Illia Polosukhin: Near Protocol – From AI to High-Throughput Blockchain. Ep. 529

Transcript

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sharded layer one blockchain so welcome welcome IIA welcome back on epicenter it's great to have you for a second time yeah thanks for having me and congrats on uh yeah 10 years EP epic uh achievement in this space yeah thanks so much yeah like you said it's it's basically 70 years in crypto so we've we've all aged a bit yesterday in the episode we recorded yesterday the 10 years episode they had like this slideshow and you could see the progression of me Brian and Sebastian uh like from their youth to their 40s or late 30s so yeah that's great um cool yeah we actually wanted to start

unconventionally um with your background um but in your case is a very interesting background in Ai and machine learning so um we wanted to First sort of talk about your work there uh you're one of the authors of the original Transformers paper um can you yeah maybe start by like telling us about your start in the AI and the m space for sure yeah I mean so I started tinkering with AI I think given in high school uh I was actually excited about neural networks as a concept and uh I worked for a machine learning company that was pretty old school machine Learning

Company uh starting from first year of college but when I saw kind of deep learning resurfacing in 2012 13 there was this kind of seminal work at a time which uh now now feels like da but back then was very exciting which was uh they trained in neural network to encode and like encode the image and then decod it back into the same image so pre-training what we know now as uh and that model without any supervision learn to detect cats and so there was a neuron in the network which if you

activate it it would it would generate a cat and like different types of cats and so it learned something like semantic without any training like in any like input data from humans right just by looking at images and so when I saw that and that was done by Google by Jeff and Andrew and they did it on a bunch of gpus and uh like they they managed to scale it up and I'm like I want to do that I think that's that's the thing that's that's going to you know actually change things and so I during Google research uh my Bel always was that natural language not images going to be the driver for reasoning and for uh kind of like intelligence because you know

there's many many species in the world like hundreds of thousands of species that see and only one species that talks and has language right so there's way more semantic information in language and so my team worked across a variety of things uh specifically uh question answering so when you like type uh questions on google.com we were actually running a neural networks to try read our like uh pages that you see and respond to you with like a short answer so like you would see sometimes short answers now the challenge was the neuron networks at the time specifically recurrent neuron networks were too slow to be put in production and so we were

just using begga words models which means you literally throw all the words without any order into the model and it kind of tries to figure out what's going on and it it worked re reasonably well but uh and this is where kind of uh the Transformers gave bir was like we could not use RNN in any practical use case and so uh we were looking kind of for something and so yakob who was a manager and had like an another team uh came up with this idea like they were using attention on top of words without any occurrence for for another task and so kind of merging that idea with currence like can we use attention to

somehow uh figure out which words are relevant in the order when you do answer questions or translate something and that kind of gave birth to the Transformers really was like we need something that's really performant that can be highly paralyzed and attena is really good mechanism you know logically to do this but if you package it all kind of the way this models really work is that everything happens in parallel like the way I like to describe it there's this movie arrival where aliens talk in the whole sentence at the same time like there's like a circle of screw B but they produce it at the same time that's kind of how Transformers actually read articles it's not like one word at a time it's literally reads the whole

article all the words in parallel and then like has multiple steps to kind of process it and reconcile this like the understanding of it and then it answers the question and so so that lays out really well for the Modern Hardware gpus that we use and so it allows to have like this massive kind of performance Improvement which means also you can scale up the models and so I've uh was a you know worked on that with a team of amazing researchers uh which now all went to do really cool stuff uh and then at the time I decided to leave Google to start an AI company near AI which was supposed to be pretty much teaching

machines to code so my believe and I still believe this that now given this these types of models you can change how we interact with Computing you can actually talk to computers and they do work for you instead of needing to have an engineer to write code for you right which again like now it seems more obvious that that's possible back in 2017 there was like huh uh and so so we started in neari but we only we gave us a because obviously at that time it was a mad and we didn't have that much resources so we're doing some interesting stuff uh around data collection and some machine learning but one thing we ended up doing is getting a

lot of people around the world actually doing uh like writing some code for us writing some descriptions for the code and so we had struggle to pay them because they were mostly students in China in Ukraine and Russia in kind of some other countries and like some of them don't have bank accounts some like Ukraine for example PayPal doesn't work in China PayPal doesn't work um and so there was like no good way to do it like programmatically uh to send people money and so we started looking at blockchain as like hey can we just send people money easily in in code and the answer was in 2018 the answer was actually no because

even back then the fees on bitcoin and medium were way too high uh and and then as you probably know when you start on the blockchain rabbit hole you canot stop you just keep digging you're like wait what is this and so uh so we kind of as we kept digging and researching different blockchains and different Technologies we're like oh we actually know how to build um something of this sort right so my co-founder Alex he was building Shard of database company before um and we have like you know systems background we're like we can probably do this but we can focus on user experience developer experience while kind of solving this scalability underneath and

making sure fees are uh staying stable and so that's kind of how we went from near AI to becoming a near protocol in 2018 and starting this journey so Ilia um in this current wave of llms uh of course like this attention mechanism is a key part but another key part is just the idea of you know like just the idea of scale right like collect a lot of data from the internet from books and then pre-train the model and of course the ideas of rlf and all they came later but the fundamental idea is you throw in a lot of data you pre-train you make a big model it's

going to produce good results did you anticipate that scale was going to work this well and if so why did you use that approach in near Ai No I I that that's a part that definitely kind of was interesting to see uh that as people scaled up the models they became like they started exhibiting kind of properties like more and more sophisticated reasoning properties and it's like it makes sense now that you know you think about it like the capacity of the model is higher it it's able to like generalize better it's able to kind of learn quote unquote programs um that it can execute but yeah

at the time that wasn't like particularly clear uh that like it will be that kind of Step function change and so we yeah we were not at neari we were not doing that partially because we also just didn't have uh you know like we ra you know small SE like preed round actually and uh we we thought we could get get better uh supervised data instead um and we did we did some pre-training on like GitHub and and things like that but we we didn't thought didn't think of like train on the whole internet uh at like large scale and we did have resources to do something like that

either and the other interesting thing is kind of like this this attention mechanism also seems to like it's built for natural language processing but also seems to kind of work across different modalities like such as like images and maybe video in the future and what like how does that come across to you right is that unexpected or is that is that something you expected in the past I mean like when the Transformers were just in development there was like like the teams actually tried them on different modal I mean not like multimodel models but different modal is and it was pretty interesting to see it

worked really well um so I think it's that was kind of known that it works on on different modalities pretty early on I think the kind of the intuition there is really that you know the way kind of we work as well is very much like like our our eyes actually like move all the time every like as I forgot how many milliseconds and so we actually kind of pay attention to different parts and then our brain kind of constructs the image right at different levels um and kind of you know natural language same right you read sentences you like build some semantic meaning and then you know you kind of continue building out this the meaning of the what you read um but sometimes you like

zoom in on specific words when you need to uh answer a question and so like I think like generally speaking there is like intuition behind this but obviously again it's like it it's interesting to see how well it all works right definitely you know um like we H we had a pretty good models like even before it it just like they were super slow and like non you couldn't use them in production at all but this you know obviously like the the scale was which for example opening I went and and scaled it up and and by the way they did tremendous amount of work to make it work like it's not we cannot take it for granted they're just like oh we just

increased parameters and had enter like no it was a ton of work um across the board from you know low Lev engineering to like fine-tuning to you know they change some of the model uh kind of details of model architecture as well um but yeah like the it it is it is it was surprising for me like I think like when it went from two to three that was like interesting uh like two it was kind of like okay yeah I get it like we' we've trained models like that at Google kind of thing um from 2 to three it was like okay that's that's really interesting because I can see um the you know there's like something more now happens and obviously 3.5 is where like okay

yeah that's like it actually learned something that is like Beyond uh just language Mal right like there's some reasoning that this is extractable now through kind of this instruction fine tun on a high level I'm I'm actually curious what your stance is on this stochastic parrot versus understanding Spectrum so so there are um there are people in the AI community that let say that llms actually don't understand anything they are stochastic parrots in the sense that they have understood the statistics of what word follows what

other word in language because they have seen billions of examples and when you talk to an llm and it's generating words is just uh replicating the statistics of what it has seen in the past without actual any understanding behind behind the box that's the like at the extreme that's the stochastic parot View and On The Other Extreme perhaps there's a view uh maybe like theat view which is kind of when you force a model to predict the next word uh and you force it to do it again and again in order to predict the next word it has to start learning something

about the world itself to do the the job of prediction well and in kind of trying to predict it well it is forced to learn about the world and so it has actual actual intelligence about what world it has in it is in so it's not just uh stochastic parot this is actually when you're talking to gp4 you're talking to something which has understanding distilled into it and there seem to be like these two Extremes in the in the space and I'm I'm curious like where you stand on on that uh on that debate yeah I mean I definitely closer to

S View I like from my perspective kind of you know it at the end is bunch of math right and so like you can kind of decompose what this math is doing and you know try to build an intuition around like types of Transformations it can it can or cannot do and so from my perspective kind of you know the first step is you take the document and you embed it right so you went from words into a multi into dots in multi-dimensional space right so I mean let's let's for a second imagine it's two- dimensional although it's multiple and so there's like kind of the words that the similar right are you know close to into the space the words that are far now you have a next layer

which transforms this words right to kind of give them more context uh and so this you know think of it as rotation in the space and then you have a tension which is you know you're trying to kind of given the the current word you know try to pull in the context of the words around it to give to give it more semantic meaning and so that's another transformation right so like in a way you take kind of set of words right and then you kind of keep transforming them uh and so it it what it learns is this transformation function which in a way is a program it's a program that is trying to transform the words into a level which is useful then to predict next word right or and then like later respond to

questions and so kind of is this like a pure sarcastic parot where it's like well pure stochastic parot we had when we were doing just like you know we we were just generating Wikipedia articles for example right you just give it a name and just say generate a Wikipedia article like that's pure like you know there there's it just makes up stuff because like that that name doesn't exist right there's no there's nothing so it just generates something that looks like an article but when we when we starting to look at like okay well how would you answer to this question right it it to be able to do that right it needs to kind of process the information right it it does this kind of Transformations on the on the article and like it's trying to

con contextualize that and and give give the answer so in a way like I think of it as it learns some set of programs that like our world has right so like it's not a complete World model right it clearly has a lot of gaps but it is a kind of set of programs that our like World model has that it can apply to be able to uh to answer well or predict next word for training and and that on itself is really useful right as we see but it's also because it has so many gaps it it it has issues with doing some you know kind of specific things and the more precise it needs to be the less well it does right because it kind of

ends up being like if either the pro the pro the programs are very probabilistic and kind of semantic versus you know if you ask it to like describe the steps of of something uh but at the same time a lot of the things we do is kind of like there's like few thing core things and then everything else you kind of fill in automatically right so that's why it's really good like given that coding like most of most of the coding we do right is actually kind of boiler platey and so and so with like few nudges you can actually get to like a reasonable code uh and that's why I think like things like co-pilots or are in pretty good products in result cool so look turning to

applicative view so now this llms are are pretty amazing and you have some applicative ideas on applying them to the near ecosystem so yeah what what are they and how do you see that unfold yeah I think I think of this kind of across three dimensions so the First Dimension is actually less about AI itself and more about our kind of society and this idea that kind of as more content is generated as there's more kind of information Wars in general misinformation and again the important part to note misinformation is not a ey

problem it's a human problem the it you know we are in crypto space and so Byzantine generals is something that our space is based on and that's literally the you know the Mis citable misinformation um like and so so the idea of like misinformation of of malicious like attack on information is something that exists from you know uh from like early on and so from my perspective the way to kind of start solving that is to to bring the kind of security cryptography and

reputation to a level of um of the content of the of individual pieces of content so right now for example we are you know using websites we have https and so we have we have a some set of security guarantees around accessing specific websites but the content on the website can be coming from anywhere it can be saying anything and there's no way to kind of maintain reputation context comments Etc around it so we need a new set of Standards around that so that you can hover an image and it shows you or a video or a piece of text and it tells you like who published it when it was done if there's any side comments or contexts Etc from reputable sources that

should be attached to it so for that we need blockchain we need you know set of Standards we need browser support and we need kind of Publishers to be supporting this uh and I think that's a really important part for our society generally because otherwise we're going to be living in a world of kind of you know all the content is like you never know what if it's true or not right and it's constantly like um kind of manipulation around that now kind of the second fillar for me is I call it kind of decentralized AGI right so if we assume you know this models are getting more powerful more intelligent uh what you definitely don't want is a single company or you know two

or three companies deciding what's right and wrong for this models to do you don't want the like them to decide what you're allowed to do and what you're not allowed to do is models it's also like it's the same thing that happened with social networks like being a kind of moral police for the world just doesn't work the world is very multi-dimensional something that's legal in Amsterdam is completely legal in a lot of other countries and the other way around and so like you know what moral is is even more complicated and so it's really important to have community be governing kind of the uh alignment safety as well as kind of the you know instruction data sets uh

that this models are trained on and as well as like being able to validate that the model you run is actually the model uh that you wanted to run right so right now if you call you know gbt API or Google API you get a response you have no idea which that could produce that response you have no guarantees that it was the model that you uh wanted to run and actually sometimes it's not because they trying to optimize costs and so uh like how do you actually have those guarantees and especially for something that's Mission critical right like like if I'm doing trading on this if I'm doing Health Care like uh any kind of business decisions right you want to

make sure to you know you're accessing the model that you have predictable parameters and outputs and so for that we need decentralized inference we need kind of model Marketplace we need kind of uh Community data crowd sourcing and data management uh governance and so kind of the whole stack of tooling that really manages this and then you know on top of this you'll be able to to kind of interact with it in the hopeful like I think the other way is like making sure it's privacy preserved and so that when you interact with it you have it so there's a lot of work to be done there's a lot of like there's a bunch of startups doing decentralized inference there is still privacy Gap I think that people are researching but it's still

pretty far um there's some data marketplaces there's some other kind of pieces but it's not really I would say like combined into like a product story yet but I think like that's a really important for like Humanity period because otherwise you know like tomorrow you go to your favorite uh Mo you know AI model and it says like oh you banned or you know you use the incorrect word and so now or something right uh so all all the usual stuff we've seen before and then finally I actually think the the flip side of this is local models right because although like this big models

they have the World Knowledge they have maybe access to lots and lots of context uh but actually what you want most of the time is a model that knows everything about you but you don't want all this data to go anywhere else right you want it to live with you on your machine on your um you know your private encrypted data store and you want a model that's able to access that so you want a local model that is personalized for you you control it it's not affected and manipulated in any way by you know advertisement Giants and so it's actually on your side and is just responding kind of the way you would like to not the way you know uh tied once you or whatever and so I that is a

really important side of kind of as well and so we actually been uh playing around with like Edge intelligence and uh did a couple events and been kind of talking with some projects um around this space and it's like it's actually it's less web 3 like in those sense of blockchain but it's more web 3 in the sense of principles right it's user owned AI it's you know controlling your own data it's like all of those values that we talk about and I think I think that and kind of the web 3 of custody will be converging more kind of in the in in on the principle side right maybe and like on technology side as well and this is kind of the area I'm I'm most excited and working on right

now so in practice how how are you like approaching this are there like teams you are funding or is like there AI team in year or how how can we imagine this yeah so we've been working with some AI teams we actually just had a neon uh about a month ago and we had an AI track there with some projects presenting that we already working with uh as well as uh kind of I'm working as like adviser with few projects um kind of more closely and uh we do have I would say like AI efforts more on also just automating our own operations like so the other side of this is I think kind of the ecosystem

itself should become AI enabled and over time AI Ran So like ideally my you know my job and uh kind of the job of coordinating the ecosystem should be done by Ai and by the way the AI is a kind of like this approach actually solved the core problem of humanity and of resource coordination the core problem of humanity is principal agent problem is that when we want somebody to to to do stuff on our behalf like we select you know uh in elections or we hire someone to manage our money or something else they have their own needs and and they have their own wants and so their decisions are usually not fully

aligned with us who hired them so that's called principal agent problem and so AI actually being the agent that behaves on our behalf acts on our behalf is the way to solve that and if you scale it up to kind of governance level right like actually having AI being the actor that uh you know makes decisions based on what the population wants is a way to solve a lot of the current challenges was you know when you like someone they did do stupid things right or not things that they promis to do kind of that's a way to like really address it and so there's a really interesting kind of future of governance there but like we can start applying it now in this decentralized ecosystems because they're already fully digital they already have

kind of like all the actions are on chain right so you can have traceability you can have like V power Etc if something goes wrong and so I'm really excited about also that side of the um applying AI in in web three space and obviously you need that whole AI gen like decentralized stack to do that but we are kind of starting to do it from bottom up on on our side just in foundation for example like hey what are things we can automate what are things that we can like start leveraging this technology for as well as maybe build some of the tooling for developers to build kind of AI enabl things in in in the space we also have yeah like bunch of projects that are kind of experimenting with this across different

uh areas yeah that's super awesome I also saw actually your co-founder like the Alex working directly on like smarter llms can you maybe also like what what's that about is that related to ni or is it like some sort totally different thing or what can you share about that yeah so I mean it's it's a steals project right now so I'll I'll not go into too detail maybe you'll have him you know in in at some point to go more in depth into it but yeah I mean it we kind of so I'm advisor there and we working kind of I would say side by side but yeah he's focusing more on the lower level and like kind of preparing for the future of of this as

well yeah I think um I guess maybe you you're mentioning right like AI sort of also like making our life easier in the sense of operationally in the organizations but also I guess yeah in wi society and I guess that's always been like a huge focus of near so um yeah we wanted to sort of dive also in that side of near where um basically you're branded now in many places like as the blockchain operating system and I think yeah one of the core features about that is like sort of the the ux focus of news so maybe um yeah can you explain to us how year has sort of approached um yeah basically usability

for for developers and users on in in blockchain systems and and what your currency doing there for sure yeah so I mean this was our vision from the start because when we started ourselves kind of diving into the blockchain and again this 2018 so things were different uh you know you needed to install Mist for the um and so the I mean the experience was pretty like painful and and and it's also it was built on top of kind of a very different set of Primitives I would say like conceptual Primitives that than what normally people both users and developer expect right so you know you need like to understand the zerox

wallets you need a seat phrase you need to like kind of pay gas you need to like have do all those things which are like strange uh when you you know when you're just starting and and what we've tried to do from the start is like how do we design kind of still like a blockchain that is secure that it has all all the same properties that we all want um but is able to kind of hide a lot of this complexity uh ideally most of it and make you know blockchain kind of abstracted out such that developers when they build applications can just build like as close to normal web to experience but

using the benefits of web 3 using the kind of all of the value and then also enabling users to have like more compatibility right more ownership kind of being able to interact with multiple kind of applications and and uh has this like transportability of data and so the near itself right kind of was designed with this so we've like our accounts for example you know the account obstru ction part of the accounts have been designed from scr from the start on the protocol level uh there's like a bunch of kind of differences that uh we've done including that account themselves are you know just a username uh that

follows kind of the main name structure we have lots of different keys with different permissions which allow us to have like multiple devices securely it allows to delegate uh access it allows to like applicate the front end of application to have a session key for example to transact uh for a specific set of uh kind of interaction so kind of all of this functionality comes in by default and then uh on the developer side the choices we made are around first of all choosing web assembly which at this point is like seems that everybody's kind of agrees on uh but um pretty much it's like it's an engine

that runs in all the browsers it's it's something that uh you know is like on billions of devices at this point it's supported by you know large network of uh kind of developers it runs an edge it you know it supports lots of languages you can run a lot of uh software in it and so uh so we kind of picked that and made it really easy to build like in a way from a developer perspective what when you write near smart contract it's really just a service which has message like messages in and out and you have a kind of local key value database which is pretty much like the limits there are so big that like I don't think anybody

ever hits them like you can you I think we have contracts that have like 4 gigabytes of storage in their uh in their database right um so you can build like massive massive contract specifically you can build Aza chains as a smart contract on near so we have Aurora which is an evm as a smart contract just like taking you know the evm that usually run people a separate chain just put it a smart contract they're their database is where all the state of the uh of the storage right you can do the same with Bitcoin I've been suggesting somebody to like Fork Bitcoin and put it on there make it ultrasound money um um we have JavaScript running as well so you can

run JavaScript smart contracts you can potentially do Python and other stuff so like it kind of enables the developer experience across the board and since then we kind of following the same Principle as like okay well now that you can build anything on Smart contract side what's the next next part well actually you want to get the data out of this um out of the blockchain and blockchain are not optimized for reading data they are kind of we' trend to optimize them for writing and kind of maintaining security and so for reading data you want a completely different data structure and so that hence there's like this principle of indexing and um kind of in the way of chain computation and so so we've been building indexing

framework and that actually culminated in what we call query API which is a service that indexes that you can like write a smart contract that describes the indexing of data that executes offchain so in a way it's like a offchain computation framework uh that allows you to store output of that computation in kind of SQL databases that then you can query and finally well okay now you have back end and middleware now you need a front end right and again it seems weird that we are like oh you build everything decentralized but now run a server on a specific domain that you will need to maintain it's like okay well that kind of violates the whole part point of what we're doing so so we created this uh

kind of decentralized front ends framework that allows to store the front end code itself on chain so again the smart contracts code on chain the middleware code on chain the front end code on chain and now anyone any kind of we call them gateways can render this code on the user side right so we have a desktop app we can have a mobile app and we have obviously VB apps that can load that from the blockchain directly into your browser and render it there so there's no kind of middle server that's needed uh to render you you don't need to have a domain you can obviously L if you want to and so you can just you know launch your launch kind of part of your lab app as as this decentralized front

component and now it will live forever on blockchain right by side by side with your smart contracts have the same upgradeability have security cryptographic security who has it have versioning so if I as a user don't hate a new version I can go to version before and so like all the same properties we really like about smart contracts we now get for front ends so so all of that is really enables like a full stack decentralized development that is you know familiar with to normal developers it's react JavaScript components it's JavaScript for middleware indexing it's JavaScript rust C++ and like other languages for smart contracts so you have like a full stack decentralization that you can have and interestingly as

we were building the front ends we realized actually the front ends can work with any blockchain and so uh we kind of just turned on all avms and some other uh blockchains and people start building all the evm fronts as well so we have a Unis swap for example for linia the the kind of official Unis swab front end is served out of the decentralized front end right because by the way it also doesn't charge extra fees and we have like Partnerships with others zvm mantle Etc and so the idea is like actually as you start looking from that lens from a user lens right as a user I don't really care which blockchain the apps is on I just want to use it and like if you go to you know some like you know some of this uh gateways where

you can access this front ends you can just go and search for whatever app you want click on it and start using it that that's how it should be and so uh and this is kind of where we get to this concept I started with which is like hey we want to abstract the blockchain for users and developers we getting back to it with kind of this now that we have this full stack decentralization we're like actually this works for all blockchains for all chains for rollups for whatever uh because you can actually abstract out all that on the front inside and make it really easy for people to interact with it and so hence we kind of started going backwards now with some of the other launches we had right allowing pretty much as a kind of

how do we make it really easy now for one experience to to unite all of the blockchains and kind of we call the chain abstraction principle and so this goes into like GA and and some other things we yeah we can discuss so so India is it is it correct to imagine um so when you talk of like this indexer service or the service of hosting a front end is it correct to imagine it as the indexing logic or the front end logic is stored on the Chain but then there is some kind of off offchain actor that is actually taking that that um taking that logic or and the data and actually serving it much as

a traditional server and somehow the chain is guaranteeing that this server's work is correct and it is compensated is it is it correct to imagine it like that yeah pretty much so the idea is I mean similar to maybe blockchain validator nodes as well right there's a kind of a logic that is conceptual and then all the validators are doing that job um and like you can always have you know more validators less validators it's kind of independent of that similarly yes the indexing logic and the front end kind of source code itself is stored on chain and so any server can

run off and kind of create the same you know outcome from this right again similar to rpcs for example RPC server right is serving your data but it's uh uh you know anybody can run an RPC server and get the same results so like it's it's part of protocol in a way uh it becomes part of protocol and so similar thing we're try to do for front ends and middleware indexing as well so maybe one way to think about this is that so on on on ethereum like if you look at ethereum um there's a basically a blockchain and then there are separate protocols like the ens for naming your blockchain address to a human readable name there is the graph

which kind of like indexes a smart contract and kind of presents historical data about the transactions and events in the smart contract um and maybe maybe there are other examples that I'm missing so in ethereum like these are like different systems and usually they are competing systems there ens but they want be a competitor to ens the graph and they might be a comparative to the graph but in near near has kind of taken the philosophy that some of some of these things are like are like really key to the ux of a blockchain and therefore they should be supported out of the box by the layer one itself is that is that the philosophy here to extent yeah I

think I think the way to think about it is it's more than just layer wi right like at the end when we are interacting with applications on any of this chains um like there's a whole host of tools and and more importantly standards that we are interacting with right and so like erc20 for example is a standard and it's a standard that kind of came out of the application space but it's now like you cannot imagine a cium without rc20 standard and so what we're doing here is really defining standards for the key Primitives that are just going Beyond just you know token transfers but going to like how to how to define indexing

how to define these entr runs now implementation of those things can like you can have many implementations you can have you know mobile render and web render you can have indexing like you can have you know external Partners who are competing with each other how to implement it uh same same for rpcs right RPC is a standard but then the way it's implemented right can be very different like underneath you maybe like cached everything in database maybe using cloudflare like whatever the architecture you want to use but the standard is there and I think what we've been trying to do is Define a standard and I mean have a reference implementation but for for this more key pieces to make indeed The Experience more aligned and kind of have this like singular Journey for developers and

users that you know is cohesive and yeah like the way you know some of the things like you can have businesses around the standards that are you know very profitable um but like the the core principle for me of decentralization is actually in the standard it's the fact that like if you define a standard it means that you can swap in and swap out any participant and so you're not you don't have this like lockin effect you don't have the effect of you know you go to a bank and you cannot move your money out because it don't allow you to or you know that cannot cancel your Telco provider because like or like POS Telco providers don't even work for you the here we can always have like a competitor that comes in and if they're

more effective and can provide better prices people can switch to it but the stand because the standards is the same and so for me that's kind of the key principle of like web 3 in general and so I think the challenge that I've seen is like not having the standards actually leads to kind of huge fragmentation of experiences and as well like actually Mon Mon monopolies been built because like now that you built all your software towards some API you cannot switch because nobody else provides this and like you need to rewrite half of your codee to do that so how much is kind of an an analogy with the Apple ecosystem versus the Microsoft ecosystem for desktop how much how well does it map so in a sense

when you look at kind of like the the Apple uh the Apple ecosystem it's a company that has kind of maintained control over its kind of like operating system supply chain its way of like delivering music its way of delivering books uh its way of how kind of um applications kind of like appear to the end user um and in the in the beginning I think they also wanted control over the hardware but maybe they have retracted on that now whereas like kind of like Microsoft is one where just like the raw operating system and then applications emerge and if there are standards need it for their interoperability the market kind of like figures it out and from the

outside it feels like okay near is kind of like more going towards that Apple philosophy that we are going to Define all of the standards for for many of the things that are key determinants of the user experience uh whereas other reos systems like Cosmos or ethereum might be more kind of like the Microsoft approach where we are providing like transaction throughput as the center the account model as the center and then kind of a lot of the interoperability between the standards is to the market to figure out how much does that analogy map and how much does doesn't it map I mean the I would say the part that like agree on is we're definitely trying

to focus on user experience right and so with that it's it's important to figure out like what are the touch points that you wouldn't have standards on again like my perspective is for example RPC Json RPC is part of ethereum standard like it's part of kind of the protoc even though it's actually not but like it it for accounts if you try to change it RPC API like you will break everyone and so so we kind of see in a similar way right like if RPC is part of a standard why not some other parts but as I said like you know near for example has like number of contributors that are building things like the actually the VM that's built right now for the decentralized front end is built by

proximity right uh and uh for example you know the query pii kind of other companies can implement the same standard and provide kind of better services so I think the idea here is that by defining the standard we kind of actually opening up the market for people to fill in like with better products uh in this and again like it's pretty early still so like a lot of stuff we still build like reference implementations but similar as aium by defining a standard for protocol it opened up a place for all of the clients to be implemented right like that's kind of the idea is like you you you define a standard and then you open it up so that uh others can contribute to it in the

same way versus competing on apis and competing on like kind of uh you know in a way marketing what's happening right now in in uh and like token price what's happening in etherium for some of this like infrastructure tooling right uh it's like can can we get a bigger air drop by using a product versus like hey this is a standard everybody will be using this standard and so now what's the best product people can build for the standard so I think like that's kind of the difference I don't think it's as applicable to like this you know big commercial for-profit companies versus like this is an ecosystem or a building um and really defining more kind of this

I would say like layers of the stack going back a bit to like this what you said about the switching cost from your Tel I guess like related here I guess one big thing in blockchain is generally like bridging or like if you want to switch the ecosystem you have to like go to some other chain and then like move the liquidity there which can be like cumbersome and you did mention the chain abstraction for a second there and I saw on your Twitter a bunch also like this concept you have like of account aggregation uh that you teased so maybe you can yeah can you talk tell us a bit about like what what are you doing there or how are you like sort of solving this

interoperability problem in in in the blockchain space for sure yeah so that that's a very important topic so although we have started Building Bridges I think so the our Rainbow Bridge been built from 2019 so I think we started building you know kind of in line with ABC uh uh kind of timing and we've been we've been running since um I guess like beginning of 21 and at the same time like bridges are really bad as a concept because they created a Honeypot for security they are the place to siphon off assets uh and like there's you know if there's any attack on the

protocol itself bridge is kind of how you exit uh and and they like the just the amount of failure modes between different blockchains is pretty like it's pretty big right but between multiple blockchains it's like insane like you know chain stopped blocks didn't publish like all those things you need to like as a developer now you need to handle and then on application side okay here's you know the fungible tokens transfers is maybe reasonable but as soon as you add any logic right be that you know rebasing or be it nft now when you bridge it you lose all of the logic on the other side and so so the concept I've been kind of exploring for a while now I was calling it originally uh

remote accounts but we we kind of um reframe it as account aggregation this idea that ideally you want to have one account and there's mapped accounts to this on other chains so imagine you know you have my root. near account on near and then I have an address on ethereum I have an address on bitcoin I have an address on salana which I control with this account and so now if I want buy a salana nft right right now I would need to like set up a new wallet you know Bridge some stuff to salana buy the nft and then I like I don't know and then like go and look at it you know from time to time because I'm mostly sitting on here or you can you have this salana

address that's linked to your uh to your new account you pretty much through this buy an nft for this address and we can talk how that works and now you have the front end that actually shows you everything you own across all of the chains from all of this addresses and the way the way mentally to think about it is when you go to binance or coinbase and you sign up with your binance or coinbase account you have addresses on all chains right and I mean there they deposit addresses usually but imagine those addresses were actually normal addresses you can use apps and buy nfts and tokens Etc wiiz so that and but your account is your you know coinbase account and so that's kind of where your

you know like ownership is and so that's what we're trying like Web building we're going to be launching end of first quarter is this concept of account aggregation that now allows together with decentralized front ends allows to actually collapse the kind of this whole you know multiple chains switching networks you know bridging all this into a very simple experience of you get an account you know you deposit some funds into it and now you can transact across all blockchain uh across all of their apps and it kind of will get executed on on your behalf on those chains and you have this addresses but it's all self custodial and all kind of hidden from you you

don't need to think about gas fees on those chains Etc so that's kind of the experience we're going after and again this is just an extension of what we've been building was near by trying to abstract out the near blockchain we're just like okay well we can actually do that the same thing for everyone and really provide like a unique and valuable experience because you know anything multichain you want to build near will be actually the place to build it because you will be able to transact across all of the chains without having to bridge without having this like complexity uh you want to build for example Bitcoin defi well on near you know every near account or smart contract will have a Bitcoin address you can deposit to it can start you know doing stuff right and so that's kind of

conceptually what we uh really bring into Market Market with this and like kind of finishing our I would say Arc of chain abstraction that we started with doing near in the first place so on a on a high level India like like this idea is is in the cosmos ecosystem there's a chain called Neutron and because the cosmos ecosystem has IBC so Cosmos chains can bridge to each other in quite a good way neutron has the idea that uh in Cosmos you have the IDE of delegated account control which is like on one chain you have an address and that can control many other puppet addresses on other chains and neutron is trying to build that kind of

that that Puppet Master chain where like you will have your central account and you will control other addresses on a lot of chains over IBC through Neutron it feels similar but the reason it works in the cosmos ecosystem is you assume IBC that there's a secure bridging solution underneath available for this to work in Neutron my I almost start to think that okay the only way like this can work for near and Solana for example having like a address on near that can control a puppet address on Solana you need a secure bridge between near and Solana is it not so the bridging problem solving the bridging problem seems like a

prerequisite to this yeah so we're trying to go away from bridging almost completely I mean there will be some places where you still need Bridges but um so let let let's look at Bitcoin as just a a way more clean example right with Bitcoin you cannot have a smart contract Bridge because well Bitcoin don't have Smart contracts and so the only thing you can do is to own addresses and so the core idea here and it's conceptually is the same as yeah what Neutron is doing but the core idea is different the core idea is we make NE near Network itself be able to sign transactions for other blockchains and so near Network becomes uh in the way custodian of all of this address mapped

addresses on all other chains and you as a near user telling Network right be that through smart contract or or or user user interaction to sign a transaction on bitcoin to send some Bitcoins from your remote address from your delegated address to some other address right and so because of this like you don't need to actually Bridge Bitcoin to near to do anything right you you just literally the Bitcoins live on bitcoin Network the O you know op coins live on optimism the you know salon and nfts will live on salon nft on salana and I just control all that uh by just sending transactions there but as a user like I just interact with near and I can

I pay near gas fee which is very small I say like do this you know I attach whatever also you know if I need to buy something Etc on near and then we have kind of intent Rel layers that actually execute stuff like you know the transaction gets signed by near Network and then inet reler you know send that transaction on your behalf on the other and so there's no actual like bridging there's no kind of security um kind of issue where like if this bridge gets broken or whatever or that Network gets forked Etc like none of that exists and because new there's also like a very interesting and kind of a little bit crazy thing because new accounts are are actually tradable so you can actually list near account as nft and somebody

can buy it and get access to it because you can rotate keys on near what this allows to do is you can have lots of assets across all kinds of networks and then you can list that as a bundle on near as like you want to sell some BR c20s some Salon nfts some ethereum nfts and some I don't know op coins and GMX at the same time you can list all that as a bundle under one near account and then somebody can buy all that with one transaction on near paying near transaction fee and within 1 second uh block time so you don't need to wait for Bitcoin transfer you don't need to wait for all of this you can do it on one so you can actually start bundling all of

this things and trading kind of across all chains on near very easily without actually sending transactions or bridging anything anywhere else and that's kind of the the shift that we're trying to do I call it un bridging that we like you have the account kind of ownership that's maintained indeed but it's maintained by very specific security parameters that are near parameters and then if if the let's say salana Network fails for whatever reason there's no Bridge problems right that would you know uh rise from from this like because you own stuff on on salana so whatever salana has to deal with right like whenever it recovers Etc like you will get it back but like it's it's

kind of the same like you know you have this kind of relationship with that network but not like there's no bridge that you need to deal with and kind of think of as like an intermediate you know complexity so that's the idea it's like you know again we're going to be rolling out more documentation uh it's like we have a deset version coming out for people to hack on uh in in kind of January and so we we actually invite people to start building because again like and multi-chain experiences like you'll be able to build with this way easier uh because you don't need to think about all of the complexity of like oh this message didn't deliver the network is like paused you know like something crashed because of inscriptions like you don't need to deal

with any of that right it's like you can literally sell your your you know Network failed you can sell the account that that has Assets in failed Network right to somebody else for example if they want to take that risk right so like you can do that without having that Network life uh even so so that's kind of the the the level of experience we want by up in like this leads to fully abstracting the blockchains right because now from a user interface I just go I use an app and like I just see that I'm using my for example near account and um it doesn't really matter for me that that was a salana like nft that I bought right I just see it in my portfolio View and like you know for that we need like indexing of salana and all the other chains data so the same

stack there we need decentralized front ends that kind of aggregate all this and so kind of that that's like how we package all the stack in to uh by abstracting the blockchain so quick quick nerd question which is so okay so Nia is like this is awesome first of all I mean near becoming like a distributed custodian essentially imagine it as like coinbase but distributed and the distributed custodian can have hot wallets basically on all of the other uh all of the other chains but as an engineer my my my questions really starts to be in in Bitcoin you have like a single sing account or a multi- account that's what

Bitcoin provides available right like it it assumes that there is like maybe like one private key and then one public key and there's a signature to that public key whereas neara as a distributed network has lots of validators so how do what fancy cryptography makes this makes this work yeah so it's called chain signature and so this is a threshold signature with uh where the Val as vales rotate you can maintain actually the same set of public keys so even though you rotate and like have different parts of the private key uh being rotated they all like when they sign tal signature you get the same public key and I mean you

can have derivations obviously so you can have like as many public Keys as possible but they all deterministic wasin the whole blockchain so so that's a pretty cool technology um and yeah like it's kind of reasonably new some of the folks from thein been pioneering that and uh yeah we kind of leveraging that as a way to have near to become this decentralized kind of custodian right I think maybe also Axel Works a little bit like that or am I I I think but anyway one question that I had like in this scenario where you have the B Prov nft on salana you need the liquidity right

on Solana as a user so maybe I have like funds on near but I don't have on Solana like is there some system that you're thinking of to to balance that out without bridging or yeah exactly yeah so we so this is where we call them intent through layers or I mean we we're still shopping the name but so this is the idea that on near we have this um well we have this principle of trial account so this is idea where I can send you right now a link you click on it and you'll have some near in it so you can do stuff on near but you cannot withdraw that near so we actually like we kind of like what what it will do is like actually send you a one time us private key which when you click it actually

create a new private key in your in on your browser switch that private key but that private key is limited access to that account so you can transact but you cannot withdraw funds and so that kind of concept applied now to other uh of chains in a way allow what it allows to do is we can have other parties to to fund their account uh to execute things right they can put some salana tokens to pay for gas or for nfts but you cannot withdraw that by sending a like direct transaction to withdraw salana so so what this allows them to do is you can pay the somebody on near with near token and then they will put salana

tokens there and then execute your transaction and kind of by doing that right we kind of have pretty much a way to that's why I say it's intent right you say like my intent is to buy some salana thing but I don't have salana token like here's bunch of near tokens execute that there and so and you know now you need somebody who has liquidity on all the chains to execute the stuff but that's like having a thir parties doing that is way easier right than to have like whole bridging and automatic uh execution so this is like yeah really like um some sort of fee attached to it and the relayer can grab it it's not like a blockchain network or anything yeah yeah exactly yeah there like a surf body like

you know like a market maker whatever whoever it is yeah yeah any Market maker or any like a like bot Arbitrage Bots can do this kind of stuff pretty much and and and they also as doing that they'll just relay the transaction as well so like you don't need to actually also send like submit transaction because like the validator is only sign transaction right now somebody needs to like actually ship it to peer-to-peer Network so they they will do that as well yeah that's pretty awesome yeah like looking forward to reading more about it once the the more documentation is there and stuff but yeah thanks for for sharing it here and um yeah I guess further in the near Journey like we didn't actually talk about much about the chain itself right I think um you

were basically one of the first if not the first like sort of sharded blockchains and um and been like staying with that sort of narrative while I think yeah others have pivoted from that um so yeah can you tell us a bit like how has the like near sharding developed or what what is sharding actually again for people that forgot about it uh and you know where where where is it going yeah so as I mentioned right my co-founder Alex he was you know building sh database I mean I'm coming from Google where everything is ched just like you cannot have you know billion users and put them into one database

that just doesn't work and so and like on my computer and so for us it was like you know kind of pretty obvious that you need charting and so sharting I mean at at the core the idea is like you as you process you know as you store more data as you process more transactions you need multiple machines doing work in parallel and you want this machines to be kind of doing similar work right and like Distributing load and ideally as more load comes in you actually increase number of computers right so this is how all of the web 2 Giants work you know again imagine your Gmail right or imagine uh Facebook right there's like a database underneath which you know is

shed it has hundreds or thousands of servers that store for example user data and uh you know when you're user requesting it routes you to the server where you're user data is and achieves it and then when you need to update something or process you know transaction it kind of routes a transaction there so that's kind of the core concept and like you know again logically you cannot have like you cannot have billions of users using the same like one server right and this is what's currently happening where for non- sharted systems it means like they relying on pretty much one server replicated but one server nevertheless to process everything that happen on their chain and so so for us it was kind

of you know pretty obvious that we need to do this now blockchain adds extra complexity compared to web2 where you have all of the know security that you need to deal with and so um we've been kind of obviously iterating on on a design kind of within this conceptual thing and so we introduced Nightshade um back in 2019 which was our Shing design where in a way every single near contract or account is actually a separate chain and we just bundle them in such a way such that as users and developers you don't know about it right uh and so we kind of bundle them to the number of machines that you know

parallel processing machines at a time you need to and so again this is very similar how web 2 Works where you know every like user account is in a way independent and they store and they can be like moved around between different databases like different computers uh in the database and so so this kind of allows to abstract out the complexity of the sharding from the user right as a user if you go to near blockchain you will not see shards we don't actually show them like you need to go to RPC and like query the block headers and stuff like this um now the thing that we in 19 were planning to do was uh for security was based on challenges and that's proved to be very challenging and this

is across the whole Space right we've seen like a number number of other chains actually struggling with implementing challenges and so kind of earlier this year we ended up uh kind of doing research and and refocusing on instead doing stateless validation so what this means is now when block is produced uh block actually contains all of the state that that uh execute the transactions touched and that information is being sent around to everybody else what this means is that other validators don't need to have state of The Shard they can just validate the block on its own and it means we can have you know

hundreds and thousands of validators validating every Shard it can be completely random they don't need to be assigned to specific Shard at any time and uh this also means we can you know have now a lot more kind of nodes and validators in the network kind of proving the whole system now kind of on a low level what it what near is is really a decentralized shared sequencer that then send out the data availability of this transactions across the whole chain we use rasia coding and then we have this execution which now is stateless execution which then is being proven by number of other vals and and settled right so we kind of package the

whole what now is modular framework actually in one you know pipeline way on top of the same set of validators right kind of just being rotated constantly across the network and so that's uh you know at the core what near is and so we actually uh going to be launching the new uh testing Network for stess validation uh to kind of as a part of our phase two launch and so this is kind of finalizes like core road map of of sharding that we've outlined since since 2019 and uh this should be coming kind of January February and we're going to

have you know the full main net launch probably in April and this is the idea that actually kind of conceptually if people read like vitalics endgame this is in the way that structure you have block producers who are sharded who are kind of can you know we can keep adding more block producers in parallel so you can keep scaling the network uh we're also moving the uh kind of somewhat in because of this block producers now don't need to rotate as much we're actually moving the whole state into memory which gives us about 10x Improvement on each shards uh kind of transaction processing uh and so like each Shard

gets 10x and then you can have more shards and so then they kind of you know they do raor coding data availability and then they do processing create this uh blocks with State Witnesses send them out and then you have large network of validators who who don't need to be this large who can just validate these blocks without having the full state of the chain so that that's kind of the you know in a way finalizing our road map but also very much at end game it kind of bundles a lot of the current like rollup Concepts and you know sells a base concept that ethereum is talking about into one product and then uh we announced we we

working on zik vasm with polygon because this kind of just sending out State witness with the block is actually uh a lot of bandwidth and what ZK wasm allows us to do is actually to prove the whole block execution with State witness on the Block producer directly and so now instead of sending like potentially you know megabyte of data we can just send you know whatever 10 kilobyte proof uh out and everybody else can just validate that without re-executing all the same transactions so that is kind of actually you know final end game I mean there's like few more pieces that uh to complete the picture but that is the structure

that we we think is pretty much final kind of architecture that uh you know you have Tor resistant uh shared sharted sequencer right so uh and you can you know you have like all the data availability underneath to Pro provide you so that and like we do data availability first before execution because that means all the other indexers and other pieces of infrastructure can start executing in parallel and so you don't have latency on user interfaces before the kind of finalization of the execution on the validators itself then you have kind of execution non validators send out witness and now uh you know large network of validators can validate it

and prove it without needing to have state rotated and all kind of having like you know potentially state is like 50 gabt for example so they don't need to like have that 50 gigabytes on them they just receive whatever relevant for the transactions that being processed and so that's kind of the yeah I mean it's it's a little bit complicated as a as a scheme but but like really it's powering this again like the kind of the endgame structure uh that uh people been talking about at the same time it's it is like kind of that modularity just like reusing the same set of servers right to to ensure kind of uh throughput and uh Laten low latency yeah like that's that's like an

episode on its own to be honest to dict through that is it correct to think that like the stateless validation requires ZK wasm as a primitive so no because you you can do status validation without ZK okay so what you do is you execute transactions you record which pieces of State you touched and then you just send those pieces of state with with Witnesses right with uh kind of uh proof that it's part of the state together with transactions and so we're actually launching that first while in parallel kind of working on zkm and so zkm what it allows to do though is just compress all of these and execution of and validation of this into just a proof

right so in a way like ziki vasm will prove the execution of this blob pretty much State plus transactions into just a fix size proof but it but so it's more of an optimiz zigm from this perspective is optimization and it's obviously like way better for like longer term you know storage but it's not a prerequisite I mean maybe I I'll try to present my simple imagination of like of this system so the way I imagine it is like if you imagine I'm a I'm a valid dat i an accountant right automated accountant essentially in near I have the capability I'm assigned somehow like

some piece of work and and somehow my work is also rotating right like it's not part there's a massive ler massive Ledger massive State and I assigned he go and make some changes to this part of of the state so I can I can basically go to that part of the state there are a bunch of transaction associated with it I execute the transactions and first I can I make the data available hey these are the transactions I am I'm going to execute I make the execution I update the state and today I somehow provide some witnesses so that for the other accountants I can sort of provide

a proof hey I did my job correctly here's proof and they don't need to download my part of the state to verify my work and this ZK proof will make that even easier so the state imagine as massive massive tree or something I can I can modify some branches of the tree and I create a proof and then I that proof is Witnesses today ZK wasm tomorrow and I can send that thing to others they don't actually need to have my part of the tree in order to verify my work and um and then there's a separate system that says okay in modifying this part of the tree what are the transactions I did some somebody

duplicates duplicates that work and because because I can modify a part of the trick quite independently and there are many like me um so there are many accountants like me all of these accountants are kind of modifying like different parts of the tree uh in parallel and like that is fundament ly why the system is able to scale yeah very well put so you have partnership with I da why do you need a partnership with igda in that case yeah so so this kind maybe yeah CH changing gears right so so this is like near itself this is near itself right like it has no interaction

with other things but yeah yeah so so and again near itself right now is you know top use blockchain by number of addresses for example uh you know daily active monthly active weekly active and so like the itself has like a bunch of utility and and value already but again we kind of when we frame this like chain obstruction thesis right what it means is that for the developers and users on top we're trying to provide as smooth experience across using other chains as well and this is where we kind of looked around and like oh near already had has data availability built in uh like that's just part of our

protocol and so we have you know bunch of layer twos that we can plug in into this to uh kind of hook in into the rest of our systems right and so that's where we kind of you know started uh and in like kind of pretty much provided a way to hook in up stack cdk uh uh Stark Nets kind of Stack how do you publish your data on near now if you just publish data on near it's useful it you know it's obviously very cheap it's you know way cheap like cheaper than uh pretty much everything else in the market and because near is shed you actually have more capacity than anything else can that can take

your data already and we're going to add more shorts but it's not as useful because you cannot route messages between um between kind of smart contracts on rollups between each other and near near contracts and so that's where we had a partnership with igen layer not igen da to uh help us actually um do the work for this layer twos to get get to executed State and the outgoing messages such that the uh applications that want to R messages faster within one or two second they can actually do that through the near Network so Ian layer Val Val ators will

execute this rollup given the data published on near they'll execute it and they'll have a new state route for the rollup itself now so think of it it's it'll be extra accountants ethereum accountants who will be actually looking at the rollups um and updating State TR there but then publishing back to the near like telling it to a near accountants as well and so now near accountants and AUM accountants together know the state of both near and all of the rollups that are plugged into the system and so now you can route messages between rollup contracts and near contracts and you know back and forth and so this allows us to kind of again like align more the the the space of of

the uh the space and so again for chain abstraction for account aggregation it means we can do things way faster between all of the rollups that that fit into the system so that's kind of how like the A+ I layer kind of provide this fast finality and then you know there's other kind of tooling that we you know plug in on top with decentralized front ends to really kind of abstract it from a user but like we need that kind of alignment again near in the way each account like each each element of that tree is a separate rollup right and we kind of we have a system for managing them and so we kind of trying to fit the other rollups into the same system and you know obviously we need to like plug

in some pieces to to make it work under the same security parameters that roll up expect right which is ethereum security hence dag in layer and then da is kind of way to get this data you know into the system as well and and provide some guarantees there um hard to unpack but but like logically it's like yeah imagine is exactly that it's imagine near as this massive tree and then there are like L lots of accountant in near itself there's one group of accountants and then accountants can kind of modify parts of the tree independent of each other they can send proofs about their modification so that other other accountants can trust their work and

then kind of like this I L partnership is in some way saying that there CDM accountants yeah yeah it's like near near says we have an awesome group of accountants but if you want your own accountants and if you want your own roll up you have created a a separate group of accountants but then your accountants and linear accountants we we sort of need to interface in some way so that um so that the work your accountant's date can be duplicated on near and the other way around and Via this D duplication we can somehow achieve like trustless interactions between ethereum

rollups and near something like that right yeah pretty much like I would say the so rollups is pretty much I want my own accountant right that runs everything but then I I trust aium accountants to revalidate everything and and finalize it right so like etherum accountants are are F the final final my accountant is the one who can do quickly right he sits right by my side and so what we say here is near accountants can you know can provide a bunch of value by you know either connecting your accountant to the other gu's accountant right so you can connect together or to our

applications but you we still need ethereum accountants because the finality of the rollups is on ethereum right and so that's why we have I layer pretty much to lend us their ethereum accountants uh to kind of use the Le the you know as a rollup publishes a ledger right from their account and first like we have theum you know account St layer to like validate everything quickly right before the ful edum finality will happen and so that allows to kind of near accountants and to have like trust into into the execution of what happened on the rollup while El have the way quicker you know time to finality and to

communication of messages for this rups and maintaining the same security as as they have through e CDM so that's kind of like you know it's like rollup near an eum coming all together into like one happy family of accountants I think that's that's a great note to end on right like uh big happy family of accountants um yeah IAD thank you so much for coming on it's been like a massive episode I think um yeah uh I need to like process this and I'm I'm sure our listeners will take some time to process everything too well we can do another one in a few month as we launch all the stuff so yeah totally and yeah we still also have Alex episode about the smarter

llms outstanding so uh lots to do but yeah thanks so much for coming on and and thanks for to our listeners we'll have like one and a half hours of of content here thanks guys