Zero-Knowledge AI: The Frontier of Cryptography

welcome to Vanquis where we explore the frontier of Internet money and internet finance and today on this episode of our Zoo's aloe series we're exploring some New Frontiers New Frontiers and new technologies all of which are poised to completely revolutionize the world and change everything about the operating system that Society is currently running on this episode of our zuzelio series we're exploring the frontier of cryptography which is maybe not as new of a frontier as some of the other ones that we've explored yet nonetheless the cryptography enabled future is poised to change the landscape as all the other

technologies that we've talked about I will say the the ZK week at zuzallu was one of the weeks that I intended the fewest talks and workshops on because I mean come on what am I going to do there which is why I pulled in a very familiar friendly face Justin Drake to summarize the entire ZK week at zuzallu in a 45 minute episode turns out there's this cool new frontier of crypto called Nova Nova ZK Nova which has to do with folding numbers recursively to make cryptography harder I don't know how to

explain it but that's what Justin is for but first before we get to the familiar territory of Justin Drake We're going to talk to Daniel Shore who's working at a startup in the zkml landscape which has gotten a ton of hype and attention lately and if you listen to the interview with Daniel you'll understand why the thesis is that there's going to be a Cambrian explosion of AI models out there and simply verifying the model itself on chain using ethereum and a ZK proof can give consumers and users of these models assurances of the

authenticity and the outputs of that model the fact that the input actually went through the correct model and the output is actually verified by the model that you want why this is important and what this unlocks Daniel will explain in the show Bank location this one is a doozy but Daniel and Justin do a great job of dumbing it Down For Us in this episode so let's go ahead and get right into it but first a moment to talk about some of these fantastic sponsors that make the show possible Kraken Pro has easily become the best crypto trading platform in the industry the place I use to check

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know uniswap it's the world's largest decentralized exchange with over 1.4 trillion dollars in trading volume you know this because we talk about it endlessly on bankless it's you to swap but uniswap is becoming so much more uniswap labs just released the uniswap mobile wallet for iOS the newest easiest way to trade tokens on the go with a uniswap wallet you can easily create or import a new wallet buy crypto on any available exchange with your debit card with extremely low Fiat on-ramp fees and you can seamlessly swap on mainnet polygon arbitrum and optimism on the unit swap Mobile Wallet you can store

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the op stack but uses eigenlayer's data availability solution instead of the expensive ethereum layer 1. not only does this reduce mantle networks gas fees by 80 but it also reduces gas fee volatility providing a more stable foundation for Mantle's applications the mantle treasury is one of the biggest dow-owned treasuries which is seeding an ecosystem of projects from all around the web free space for mantle mantle already has sub communities from around web3 onboarded like game 7 for web free gaming and buy bit for tvl and liquidity and on-ramps so if you want to build on the mantle Network mantle is offering a

grants program that provides milestone-based funding to promising projects that help expand secure and decentralize mantle if you want to get started working with the first dowled layer 2 ecosystem check out mantle at mantle.xyz and follow them on Twitter at Xerox mantle bankless Nation it is ZK week here at zuzelu and I am talking to Daniel from modulus Labs Daniel welcome to the show thank you for having me okay so uh there is growing hype and attention around this world of ZK ml uh and so we're getting some hypey

adjectives uh not adjectives hypey uh letters consonants yes exactly letters yeah uh can you explain the world of ZK and ml to the best of your ability and as short as possible and then we'll get to why these things are currently getting married in a short time yeah I think um I mean let's just start with the letters ZK is the first two zero knowledge is often known as an accountability or Integrity technology so it basically tells you that some compute was done correctly so that's exciting and actually has this odd property we're verifying that compute is

a lot less expensive than doing the compute naively so it's often been used to compress information and then in the case of blockchain bring that information on chain while retaining the security standard the metaphor we like to use a lot is that it's hard to complete a Sudoku puzzle but once a Sudoku puzzle is completed it is easy to verify that it was done correctly exactly and that's just like ZK in his Essence yes yes precisely that's that's kind of the most powerful property of ZK in the blockchain context kind of what's next then at least for us was okay

excuse me if this technology can be used to scale blockchains what is the most kind of intense or almost irresponsible kind of compute we can throw at this kind of technology and in terms of the size of compute it doesn't get much larger than machine learning models irresponsibly such as just in like the magnitude of the compute yes exactly so you're stress testing the whole Paradigm of ZK that's right and that's how you got to ml that's right why is okay what is ML and why is it so intensive yes so machine learning or just artificial intelligence in general is a process of

using an algorithm to approximate human-like decision making so think like high semantic output space right so I want to look at an image and decide if it's a cat or a dog or I want to uh kind of predict what might happen prices in the future by looking at a lot of data from before traditionally this has been seen as kind of a task for human human beings but ml is this kind of wild regime where algorithms can take the place of human decision making and specifically these algorithms uh there's there's a software and a hardware component right and the hardware is kind of the clock speed how fast this thing

can think and you can throw a lot of hardware at this thing you can you can and that will get the result faster but the point is is that blockchain's ethereum is not is not something that you go to to do a lot of compute quickly because that is what gas is that is what gas fees are that's right okay so like where does this intersection occur at so like if you're if you said that you want to have this irresponsible use of a ZK proof and what that means is just like throwing a lot of compute at this thing that's fun why is this a real utility

well yeah why is this actually useful well kind of the the magic is I guess the security of the blockchain right and the ability to bring compute of any size but especially in this case really large compute up to that same security so that you can ingest AI decision making into your smart contracts or into your D apps and on-chain services that we think is a really powerful Paradigm and something that's now uniquely enabled by the fact that ZK has improved so much and especially at least in the case of modulus with a focus towards machine learning compute okay so apps can use AI

you just unpack that a little bit for sure it's it's a very general statement yeah can you make it a little bit more just to find and illustrative of course uh let's take a uh uh some kind of defy service which has liquidity pools perhaps they want to rebalance these pools using a really Advanced algorithm maybe something even akin to an AI algorithm currently all that compute needs to happen off chain because it's just too expensive to run on chain but with zki or zkml you can imagine that option compute getting that Z Haze seal of approval it's like okay this compute has been pre-committed bless you of course and using zero

knowledge we can prove that that compute was done correctly thereby upgrading it up to the security standard of the chain and it's as though that entire process in this case of rebound announcing the pool ran naively just on chain why do you need to verify why do you need to verify it why can't you just run it without actually having to verify it yeah and I guess I'll start by saying a lot of services currently do just run compute off chain right it's certainly a lot less expensive but I think a big part of why we're in the blockchain ecosystem at all and certainly a big part of what attracts modulus is the

kind of security standards that's established by this decentralized decentralized network of nodes and having the social consensus and all the wonderful things we get in ethereum and some other chains as well and so we want to make sure that the services that write on these chains that buy into the security ethos of the chain gets to participate in that fully even as they take on bigger statements of work when it comes to compute so if I'm a d app or I'm an on-chain service and I want to use AI maybe I don't have to give up on the security that my customer and maybe even myself I expect out of my own

service okay so the I think the reason why this whole area of focus is getting so much attention uh ml machine learning chat gbt has just like elevated that into the stratosphere yes uh ZK on the crypto side of things uh the the theme of ZK week was how fast and compressed and capable some of these ZK circuits are becoming yes and so on one side of things we have the growing Cambrian explosion of AI getting large in capability and then on the other side we

have ZK decreasing uh which was what ZK does decreasing complexity and and simplifying compute yes and so like at a high level at just like broad stroke you can see how these things kind of would work together I'm guessing without um knowing too much about this kind of naively that the idea of putting an AI on chain implies that there's going to be tons of AI models like generalizable and any any kind of model that you can think of that an AI would be able to to

produce for I don't know uh D5 liquidity comes comes to mind but like literally anything sure and then the idea is that with uh zkml you could to verify the uh the actual model the external model that I'm assuming many many people are going to work on like individual models and we want to make sure that that is the actual model that we are running on chains and that is that's the ZK component yeah you got it I mean this is uh I mean sure it's defy and it's certain Market mechanisms potentially or maybe moving users uh funds of course or

crypto across different chains to optimize yield farming or even nfts right let's say I want a machine algorithm to Output pixel art or any type of generative art but I want to know that that piece of art actually came from the algorithm that might be really valuable right so zkml is a way of extending that kind of cryptographic Promise of authenticity to all kinds of uh AI outputs specifically um so you know I guess the possibilities are are substantial so long as we can get the tech right and I'm obviously all the acceleration on the ZK side really

helps with that so I'm just going to like list off a bunch of models that I can think of we got like uh chat gdbt is the big one gbt4 um mid-journey um what are some other ones that are out there like we got we got um uh Bard sure there's all of these older models like Bert right recommender models uh generative models that output uh pixel art Gans generative adversarial networks as well as uh maybe more subtle models like uh anything from uh you know a game that uses an agent right an AI agent to

simulate NPCs uh to something more kind of outlandish like uh like an llm that maybe predicts uh investment decisions or things like that so um perhaps one model is in the gaming World sure is something that is uh generatively producing a landscape sure yeah that is a model yes and maybe this applies in the world of uh for people that are familiar with dark Forest sure totally you need to make sure that we're playing a game that has a specific model yeah to define the landscape of the game that we are playing exactly this is an example of a model yeah that's great and and the

counterparty risk here is bigger than just swapping out the models it's swapping out the output entirely so let's say you have an AI responsible for the landscape or the weather or the in-game economy or it's like a almost like a god role in your game right um if you know I as the operator of the game or the developer is biased to let's say penalize David's camp or David's planet right we're going to Nuke your planet from orbit via the decree of the galactic government and there might be enormous Financial Stakes to these in-game economies that's like a devastating result and so in the same

way it's a rug pull it's a rug pool yes and so in the same way that blockchains kind of extend this uh this veil of security where this this promises security rather to everything that's on chain we want to make sure that keeps being the case even as we want to bring AI kind of feature sets on chain right okay and so like just going further like we got the AI generative landscape and uh you also have like the models of AI NPCs sure and like I could just think of any this is kind of fun to think of like what AI models could become but I think that's kind of the point sure is that it's so generalizable right and so uh

AIS we're about to get into AI week loss of AI talks happening right now there's a talk of generalizable AI like artificial general intelligence but then there's also the topic of like narrow AI yes these are both models yeah right like Alpha zero is a narrow AI about Chess and then we have more generalizable AIS that we think are coming or word are coming also a model uh and so uh the the landscape of models which is a it's one of those words that you don't really understand until you see how generalized it is the growing

world of AI is generalized models for stuff and I and then the ZK element allows it to take the soul of that model of a particular model and and place it on chain to become an on-chain resource that's right for the rest of the blockchain to ecosystem to use exactly and it has all those properties that we love so much about things being on chain including it's composable uh it's it's it's obviously a high security uh it's in some sense really a testable and referenceable all these things that you know are makes the chain kind of a wonderful environment you kind of imbue

that AI compute which previously was just in a black box somewhere and so like this I'm I'm assuming yeah the composable part gets really really cool because then you can create some sort of system that create creates a world of models and I don't know where where is the utility coming from first like so if there's it's exciting to see all this possibility sure what's the lowest hanging fruit where it's going to get built first yeah great question you know there's already kind of prototypes including ones that we've built and others as well kind of exploring it's still a very nascent category right

everything from you mentioned this briefly but like chess engines right so we brought a formula in parameter chess engine on chain and now players can stake and bet against a chess engine knowing full well that they're always playing against the same AI model and in no way can modulus or anyone else swap out the results of this particular chess engine by calling up our friend Magnus it's like hey Magnus what move would you play right yes uh but you know that's just where we're starting uh we're also starting a ZK Gan project so generative art and of course we're kind of marching towards that llm goal but there's a lot of kind of space in between that of

course right again I mentioned like recommenders earlier clear there's a lot of use cases for just any amount of personalization when it comes to the chain but still at the kind of security standards we want right if you have a social media feed but you want to know that the same algorithm that drives the Equitable results you see on Daniel's feed is the same one that David sees then zkml can play a really really key role there so okay at modulus Labs uh what What's the current what are you guys focusing on right now what do you guys what's the current uh bottleneck or constraint or problem that you guys are currently solving yeah like where are

you where are you in the road map I guess yeah great question so uh you kind of alluded earlier in the ZK week right we're seeing kind of the ZK overhead come down substantially and that is amazing and obviously very helpful precisely because at the top we mentioned that AI is like a lot of compute it's almost irresponsible I think the exciting here is that our job's almost easier because AI as a classic compute is really structured really repetitive and those things those like properties of that compute allows us to make the ZK stack much more efficient right in some sense it's almost like you've down selected to a

more specialized class of problems that gives your ZK approver a lot of space would be more efficient and kind of take advantage of that structure and so module is kind of what we work on for the most part is making the proving stack significantly more efficient so we can bring much larger much more expressive models on chain at so that same security standard okay so this is what your guys's technology is you guys aren't you guys aren't bothering with the AI world you're not here to build AI models that's for the AI industry that's right yes you're here just to build the bridge to be able to verify models on chain exactly so you guys are operating in the ZK World precisely precisely you

got it yeah okay uh it sounds ambitious uh we do our best yeah uh there how many of there are are there how big is modulus Labs modulus Labs is currently a very proud for people and when did you guys get started uh about seven months ago okay yeah uh where did the original inspiration come from was there like an aha moment or how did the team come together and what was the the motivation yeah I mean this is going to sound a little ridiculous but of course there was all this kind of excitement around stable diffusion and generative models and around the same time we kind of fell in love with ZK and we kind of started asking ourselves a question of hey kind

of what would we want to build here right and the background of the team is all like AI researchers from Samford and so it was almost kind of an obvious thing uh we kind of asked ourselves oh how silly would it be if we like put a very non-performing AI model on chain to I don't know let's say predict each prices so that's what we did we built the world's first on-chain AI project as a joke we hacked it over uh or hacked it together over a week and it started predicting prices of eth and making trades on L1 with a unisoft contract um it's a joke right we did this purely as a proof of concept we the point was

not to make money on eth I don't think I don't think the goal was to make money that wasn't the goal no no it was an idea and this model would not be able to do that to clarify uh but kind of uh and I guess just to really nail that point home we didn't put a call function in the smartphone so like once money went in we put in like 500 bucks right um no one could touch it us included uh but kind of something miraculous happened which is lots of randos on the internet and ons uh included started donating money uh to the to the trading bot and if you look at the kind of

historic performance there's like a friend and it kind of goes up into the right right it's not actually doing that's just like buoyed up by the donations it was getting um and of course eventually it lost all everyone's money uh as we've been telling a very kind of transparently uh their algorithm failed to produce more ether it did uh yeah but it did uh succeed at being an algorithm on chain exactly and was the point precisely and kind of there was not nothing that the modulus team could do to again tamper with anything that it's kind of like an imagine like an autonomous robot budgets executing forever

um so kind of from that point we're like oh man what if we brought an actually performant model on chain imagine how cool that would be yeah okay uh so there's there's two worlds that I see spawning here there is uh the insular world of crypto who's like oh we could build models to do things inside of the crypto world yes and then there's external uses that need to verify models and their execution off chain yes is that can you talk about how these two worlds might develop independently yeah

uh exceptional kind of insight you're totally right and that's kind of how we see it as well in some sense the crypto world is a little more convenient because um you know there's already kind of a cultural expectation of compute Integrity as a really core value right we want to see that as much of the compute that's related to our d-apps and on-chain services are on chain as much as possible right this is kind of the the excitement that's driving all the ZK role uh kind of activity but of course uh the question is what happens when you step beyond the on same world does the rest of the world care about verifiability that this algorithm was

the one that made that decision right and you can imagine in a future where the judicial system uses large language models to make decisions about sentences oh God forbid or a medical system that uses a very sophisticated model that determines certain medication treatments these kind of intersections are really sensitive where liability is a big concern I think verifiability is going to be a big deal and what's cool is we get to get that flywheel started the cultural appetite for it in crypto and really kind of hopefully build up a really strong kind of um almost a a a

strong example of what it's like to be able to attest and make our algorithms accountable and then we can communicate that with the rest of the world but modulus right now we're very much focused on crypto uh with kind of an eye to the Future sure sure yeah but but knowing what the eventual Tam would be especially as the Tam is likely going to grow as AI grows right so the the mental model I have is like the little like SSL certificate like a little shield in your yes it's this it's kind of like that it is prove this model that you're using is proofed exactly and you know thumbs up

go for it that's right rug pull resistant exactly or a rug pull immune um I would imagine that like as uh all of the AI people that are over there talking about AI Doom uh they're they're talking about like one of the past towards AI Doom for first before Doom we get to AI fun times and so that's right in the AI fun times uh you know an explosion of models an explosion of usefulness an explosion of human productivity and flourishing and wealth generation precursoring the the inevitable blow up

but before we get there it's a world that we like live the humans live on models yes and our life is Guided by models and determined by models and so with that Cambrian explosion of models I would assume that the surface area for rug poles also gross yeah uh it's it's actually kind of terrifying how big the attack Vector can be for uh you know generating cash results in your AI models right there's a kind of classic example of a vision model which sees a stop sign and you go in or a picture of

a stop sign say and you go and you put three pieces of tape or manipulate some pixels in a totally in a way that's totally indecipherable to the human eye and it thinks the stop sign is a you know a go sign or God forbid is is a toaster you know anything right these AI models do have very substantial kind of adversarial environment or attack vectors and uh it's it's a little scary for sure yeah okay so we're helping secure our future which sounds pretty important and also it's like making it it's just like trustless there's many different aspects of AI and this is like one way to make AI applications safer it

is not it's not the AI safety conversation but it is part of it yeah I mean the way I like to think about it is you know you have all kinds of different models and your model might be more explainable more robust to attacks uh more Equitable right it doesn't bias for a specific political allegiance or anything else right and these are amazing attributes and very hard problems that people are actively working on but without verifiability right without the ability to pin down that model at any given instance of use you can swap out that fair model that robust model for a different one or for

no model at all I can just be feeding it any answers I want as the operator and so in the same way that the security center or blockchain is that it's all there right like you can just go into The Ledger and see exactly the transactions we make sure that the algorithms have that same kind of quality right and so the one the insular way of using this technology is that we get smart contracts that are AIS that get to do things on chain and that's going to be pretty cool and tight and I don't even know where to think about how to start thinking about that but the outside world is at that point just

using the blockchain as like a Time stamping tool correct yes yeah yeah as in the blockchain is kind of this amazing environment where uh public verifiability is like so obvious there right and so it could be this amazing kind of settlement arena for the world's compute right yes yeah and and in a world in which uh we are probably are going to be using AI models and we're probably not going to think about the rug pull back surface surface uh area sure right yeah so like humans when uh

when we use these things we're going to assume that they're the things that we want them to be and so we're not going to be looking for the rug pull and this actually this technology actually allows us to be cozy as we use these models yeah in some sense and in Silo Insidious um these models are very sticky they're incredible right they're very personable uh magical kind of uh features that we can add into every part of our compute diet as a society and of course while that's happening we're very quickly expanding the surface area of potential attacks and you know the goal is to make

sure that before we have that catastrophic outcome right before somebody gets really injured where a lot of money is lost because of the widespread use of large AI models that we have that accountability piece in place along with all the other AI safety Technologies yeah uh Daniel I would imagine that this conversation just about ZK ml what we're talking about here can go on and on and on and on and on it definitely can what parts of the what are there any big parts of the conversation that I haven't opened up yet a good question I mean I every part

seems like it's it's filled with potential right uh but something that we spend a lot of time on for example is and this is going to sound like the opposite of the kind of aspirational exciting thing that's happening is the literal cost of doing this process of running these compute or these are very this very expensive class of compute in a zero knowledge setting and making sure that although we're excited to kind of have our heads in the in the sky uh we're kind of marching towards uh real implementation real use cases real customers right so uh you know it starts with working folks like World coin on identity verification or or self-custody of biometric information all the way to

games and D5 protocols and of course nfts as well to kind of push the envelope on accountability for machine intelligence right so um you know we have this kind of bigger thesis but at least for modulus and I think the category in general this nascent category we want to make sure we March to the beat uh of of kind of uh real you know impact right making sure that it's actually making a difference uh in the ultimate lives of these service providers the phrase accountability for machine models I think is going to be something that really uh resonates with

a lot of people even at just like the the cursory level yeah right uh AI had is going to and has triggered just like a lot of people is just like the the hairs on the back of their neck sure uh and so just as a branding so yeah hey we're helping me I a I uh be safe it's like a really good branding to lean into well kind of what's exciting of course uh is beyond just The Branding being kind of very appealing for sure is that this is uh you know I AR researchers are not going to love kind of the way I phrase this but I almost see these Technologies with personalities right

um AI is this like very expressive creative like infinite potential very powerful but cryptography is very humble it's very discreet it says this is the statement that I can show with pure mathematics and you know this is kind of the the kind of claim that I'm able to make and no more and so being able to marry these two things which have quite a bit of tension by their nature is something that's like deeply exciting for certainly and I think the whole modulus team right yeah yeah you use that word expressive which is like one of my favorite words uh and and we have all of this explosion of AI models who

that have all of this power yeah and personality that you're saying and I think like maybe adding in that ZK the ZK circuit component also adds in just like a stamp of authenticity yes where's icy yeah it's like um I mean you mentioned the little little check mark where it's like a Twitter verify check mark maybe back in the day when that was more substantial socially uh but having something like that for your models right for your AI models or for your your any mechanism that is you know sophisticated compute precisely Daniel I've learned uh quite a lot uh where

should listeners go if they want to continue going down this knowledge Rabbit Hole yeah I mean uh uh not to show our own stuff too much but modulus Labs we're on Twitter uh uh we try to put out decent content um and of course I watched your guys's first video on the scroll YouTube and man that that broke my brain oh my goodness yeah yeah there's there's you know all parts of the stack to enter were very technical to kind of more philosophical but we want to make sure that kind of we meet people where they are because it's really cool and we want as many people kind of to be in uh in the know about this stuff and kind of be part of this movement for your words now

accountable machine intelligence yes I love it Daniel thank you so much thank you David really appreciate it yes metamask has something new introducing metamask portfolio metamask portfolio is the best way to view your crypto portfolio from a holistic level see everything across all the trains all at once in your portfolio metamask will report the aggregate value of all the assets in your metamask wallets and even the other wallets you import too but metamask portfolio isn't just a passive portfolio viewer it is a place to do all of the money verbs that make defy so

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