Data, data, everywhere, nor any drop to drink. Or so would say Coleridge, if he were a big company CEO trying to use A.I. today — because even when you have a ton of data, there’s not always enough signal to get anything meaningful from AI.
Why? Because, “like they say, it’s ‘garbage in, garbage out’ — what matters is what you have in between,” reminds Databricks co-founder (and director of the RISElab at U.C. Berkeley) Ion Stoica. And even then it’s still not just about data operations, emphasizes SigOpt co-founder Scott Clark; your data scientists need to really understand “What’s actually right for my business and what am I actually aiming for?” And then get there as efficiently as possible.
But beyond defining their goals, how do companies get over the “cold start” problem when it comes to doing more with AI in practice, asks CFI operating partner Frank Chen (who also released a microsite on getting started with AI earlier this year)? The guests on this short “CFI tes” episode of the CFI Podcast — based on a conversation that took place at our recent annual Summit event — share practical advice about this and more.
The CFI Podcast discusses the most important ideas within technology with the people building it. Each episode aims to put listeners ahead of the curve, covering topics like AI, energy, genomics, space, and more.