessed media and investors is understood to have employed a diverse dataset of around 1 petabyte. Aside from the challenge of getting that data to provide meaningful output, the company was tasked with getting the data in the right place.
"The company that's had large data volumes for a long time, like Procter & Gamble – you come in, there are challenges, but you tend to work them out in the proof-of-concept phase," he said. "The hard part is that you hit corner cases of the APIs that no one ever really thought about. You find you cannot pull an endpoint as frequently as you want. Or you have weird, like, n-squared behavior when you try to update data.
Despite its popularity, Fivetran has attracted criticism for its slow support for data lakes, especially those using AWS S3 storage, which theIt's not like the sort of big iron number-crunching, supercomputer-type stuff that people want it to be
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