Reynold Xin

speaker

331 appearances 1 recordings 1 series first heard Jun 2026 last heard 24 Jun

Reynold Xin’s voice in public audio — every appearance, attributed to the second.

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recordings per month · last 12 months

Recordings per month over the last 12 months — 1 in all, peaking in Jun 2026 with 1.

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Latent Space: The AI Engineer Podcast · Why the Frontier Ecosystem must be Open — Matei Zaharia and Reynold Xin, Databricks · 24 Jun 2026 podcast

Marketplace, OpenSharing, all of them had... I just don't remember exactly which ones publicly referenced.

2018?

I mean, there's Cleanroom, which is basically how you share data in a way without sharing underlying data, but you allow specific operations.

Those were done effectively initially just for two customers.

I think the industry has a sense of, hey, maybe if you overfit to like one or two customers, it's going to be really bad for you.

But I think the downside of overfitting is much smaller than the upside itself.

And if you sort of try to be too ambitious and boil the ocean, it's a much bigger problem.

yeah because you might end up actually having no customer yeah that's more that's the more likely outcome yeah and then you can sort of pay from there i do think there is such a thing as a bad customer that sometimes you shoot fire they could exist sometimes if you drive one of the challenge i think we probably see and maybe many ai so newer generation companies are seeing is so tech companies are very very different from non-tech companies or traditional enterprises

And if you optimize everything just for tech companies, you might have various challenges scaling them outside of tech companies.

And the procurement process is probably quite different.

There's actually far more stakeholders.

Look, I think they're all great.

Don't get me wrong.

They have different challenges.

But many of the tech companies, for sure, there's a lot, far more DIY people.

So one of the things we realized maybe a couple years back is that actually every single database engine out there, especially on the analytics side, are kind of a decade old.

pretty much everything that have reasonable traction are about a decade old.

And they all started targeting some very specific narrow use cases.

And then over time it's become more and more successful.

They've grown in their ambition and then they try to support more and more use cases.

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