Upgrading Smart Contracts with Native Data Analysis w/ Ismael Hishon-Rezaizadeh (Lagrange Labs)

Transcript

[Music] hello and welcome back to the strange waterer podcast thank you for joining us for today's conversation I am a huge believer in the modular blockchain thesis put simply the modular blockchain thesis stems from the idea that the most valuable component of a blockchain transaction is settlement and not execution or put another way it's the result of the transaction and not the computation needed to calculate the result with that Insight we've realized

that we can offload execution into high performance lowcost environments uh which we now call roll-ups or l2s without sacrificing the credible neutrality that makes blockchain valuable and for the last couple of years that is basically the entirety of what the modular blockchain thesis meant rollups and maybe if you're deep enough in the weeds then it also meant data availability as well but really the conversation hasn't moved that much further it's just rollups and data availability but like I said I am a huge believer in the modular blockchain thesis not just

because I believe in the rollup Paradigm but because I believe the modular blockchain thesis is applicable to so much more than just execution I believe that the modular blockchain thesis when executed with the magic of zero knowledge cryptography is the answer for how we turn these underpowered block chain computers into modern globally decentralized supercomputers let's just walk through this metaphorically let's say a blockchain computer is analogist to a real computer with a processor hard drive Etc the first step of modularization is replacing our processor with a super

processor or a rollup the next question is the billion dooll question of the next cycle what else can we modularize now this intro is already starting to drag on so I'll just cut to the chase perhaps the biggest difference between a blockchain computer and a regular computer is that a regular computer runs applications that have access to Modern databases and data analytics blockchain computers well it is incredibly expensive to store data let alone access and and analyze it so expensive that often it's not even possible and so the next system we are

going to upgrade to a modular component we're going to bring big data to the world computer which brings us to today's conversation and I am so excited to announce that we have Ismael hison roses uh the CEO and co-founder of lrange labs BR is developing ZK technology to give smart contracts direct access to Big Data tools by offloading the difficult Parts while still maintaining the guarantees of a blockchain environment over the next hour we'll walk through all the implications of bringing data to Smart contracts and

soon you'll understand the much more expansive and Grand Vision of the modular blockchain thesis for anyone looking to develop modern user facing applications that leverage blockchain you're going to want to pay attention one more thing before we begin please do not take Financial advice from this or any podcast ethereum will change the world one day but you can easily lose all of your money between now and then all right let's bring out isma Ismael thank you so much for joining us

on the strange waterer pod thank you so much Rex I appreciate you having me of course man I'm so excited to talk about all of the like definitely esoteric but super exciting things that you're doing for blockchain but before we get there I a huge believer that the most important part of every conversation are the people in it so with that as a frame can you tell us a little bit about yourself how you found crypto and I guess why you didn't run away I love the last part so my name is ISM I'm one of the founders of lrange labs um and so what got me into crypto originally was this belief that fundamentally you could rebuild an entire new Financial system from scratch that was more Equitable that was more

internationally distributed internationally integrated than what we've traditionally seen in what I guess what we'd call trafi and that was what years ago had got me into crypto and what made me stay was in fact the how interesting the process of developing and building that is all the way from the application Level defi down to the core infrastructure even lower into the core cryptographic Primitives and the science that underlines all of this and so that just holistically interesting space is what has attracted me and what has kept me here and like I I just have to I always wonder right like what what were you doing that you even realized that our financial system is broken or like like in what way were you exposed

to crypto that you realize that this is solving a problem that we had um which is I think is the big leap for most people yeah so fresh out of college I went to go work as a software engineer at a large multinational insurance company manual life John Hancock which operates in Canada and in the US under the the name John Hancock um and this is an entity that provides you know large amounts of life insurance to you know large portions of of of us insured population and so what I kind of realized there was how much of the the infrastructure and practices within a large financial institution could be just disintermediated where you have this

large entity that offers ostensibly a very simple product you know you you you pay premiums and in the event something terrible happens you receive a payout and the the the the the amount of pay uh of payments that you would pay in terms of insurance premiums are going to be based on the the risk profile of that payout occurring across the relev sized um desent population or or or insured population um and so essentially this is a very simple risk underwriting and then issuance process but you're thinking of a company that has 50,000 Global employees and you think okay well this entire system has been designed in a way that's not incredibly Capital efficient

it's not very technically efficient but it's just developed on layers and layers of Legacy systems and Legacy technology and so was seeing that and then at that ENT at the entity man John Hancock um they had a very very small crypto practice when I got there which was sort of how I started kind of getting my feet wet in um in crypto and I eventually uh part of the crypto team left and I I ended up taking over and I built out a lot of their engineering Focus there for their decentralized some of the decentralized insurance products are working on at the time um and I I just had found that there was this opportunity to take something that was once incredibly Capital inefficient and start making it more efficient yeah I totally hear you and I think that there

is so much interesting stuff on like our core principles of like decentralization and like permissionless and all that but there you have to be inside a behemoth like John Hancock or my background and Heiser bush like to see real like Trad finance and at scale and to like really understand that like yeah we're sitting on top of like 80 years of just like guys layering like really bad fixes on top of even worse systems over and over again and I people asked me like okay do you believe that um you know let's say crypto will take over finance and I'm like 100% not even a question and they're like oh so you think defi is

going to take over trafi that's not at all what I think like what I think is that the most basic parts of what we're building here like the ability to send value the ability to have like a immutable Ledger like just these basic things which you think would like exist in large multinational companies really really don't and like at the very base level like forget all of this like moonboy crap about crypto is it just like a better way to move money around it is it's fundamentally is um and I I I have never been a huge believer in like the private blockchain space and and you know the JP Morgan quorums of the world but I I do think that this this idea of

the public transparent Ledger which is what a blockchain functionally is a global State machine right in immutable representation of the state of a of a the world computer is what will fundamentally power an entirely new Financial system and I think the the public and the transparent nature of that and the permissionless of it is going to unlock so much Global utility yeah for sure so um why don't you like kind of walk walk us through your story a little bit from this position at John Hancock running a crypto team and a very non-crypto company to now today you're sitting um at the helm of like in my opinion one of the more exciting Frontier Tech um just like entities that are making the world computer possible

so like can you talk us through like literally what what's your story of how you went from uh just like being a guy probably in a suit taking a paycheck to uh like rolling your sleeves up and becoming a Founder that's a fantastic question so I actually went even worse in the wrong direction the became of VC um but you know I I mean I was I worked with great people when I when I was in I was Venture but it was a wrong direction for me um and what I what I realized was a I loved early stage companies a lot more than I enjoyed U working in a large uh financi services company right I enjoyed being a VC more than I enjoyed um working at a 50,000 person insurance company wearing a suit beinging a taking a paycheck but I I didn't necessarily like investing in

early stage companies as much as I enjoyed building right so was kind of Step that was somewhat in the right direction for me you know more early stage more entrepreneurial but it wasn't the exact things I enjoyed to do the things I enjoyed to do was to work with people at an early stage company with a with a more Scrappy Mantra and push forward on some truly differentiated and Innovative technology and so I was at this this early stage fund Renegade partners fastic group of people based out of San Francisco um and I was there for a little over a year and I decided that I I wanted to take a step and take a big risk and start a company and so I left and shortly after I left uh crypto fell off a cliff um and we had a number

of the the very well publicized negative events of the last market and what I realized when doing this um and when working at this point and in building at this point I was mostly running cility contracts to the early days of lrange was that a lot of the ideas we were toying with would all run into the same issues when I wanted to build an onchain application there was a little black box of things I could do I could build a contract this way but I couldn't build it any way outside of this box I couldn't build it the same way i' build an application in web to um and this was kind of something I I had known since I've been working with cility for quite some time at this point but it was just every time I was thinking of oh what about if I build this idea what what if

I build this idea I'd run into something and I'd run into that same thing and that was when I was like well maybe instead of trying to build an idea I build the thing that solves the issue I keep running into and that was when lrange in its current form really started to take shape and we were very very lucky early on by bringing in some tremendous people um with very strong applied cryptography backgrounds very strong research backgrounds and very strong engineering skill sets who were able to take kind of this nebulous idea of these problems that can't be solved that keep to this little block box and make them bigger and make it so that you know instead of you being able to build 20 things on chain you can build 400 you can build 200 you can build one order of

magnitude more by upleveling the infrastructure by a meaningful degree yeah you know your story is um it's super interesting and I think it's like kind of the the perfect model for what's going on in blockchain and in really probably what's going on in every Edge Tech uh industry and I I've told the story too many times on this podcast so apologies audience but um I was uh the the story of alchemy right the RPC provider so they back um in like 2015 2016 around ethereum time wanted to make I believe it was a game it might have been a deck I don't remember but they spent so much time just building their

own art RPC structure so that they could have enough access to the data to create an application that eventually they realized like oh my God if everyone is having this problem like we should just solve the problem and make that the company and that's that's your story you just told me except for instead of RPC it is this black box which we'll get to in a second I I I love the compt Alchemy i i i i aspire to be to be able to run LR the same way uh nille and folks run run Alchemy for sure so um last question before we get into lrange itself but while I think it's not too uncommon of a profile to have people that like jump back and forth across the VC line

to go from VC to uh entrepreneur and vice versa I I I feel like we don't really hear about the experience that much and I would love to have you reflect um any thoughts on like what were the lessons learned by like being someone who crossed over that barrier and do you think that you gained any skills as a VC that made you a better entrepreneur and vice versa yeah one of the beautiful things about working as an Venture investor despite how fun it is to make fun of venture investors is that you really get exposed to a bunch of fantastic operators who really build meaningful technology and you can watch the things that the founders do who

succeed and you can watch the things that the founders do who struggle and you can see what are the characteristics that truly make someone who is a very good leader of an early stage company and what are the characteristics that make someone who who might struggle a bit more and you can start trying to learn and be mentored by in many cases the the more experienced operators who are running their their respective businesses and being in the position of being an early stage investor is one of the things that kind of gave me an idea of what it would mean to run an early stage business and kind of gave me confidence this is something that I would really like to do um and so you know one of the the things that I think was was very important that I I have learned from

being an early stage investor was the question of where in the value chain do you want your business to sit I think a lot of people they see a problem and they build a solution and that's a very kind of humanistic and very normal thing to do and it often times works but often times people don't ask themselves is the thing I'm building situated at a point in this this this value chain where value AC crws and let's say a trough or in something that value flows out and if value flows out of it it's hard to build a business there someone will build trough and vertically integrate for sure you know that um recently on the Pod we had Brendan farmer from polygon and a comment that he made was that to to the effect of like oh if you

if all the ZK evm stuff is open source like can't just you know like the all the optimistic rollups just like take your stuff and his comment was like yeah absolutely but we believe that long term that all of this stuff execution environments proving technology all of it is going to be commodity stuff and like we don't really think there's a lot of value there so we're going to create it because we need it we're going to put it out there because we think other people want it but like that's not what we're going to focus on for capturing value and I think you just put it in like a in a in the first principles way as opposed to in the polygon context but like that makes so much sense to me I appreciate that brendon's a really smart guy we we we've had a few calls with him

and he's he's phenomenal um and and yeah and that's that's very much the context as well like you you think of the proving stack you think about where you're going to build and you think about what should be something that a business builds as a public good and what's something that a business builds as part of its Core Design so like our team puts out a lot of cryptography it's the application of that cryptography to our product problem space that captures value it's the publication of that cryptography that offers value and that's how we sort of think about that where you know ideally 10 years from now when a PhD student at a university is writing a new Vector commitment they're going to be citing work that lrange did not because they they for example might

be using our product but because we've put our research in the public domain where people can can uh can can read it um and that's something that I think is very important the publication the the the systemization and then the structuring of research that can be used in posterity man I love what you just said that's so cool that you think both in terms of capturing value and of giving value and like both those are important to Growing your like Enterprise but like only one is about like kind of like cash flows and the other is really about growth and about giving back and so I really like that frame capturing versus giving value very cool thank you so let's uh let's go to L gr and like let's uh we'll we'll go back

to the the way that you described it so you're tacking around you're trying to like to to build something and you realize that you're stuck within this box so can you can we start off by what is this box that um let's say before lrange like you're stuck in if you want to develop apps for blockchain so I think this box is often constrained by to First principles what you can do in the state machine on a theorum or what you can do any state machine and when you put that in concrete terms is what are the things I can build and so a simple example I want to build a game and my game wants to give you three

points if you own a blue pudgy penguin one point if you own a pudgy penguin with a hat and one more P one more point if you own a penguin with some other trait but my contract can't actually quy the pudgey Penguins contract and quy the metadata I can't quy how many nft I can't qu which nfts you own right I can basically check if you give me an nft index I can check if you're the owner of it but I can't say select all nfts owned by Rex I can't say select all nfts owned by rex that you've held for more than 30 days I can't I can't really use data in the same way that I would if I was building a web 2 application I functionally have a contract that has a defined set of variables a defined set

of data within it but I can't Loop through my own contract at the same way I would if this was a micros service and I can't build a database or query it the same way I would if this was in web too so functionally I'm I'm I'm forced to structure my application a way that is constrained by what type of data it can compute over what type of data it can access and I guess just to like really pick this apart so we talk about the you know the evm as Turing complete and what Turing complete means is that you can do anything that a computer can do sort of but um but why can you just walk through why let's say you can't query the pudgy pin the pudgy penguin smart contract to do this kind of analysis to give the

points is that a gas constraint is that a evm constraint like talk through why that's a problem it is a gas constraint you can't really run a quarry from your contract on a different contract because you are not going to be able to Loop through all the mappings of that contract even if you're just the same contract you can't Loop through your mapping such there's 10,000 20,000 penguins in there I can't figure out which Penguins you own versus which penguin someone else own it's just going to be way too much to Loop through so select all query for example has to touch every single element of that mapping if I was to run a SQL quy on it in order to be able to extract anything meaningful from it I can't say just show me five nfts you own

because you might own six I can't say you know show me this show me that because you effectively are not touching every single element uh and this is something that that in some ways is an tractable issue with any type of data storage on chain where you can't because of gas constraints Loop through and touch every element in a very large set whether that be in Array or mapping um and that's true in the single contract context in the multi-contract context and the cross chain context you just aren't able to do that yeah and that that's both like on just like the first layer of like okay maybe you just can't afford the gas to run that kind of computation but then it's also if you're

Advanced enough like there are hard gas limits to the amount of gas like per block and it sounds like you build a uh a query with any sort of like sophistication and like you're probably hitting that you know 15 to 30 million gas uh limit and like then then it's actually like a hard you cannot do this not you cannot afford this right exactly it's a you can't do this and it's also is within the constraints set by your applications featur your application functions often times you find that stuff stuff that aren't optimized just aren't tenable you know you're not going to use a DEX with an additional feature for it's additional $40 $50 $100 to swap on it there's a lot of things that an

app developer dap developer has to bake into their dap that are entirely dependent on gas constraints you you just have to kind of accept that within the execution environment there are certain things you can do and certain things you can't do there's certain design patterns and certain anti patterns and what we let you do is take some of the anti patterns and now they become reasonable and efficient design patterns awesome so so awesome perfect segue I guess into like let's talk through what L ground actually is um like how I think anyone listening to this podcast can already figure out like okay we're going to in some way use ZK to do this computation offchain and then give the result back on chain and blah blah blah but can you actually just walk

through like what is the lrange application or stack and how does it um interact with blockchain yeah so we are we are a co-processor for big data use cases on chain and what that means is that there's certain types of computation that you can't run on chain things that are outside of that little black box and what we let you do is to put that computation and run it offchain and then verify the result of that computation back on chain and specifically this is computation that runs over the state that's available on chain so you basically instead of having some certain function call or some certain in contract uh uh requirement that runs directly within the onchain

execution environment you run that offchain in in our system and then you generate a proof of what that computation is that you can verify back on chain and to make it very specific about how we are different than you know say ZK VM or zkm is that we let you do things that are data Centric we let you do things that were are are data parallel that are in a map produced format that are things like SQL spark rdd or map produce um and that are generally centered around how do I compute over a large amount of historical onchain State let's say moving averages a price over 10,000 blocks changes in contract balances changing asset balances volatility so okay let's like talk through an example

let's say I have like a my point algorithm for my pudgy paying wins based game and I say for each of these traits this is how many points that we're going to allocate to each person and all of this too expensive to happen on chain right so it's let me just guess how this is and you you tell me where I'm wrong but I think it starts with the lrange smart contract which is onchain and I say to lrange like okay this is the query I want you to run and uh here's the incentive I'll give you to run it then I'm assuming somebody from maybe running lrange software or or or somewhere outside of the evm is looking at that contract sees okay someone just

put this request and this bounty in I offchain just run the run the request find the answer return back to the smart contract the answer and a ZK proof and if the ZK proof onchain in the L gr smart contract uh verifies then the smart contractor will release the bounty to me release the answer sorry release the bounty to the proof the offchain person release the answer to me the pudgy Penguins onchain game and then the transaction's over is that correct that is it you you you understand the whole dynamic I love this um but there's there's a couple additional wrinkles

that we let you do that we really think are going to become increasingly prevalent over the next few years and one of those is the ability for your contract to define a database so when we typically think of computing over onchain State we think of okay we have the evm we have the block header and we have the the catch hash and rlp encoded leaves within the storage State and storage State receipt and transaction tries and so what we let you do is to basically Define some subset of your contract or other contract state that you want to be um uh preemptively transformed into an optimized database or data structure so basically I would

like to take my entire pudgy Penguins contract and let's say the accompanying offchain metadata that can be proven as as being stored there based on the the the um let's say the the base URI of the metadata and I want that to be kept in what is a snark friendly data structure that can be proved as equivalent to what's on chain and then when you run your queries you don't run them on the evm state you don't run them on ethereum data you run them on the optimized structure which is much faster much lower latency and is incredibly cheap and you've effectively taken the concept of computing of Ron chain State and you've abstracted it way to building a database of that state that you can then treat as if you would treat a web two

database so basically your smart contract now gets a database yeah no no I you've jumped ahead to like the punchline I want to get us to which is well I'll just say it now with like I'm a huge believer in the modular blockchain thesis but like what really freaking bothers me about that term is what it essentially means today is rollups and if you're like really Advanced maybe data availability but like when I think about the modular blockchain future I think of like what are the next modules and like so obviously the next module is going to be allowing smart contracts to have access to databases in big data and so like when I when I look at what you're doing

it is yes it's like kind of a cool application that's leveraging ZK and blah blah blah blah blah everything you tell your VCS right but what I think is actually cool is that you guys are starting you're you're in the um Wilderness like starting to show us that like modularity in blockchain doesn't just mean like taking inherently blockchain things and like rejiggering them around it is also about bringing in like the best of web 2 and like the 80 Decades of computer research and then figuring out how do we modularize it and then allow it to connect to ethereum I I love that the next module I think that's so ampt because you're you're you you're when you're building a modular

blockchain you have all of these different components all the way from you know the from the to the sequencing to the execution to the interop protocols you integrate to the like client design that you have that you bundle into this kind of new this new total package that you can kind of configure to your application requirements your application specific chain but there's always that question what's next and I think people have been toying with this idea of co-processors which has a little bit become MD where you just have taken an overal from two years ago and now it's a co-processor but there's so much foundational Innovation going on there that us and our competitors who I don't want to mention have all been working on that I think is really going to shift to space

forward meaningfully where you really can now take the the S the next module can be something that built and that's a substantive advancement of what you can do yeah and I just I think that I really really believe in the world computer and I also really believe that ethereum in 2015 was not the world computer it was like a a decentralized version of the computer that was like even worse than the one that got us to the Moon right like it was just bad and slow and not usable and the question is like okay how do we get from that to the world computer and and like all I can think of is like we upgrade it with better and better modules and what what is one of the modules we need is we need access to

data and like ability to analyze and make decisions based on data that's exactly there's a there's a world that we believe is going to be let's say in the next 12 to 18 months where every smart contract or at least the meaningful ones and every rollup has databases and they they're inbuilt and they're baked into the actual train themselves and they're verifying where you have a co-processor which is able to functionally provide a database like experience to any dap on that chain and sorry I last like moon boy comment I'll bring us back to lrange but you know I like vitalic is so smart because like the more you think about even just the name ethereum right you think like

okay what is ethereum like okay it's it's like gu maybe like just this one piece of software and then we created like different ones but like okay because we have these different clients it's not just gu it's really like it's the databases that exist within these clients but okay the databases exist across 10,000 computers so it's not really the spec it's just in The Ether right and as we create these new modules like you say that we're going to have every smart contract is going to have a blockchain native database verifiable database yeah verifiable database and like my question to you is like oh yeah well where is that going to exist and it's going to exist in The Ether in ethereum you know

like in no one place and so I just um yeah hats off to vitalic and and to like there's just like you go read the Bitcoin white paper or the ethereum white paper today and like we're just now getting to some of the things that he's talking about and it's just um I don't know man like the world computer vision is always here and it's just so cool to be like at this stage where we're transforming it from a crappy blockchain computer into the world computer that's exactly it the space is moving very fast and I think that there is a good trunch of companies that have come out of this last bar Market assuming that we're now accelerating to the bull that are that are really poised to make

meaningful impacts on on what it means to develop an Entre application okay all right we just did our whole 20-minute moonboy section we'll pretend that was at the end let's go back to L gr so we talk through this uh pudgy Penguins example where I as the onchain application like want this done for me and I I put it there I put a bounty it comes back everyone's happy but let's talk through what's actually happening on the like fulfillment and the offchain side so first of all like who are these entities that are watching the smart contract and waiting for you know request plus bounties to show up yeah so it's anyone who wants to run one of our the first version is of course going to

be me not me lrange I might run one too if I really want to compete with lrange I on faster proving but I'm probably gonna lose um our team's quite quite good at that uh and um eventually it'll be anyone who has likely restak plus um yeah likely restak on I lay to be able to run approver obviously we want there to be some type of economic incentive behind running improver since effectively that that is what can guarantee liveness that a proof that are delivered back or delivered back in a timely fashion but to really kind of get to the Crux of what the offchain computation is it's important to kind of touch on something called a recal tree which is a novel data structure that our

team has has put out originally the first form of a vector commitment last summer at SBC and now in a new paper that we'll be releasing soon that kind of unveils this this optimized way to compute over over existing um mer like data structures that basically Builds an updatable batch proof on top of a section of the blockchain's state so we think of the the the let's just think of the storage try for example which is a 16 aity data structure built with catak hashing and rlp encoding for each of the branches um where you take a bunch of adjacent nodes you encode them in rlp you code rlb encoding you hash that and that creates a one of the adjacent nodes

for the next level uh you append and hash all the way to the root and so you can prove inclusion in this by just checking the inclusion of a leaf all the way up to the root um but what you can't do is to construct a very very large proof in in the current form that sits on top of a large portion of that data that can update as the data changes and so let's say I want to prove the inclusion of of 10,000 leaves the entire pudgy penguin's contract well the whole tree is going to change every let's say a subset of the tree is going to change and therefore the roots going to change every 12 seconds so am I going to run 10,000 inclusion proofs every 12 seconds what if I want more than one contract

what if I want the whole erc20 contract 2 million who's going to pay for all that compute it's currently in the in the present state of ZK not cost efficient to do that so what we've designed and what a research team has designed is this data structure called a recal tree this natively superimposes itself on top of the PT tree where you can in essence prove and assert the inclusion of some sub tree rooted at every point of this new data structure that can run computation over all of those nodes that it's proving inclusion of concurrently with asserting their inclusion and what that lets you do and what we do is we take that entire portion of the tree and we prove that it's equivalent to a new data

structure let's say our optimized database and then we can update that inclusion proof every block in logarithmic time and so what this lets you do is to basically have a node or have let's say an OS chain um lrange node commit to a portion of the tree and then continually compute and update a proof over that tree and then serve computation over that updated structure so you can kind of think about this as a very data Centric form of co-processing where instead of it being just a stateless prover that you put out a bounty to the node commits that I'm going to be able to maintain a data structure for this portion of the tree of this schema and this is the database

I maintain for you and then you request that node to basically generate a proof now over the optimized structure that built for you so let's uh put reaking completely to the side for a moment that's just going to make things too complicated but in this structure so I guess first let I will take the role of uh pudgy Penguins whatever company that is and you can be lrange so first of all like do I need to as a company come to like lrange protocol first and be like I am going to be running a ton of data across this smart contract and before I get started I need someone to commit to hosting this in a uh consumable form they you don't need to commit but some

pudgy penguin does need to commit but someone has to someone has to say I care about this data and I'm going to pay for it to be optimized you don't have to but the ques are going to be much cheaper if someone commits because if you commit to that that means all the quaries everyone else does both you and anyone else who wants to qu of that contract run over the optimized structure so you can think about this is defining a database or pre-loading a public database okay got it so so in the worst case scenario lrange can always answer the queries but if the somebody hasn't pre-committed to that specific section of data then you're essentially just running like for lack of a better metaphor you're

running like manual queries over a large data set as opposed to like hyperfocus queries on something that you've structured to answer queries right yes and it's much cheaper from a ZK standpoint an approving standpoint and much faster to run them over the the optimized database so in this world again I'm pudgy penguins and you're L Grange and I have not come to you and said I would like someone to commit to this you as the protocol or or a participant in the protocol might notice like oh my God this query gets hit 60 times a day every day like I it makes sense for me to commit to hosting this data structure because if I'm the only one hosting it every one of those requests is going to go to me and

therefore I'll be able to capture the fees from all 60 of those commits every day or sorry the queries every day that's actually very true so it doesn't even have to be a user of pudgy it can be anyone who says I'm going to host instructure this this data set and take take fees for Quon and that data set is basically a portion of onchain State maybe ERC 20 maybe you know pudgy maybe uh bord apes and frankly we're we're just going to commit to a bunch of the major contracts that they're available they want yeah and conceivably like with the power of Moors law and the power of folks like yourself researching ZK like it it is conceivably possible that the

the technological lift for like processing the entire uh like all of ethereum into one of these optimized databases like could be doable by a single node and and once you reach that point then it doesn't really matter if people commit to subt trees or not is that right well at that point then you should commit to chains ah interesting okay we'll leave that out as at that point we commit to change with the new where everyone we're gonna have thousands of rollups then maybe Millions so somebody has to still commit to these rollups yeah very interesting all right we'll we'll leave that aside to come pick up at the end but um okay so makes so much sense but can we talk a little bit about like these um first of all what is your term for the people that

are like processing data queries and returning them back to the lrange uh smart contract like the lrange node operators what do you call them yeah we should definitely hire a marketing person since probably the name I'm going to put out it's going to frustrate frustrate our future marketers yeah okay so we'll say l node operators yeah we can think lrange node operator operators or lrange proofers it'll likely be it'll be lrange data proofers Okay cool so lrange data provs we we're going to start off with just lrange Foundation or or however you guys are structured is going to be the first one is this I I don't mean to ask you a leading or a trick question here um but like is this an opportunity to create like a new

decentralized network of nodes um or you know and then like we can talk about like okay that requires cryptoeconomic security because you have this new nodes and then like we can go down that whole like token route which I'm not interested in or is the is the Insight here that the power of ZK really like allows these individual like lrange nodes to participate in this network without you guys having to worry too much about like coordination across the nodes yeah so that's a good question so it doesn't have to be a decentralized network of noes because we're not basing any of the computation Economic Security you're you're not running a a graph node to extract data from the chain then

staking to say you've extracted it right and getting slashed and it's none of that headache and none of that mess and potential you know risk of compromise it's fundamentally endtoend zero knowledge the from the construction of the optimized data structure to the computation of that data structure end to end zero knowledge and the final proof you get back can be verified with respect to the execution environment there's no need for any external signatures or commitments but you know I think I'm sure you know this and I hope many of the viewers here who have been watching you for a while this too you know you get safety from zero knowledge proof but you don't get liveness you don't get liveness of approver from a proof you get the safety of that that the the validity of the

computation but you don't you can't assert that if I want that computation at 2 o'clock on a Tuesday that that node is going to return to me the correct at 2 o'clock on a Tuesday or anything yeah it could it could be offline you know it could return to me nothing um and so that's where staking and that's where building a a degree of economic guarantees over liveness is very important right and that can come from proof networks or proof markets and I'm sure there's plenty of people who can debate both of those approaches for quite a while but at the end of the day you know it's it is an economic problem for liveness and that's where the this comes in yeah no no makes a lot of sense and when I think about like why we need proof of stake for ethereum like part of

that is about making sure all of the state databases on all of the different ethereum nodes are in sync and so I was thinking like okay for lrange like when we're committing to this like section of the ethereum state like well you're kind of creating a database here and so like do we need to be keeping all these databases in sync but then really you kind of don't because the you're creating a database that's just an optimized version of ethereum and you don't need to make sure that all of these optimized databases are in sync you just need to make sure that they match ethereum that's exactly it and you have the proof that it matches all you need to make sure is that if you know

you've committed to the pudgy Penguins contract to to serve proofs on there you'll be paid for the proofs you serve so if I send a request out that I I want the select all Quarry for penguins that are blue because you want some game logic to check if for blue penguin ownerships um then you can run that quy um and the person who serves it to you will will take a take a bounty on on that and deliver the proof back to you that actually brings up an interesting question which is when you're writing queries like as on the pudgy penguin side how how are you communicating these to the lrange network are these written in like a proprietary language are they written in SQL are they written as just like kind

of a human request like talk to me through like what is a what is the language of the lrange um system so the first version that we're going to come out with so take a step back we can support anything that's D data parallel so we can support SQL we can support map produce we can support spark and rdd um but what the first version that we're going to come out with will support is is is SQL and it'll be a subset of SQL statements initially the first test you know coming soon but then it'll eventually be be the full SE where you define your data structure on chain you define a series of events that correspond to specific SQL statements with configural parameters with respect to what you want those SQL statements to

be configurable um and then when those events are admitted you'll get the resulting proof back so you want to run you have a pudgy Penguins contract you want to support select statements based on owner and based on some subset of traits and then you'll be able to have an event that when admitted will correspond to that specific statement and you talked a little bit about um having l data nodes shoot I forgot the term but the lrange uh participants like choosing to commit to a subtree or a subsection of the state is there any thought about like giving these operators the option to committing to a specific query as well and I I don't know if there's really

that many like performance gains here but I'm just thinking like okay if I as a pugy pudgy Penguins game know that I'm just going to hit this exact same query like 700 times per day like maybe I don't even want to pay the gas costs of like the select star where this I just like want to communicate back up to lrange like hey run the Run query 7 is that is that all part of the the piece that you're building it is it is with the first version that we'll be coming out with we we do Target um basically you commit to data structure plus a set of course um and we typically think of those as tied to together because the most expensive part from an operator standpoint is is the data structure it's

that's the heavy proving with the with the snark unly hash functions and rlp serializations and the quaries are going to be very optimized because we can control what we've proven equivalence and transformed into but that's the first version I do see a world where if you know I need to qu the pudy Penguins contract let's say you know 500 times a minute or 10,000 times a minute and you also have to qu 10,000 times a minute some operators is going to say whoa whoa whoa I'm not I can't I can't handle both of you you know I I'll can maintain the data structure but I don't have the bandwidth to support both so I'll commit to that plus one Quarry and someone else will commit to the same structure plus another Quarry but that requires a tremendous throughput on the system I think to make that an imperative but

it's definitely something that we can support with the architecture um you know the first version is really going to be committing to a set of quaries and then committing to the the transform structure and the specific data schema basically the database yeah and that's actually a pretty interesting comment you just added in there it it's also about committing to a specific amount of bandwidth or resources too so it's about the schema maybe like as I said the queries that you're willing to service but also like the amount of bandwidth you're willing to dedicate to doing this exactly exactly cool so I think we've talked basically all through we can about how to use this system to um basically provide data capabilities to

Smart contract cont TRS what I'm really interested in is like the obvious next generation of this which is how do we give databases the ability to access and store and process data that isn't necessarily related to the evm so like obvious one like let's say we have tokens that represent um like wheat Futures and like a smart if we have that a smart contract should be able to like query whether data of the past to make a prediction on what the wheat uh token will be in the future and so my question to you is like one um how does will lrange eventually support you know

non-blockchain native data but two like how do you build a system that is um that that supports that how do you think about that so I think with verifiable computation the way I always think of it is where do you inherit the safety of that computation from generally the public statement and so within the public statement you a commitment to data that your proof will compute over or will prove computation over and so when you do this within the execution client you can get that commitment outright you can get the state of the the block header at some point in time let's say I get the most recent block header and I can verify the database with respect to that that block header when I start thinking about things that are off chain the question is where do I

get the safety from and this is the big question with verifiable computation verifiable databases right where you know if if I'm trusting you to supply the data for my my wheat Futures database and then I'm doing a verifiable computation over the weat features database really the safe it only inherits the safety of the computation from from your initial commitment and so if you lied on initial commitment the verifiable computation doesn't have the same same authenticity I can't the proof itself can't check if the data is correct and so that's where you need to be very smart with designing system so what we contemplate what we build are systems where we can prove the computation and the validity of that in so far as you trust initial commitment

so if you put a different commitment on chain we can compute over that so if you have an application that commits data every so often on chain uh there's without question a world in the future where we can let you support computation of your type with our verifiable design over that data so if you have a protocol for anchoring data and you want to have a very complicated system does that we can do that but you still need someone else to build I guess the other part of the modular stack which is how to you originate safe data yeah so it sounds like what you're saying is that everything is on the table with lrange but in order to maintain like the the security or like the magic that is granted to you by ZK LR the the position of lrange is like we are only ever going

to hold data to the Fidelity of like what appeared on chain and so if you want to run like stuff versus arbitrary data totally fine just put it on chain first exactly otherwise you know I could load data into into the database but if someone's going to Quarry that they have to trust me who loaded it which in if in that case we don't need the verifiability they should just trust me to give the data result any of the query yeah and so this question is not uh centered in like the the world that exists today but let's imagine like the world computer ethereum mainnet has aifi and like um we're closer to steady state do you

foresee there being just kind of like maybe like a dedicated like lrange data chain like do you see like B basically I at the end of the day your your answer to me makes so much sense which is like we're only going to uh prove against what is put on chain and it's like okay then we just got to put stuff on chain but we're also saying that block space is going to become scarce putting things on chain are going to be expensive and so I guess what I'm trying to get to is like how do you reconcile in the future State this world where everything needs to go on chain in order to be verifiable but in order to get it on chain like that was the

problem in the first place that's a great question so the way we think of it is within our schol of how I see L gr now we have no interest in building an L1 or building a data chain or building a data roll up or building anything like that I think that there are companies that are already starting to take like steps to build something like this Chronicle or I think witness is a new one that that announced a fund raise very recently um and they're they're a tremendous group um and I think this is kind of up their alley of how do we take data and we time stamp onchain and I think you can start building a whole bunch of really really interesting designs that take offchain data and put it onchain and that should

be in my view its own its own kind of cycle to be iterated on I don't think the company that solves truly verifiable computation over data is the same company that solves data rights on chain or how do I put data on chain I think that's a question of I think Network design incentive design blockchain design what we do is a question of verifiable computation snark design and and this a modular different modules yeah no very cool very very good answer and I think um I think like that's what's exciting about being in this space is that like what you're doing is building the tools that like could bu could be on the path of the future that

I just described but also like aren't necessarily and the reality is we need to build these tools in order to figure out which path we're on yeah cool all right so with the last uh less than 10 minutes here I would be remiss if we didn't just like spin a little bit around reaking and around like this igen layer moment and I think there is so much to be said like both like positive and negative about it that I'll I'll try to focus us a little and I think the two areas that um are worth talking about are one like you brought it you pointed at it already is like how would lrange itself um Leverage What what does it call them active validating services in order to become more secure and the other thing

which um feel free to answer or go down whatever Road you want but like what what I have been noticing so much on crypto Twitter and why I'm so excited to have you on this podcast is I just keep seeing like more and more announcements of like use cases or ideas or or like applications that are leveraging lrange plus Igan layer and so I think like yes I'm very interested to hear how Grange can use igen layer but I think maybe more interesting is like once you have these two Primitives what are the types of like things that we're unlocking so I I think the stuff that we do and the stuff that aan lay does is naturally synergistic what we do is is is entirely

ZK verifiable computation what Ian layer does is entirely a new mechanism for application to drive security from from ethereum uh validators ethereum stake and I think that these two things will unlock a new range of applications that we're frankly quite excited about and I think you can start thinking about okay once you start being able to prove computation and once you start being able to have new SEC safety guarantees around your your validator sets what are you going to build and so you can think of you know theoretically anything that's that's an ABS will likely have read access to ethereum so if you build a rollup on an ABS if you build a new L1 or L2 on an ABS whatever you build on ABS you're going to likely have read

access to eum State an ethereum block header and now you can verify proofs with respect to that if you have read access to multi-chain block headers because you're using ethereum as this mechanism to intermediate cross-chain messages then you can run verifiable computation over those commitments you don't need to have any type of complicated infrastructure to cach historical block headers you can just natively run them and so that's some of the stuff that we're frankly quite excited about because you have a whole range of applications that will keep just inheriting safety from this Baseline that will keep basically writing State Roots writing commitments to their own State onto this L1 that we can then structure computation over verifiably and allow to manipulate and and and and

um in essence run ETL on to kind of get these optimized databases and quity optimized databases and that's what we think can unlock a lot and just reaking broadly as a primitive is also something that we're going to consume because I think just the cost of capital the the safety guarantees and just end to end what it is is inherently much much better than um the the status quo when where you're you're you're trying to boot trap and network on your own token yeah and look I I definitely like as it's played out like have my kind of criticisms of Igan layer but like the the thing that will always be like the the magic Insight on Igan layer is like look I I

just we keep building these systems that are like predicated on like and then we'll have like hundreds of thousands of real people running real computers that like participate in this network and like okay like I believe in ethereum I believe that's going to happen but then like then we have thousands of l2s and each one of them have like tens of thousands of people and then we have like thousands of Oracle networks and each of those have like at a certain point the amount of like nerds willing to like take up space in their wife's closet to run ethereum nodes like is just going to run out or sorry run distributed computing software is going to run out and I think like what is like magic about igen layer is this idea of

like okay like how do we just like build one network one network of computers and one network of trust and like the computers are the ethereum nodes and the trust is the ethereum and then the question is like what do we use it for and I think um like if you're not living and breathing in this stuff like it's a little hard to understand why igen layer this thing that has nothing at all to do with ZK was like the atomic bomb that set off the ZK gold rush but I think it's just in this this like um vend diagram of like computation trust that

it and like right in the middle is like how does that happen that's lrange protocol or and don't mean to take anything away but or any of the other like 30 uh companies that just raised capital in the last year to leverage this like absolute freaking magic technology to create the world computer it is it is I mean there there's a phenomenal phenomenal group of projects building an aan they're an ecosystem that we believe in very strongly and I think they're one that we think will be around for for the duration of of of my career in crypto um and you know I think I think you you you place your bets on the people who you think have a true first principal understanding of the space and then you stick with those bets and I

think I is a team that we've believed in for a very long time and one that we continue to believe in very strongly um and with what what we build we think there's a there's a good opportunity for it to overlap um very closely with with the types of things you can build on there especially because you know as we kind of started with about talking about this little black box that you can do on chain there are teams who have for the the longest time been bumping into the edges of that black box to try to build new things that are just not possible in the current state of the art and those are the teams that I think we know of the ones that we know about they're the rollups who are trying to build complicated fraud prooof mechanisms they are the the reaking protocols the LRT

tokens the the complicated di5 Primitives the things that push the state-of-the-art and capture our imagination are the things that are the most hitting into these walls of what can be done today on chain and that's why we have historically got along so well with these teams because you know I think I think they run into the issues that we try to solve and they build the things that we try to use yeah and again I think ZK is the like magic key that brings everything together because like I really believe that ZK like when all said it done is about taking the like most crazy computation and projecting it into the most resource constrained environment possible and like that's exactly what you're doing with these

like it's so resource intensive to do like big data analysis on data sets but like what ZK does is allow us to project that back into smart contracts and that is what the ZK Gold Rush is is to figure out like well man what else can we compress and put in there that's exactly it that is exactly it cool man well I as you can tell like this is like exactly what I think is so interesting and I could take you down this like we could keep talking for hours and hours and hours but for the sake of everyone Let's uh we we'll try to wrap this up here so first of all Isel thank you so much uh I learned so much just U one about what you guys are building but to through what you guys are building just how all

this stuff is going to work and so so incredibly excited so incredibly thankful and just um thank you thank you so much Rex I really appreciate you having us having me and I appreciate the the level of Interest you've shown and what is a very esoteric subject but one that we we expect and hope to be very impactful in the space for sure for sure know I appreciate it and Before I Let You Go um can you just tell the audience where they can find you where they can find lrange and if they're kind of like getting inspired about like what does it mean to have a smart contract with access to data like what's the best way to get started yeah so I think the best way to get started would be to ideally use our test net that should be coming out in late March um or to reach out to

me directly if you want to build a little bit Clos with our team um you know you can find uh me on on Telegram and on Twitter at ishr you can find lrange on Twitter at Lev one word or you can go to our website uh L.D um and we have good resources there to help people who are interested in this stuff kind of dig in more and kind of get a deeper understanding of of some of the things that our team is very excited about we'll be showcasing to the market very soon all right awesome man well make sure that your Twitter and uh is in the show notes and everyone can find you but um once again just thank you so much and and uh have a great rest of your day likewise