Hi everyone. Robert Hackett back here again with another episode for Web 3 with A16Z.

I recently chatted live with some of our researchers on the topic of data availability sampling and dang sharding,

which is relevant to blockchain scaling as well as paving the way for more advanced blockchain networks and user applications.

While much of the discussion is especially relevant to Ethereum,

some of the concepts we cover are also applicable to advances in computing and networking generally.

This discussion involves some specific math which we cover and briefly explain in the episode.

For quick context as you listen, polynomial commitments which you'll hear more about, are a tool that helps reduce the amount of data needed to verify complex computations.

An interpolation, another term you'll be hearing, is a way to reconstruct data from a limited set of

data points. Be sure to check out the paper referenced in this episode for a

deeper explanation at a16z crypto.com slash DAS.

That's DAS for data availability sampling.

As always, none of the following is investment business,

legal, or tax advice.

See A16Z.com slash disclosures for more important information

including a link to a list of our investments.

Okay, so today we're going to be talking about data availability sampling and dank sharding.

Now, if you're unfamiliar with those things, don't be scared because I'm here with a couple of experts who are going to break things down for you.

We've got Dan Bene, Stanford professor, eminent cryptographer, and A16Z crypto research advisor,

and Lara Nikolaenko, research partner at A16Z crypto.

Great to be here. Thanks Robert.

Thanks Robert.

Great to be here.

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