with @lera_banda @danboneh @rhhackettThis episode introduces concepts behind -- and applications of -- data availability sampling (DAS), a key piece of the puzzle that could help blockchains like Ethereum achieve full scaling. A low-overhead technique that uses random sampling of data to ensure that all necessary blockchain data has been made available to nodes without straining the network, DAS features heavily in a series of planned Ethereum upgrades called "Danksharding" [named to reference Ethereum Foundation researcher Dankrad Feist]. The next Danksharding milestone for Ethereum is an upgrade called EIP-4844, known as "Protodanksharding" [also named to reference Ethereum researcher Protolambda, now at OP Labs] -- which is planned for later this year.Our expert guests include:Valeria Nikolaenko, a16z crypto research partnerDan Boneh, Stanford cryptography professor and a16z crypto senior research advisor...who discuss their recent piece on data availability sampling and Danksharding -- including a proposal they put forward to the improve current plans for upgrading Ethereum -- with Robert Hackett (a16z crypto features editor and head of special projects), based on a live conversation that took place recently on Twitter Spaces.links to pieces/ topics referenced in this episode:on data availability sampling and danksharding, an overview and proposal / Valeria Nikolaenko & Dan Bonehon Proto-Danksharding, a technical analysis / grizzly-answer-991EIP-4844: the specification of ProtoDankSharding / Ethereum FoundationProto-Danksharding FAQ / Vitalik ButerinDanksharding workshop video / Devcon (Oct 2022)2D data availability with Kate commitments discussion on commitments' expansion / Ethereum Research Foruma note on data availability and erasure coding / Github---None of this is investment, business, legal, or tax advice; please see a16z.com/disclosures for more important information – including a link to a list of our investments. Hosted by Simplecast, an AdsWizz company. See pcm.adswizz.com for information about our collection and use of personal data for advertising.

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