Crypto's Answer to Centralized AI Monopolies | Anand & Niraj

Transcript

let's say that you wanted to take out 3x levered exposure to Apple with Dia collateral and then at at some price point you should stop out and close out the position to you know have some safety or something around it normally to do that in defi it would take like 10 different smart contracts and clicking a bunch of interfaces but I said that to you in one sentence and I I think the power is being able to take that one sentence and convert it into some sort of you know form of intent and you there's a bunch of companies building on the intent side and then being able to now interact with blockchains in a way that's actually usable by Regular People and not just people that are very in it scary stat for you the odds of falling

victim to online crimes are one in four AA provides digital security protection to keep your personal information passwords online activity and Technology safe from online threats for Empire listeners Aura is offering 14 days free Plus up to 55% off an Ora subscription when you visit AA a.com blockworks terms and conditions apply cite for details you'll hear more about Aura later in the show this episode is brought to you by Kinto the safety first layer 2 that features user owned kyc and Native account abstraction to solve the two biggest roadblocks to mainstream adoption One Security and two user experience their founder Ramone

sent me the onboarding flow it's engine gen. Kinto doxyz I would highly recommend becoming a founding member of their launch program you'll hear more about Kinto later in the show are you tired of high gas fees I'm excited to let you know about scale a zero gas fee modular blockchain that's become a perfect fit for gaming and AI apps because of their instant finality and lack of me explore the scale ecosystem today at scale dospace ecosystem and stay up to date with the gasless blockchain on X scale Network that's scale Network big thanks to scale for sponsoring Empire all right everyone welcome back

to Empire we've got a ND uh managing partner canonical Venture partner light speed Ventures we also have NJ who spent five or six years as a poly chain investing alongside Olaf and crew and then uh is now co-founder ritual so Naraj an OD welcome to the show guys thanks for having us thank you yeah um so I think the episode the episode that I want to have here is something along the lines of there's all this Ai and crypto stuff going on we had Casey cruso on the podcast back in December it's five months later um I'm seeing Martin scy post about IET and I'm seeing AOS and render ripping and I'm seeing like I'm just seeing a lot on the timeline

and I haven't really fully caught up and I want you guys to catch me up so maybe the best place to start is Naraj I'll pick on you for this question of just like why now why is all of this Ai and crypto obviously there was the chat gbt moment that kind of unlocked the like mainstream AI moment but like why is this all coming together right now the really the big reason for AI and crypto coming together at at this stage is is a couple of big reasons and many of the re reasons are what informed me to to get into the space more more fully as a builder um so if we separate out the two things we have ai and we have crypto if we zoom out and think about

why ai ai like very similarly to crypto has gone through these cyclical up and down moments where there's hyper investment and then it seems like it's dead for a few years and then constantly cycling through that albe it an AI a bit more stretched out of a of a time period ai's been around for you know 40 or 50 years whereas crypto is more like 10 or 15 um and so we've had these various Innovations you know starting from the the age of compute um you know even people like Nash were thinking about how we can have you know what you know artificial intelligence inside of computers how can we replicate you know human intelligence and move past it um

I'd say the most recent wave before the current one was in you know the you know 2010 to 2015 era where we started seeing AI being used in things like self-driving cars this is when uh a lot of the the kind of bigger companies started coming out weo and and Uber had their atg program and then we started seeing AI in this in the SAS um part of the world ways to improve the lookup of data and entry and and things like that but I think the big fundamental challenge was that there was no interesting like consumer use case for AI every thing for AI was was in the background you know you refresh your

Instagram feed and a recommendation system is like getting you the best results but you're not viscerally feeling you know artificial intelligence and so fast forward to you know 2017 2018 we start to get newer techniques in AI some I mentioned you've covered on the show before but if not we can go into it a bit later um deep learning um one of the more recent fundamental improvements in you know in the ml world came about we saw the Transformer architecture which is kind of the fundamental building block of the large language model and so those things really brought us to a place where

models are now really really good at doing a lot of things and that combined with the release of trap GPT probably two or three years ago took took this highly capable model that is you know I'd argue is better than humans at most things the vast majority of humans at most things it it beats you know most humans on sats and math competitions and things like that they're highly capable and so open AI bringing chap GPT out into the world showed that hey this is a way that you can use artificial intelligence and really feel the power of what it means to be able to get an

answer to a unique or interesting question very very fast faster than you could with Google or asking someone so with that backdrop in mind something like chat GPT has two to 300 million daily active users which is a really incredible number in the span of two years chp2 is the fastest growing product of all time so that means that there's something very valuable and unique there and I I think AI has really crossed the chasm and in terms of people being being able to use it and and understand it so if we go over to the crypto side we think about AI is great but what are some of the challenges that you know as crypto people we foresee

coming out it's things around privacy you know most of these companies still take advantage of your data being able to actually track how dat you know the data that goes into the models and how how they're being used being able to get you know confidence that a model that you want to use is actually being computed correctly and a whole bunch of other you know other features basically there's this increased centralization that if we don't solve with some other technology like I think crypto crypto being a tool for self- sovereignty you know own your identity own your data on your money will have these great AI systems that are the governance of them

are and ownership of them are controlled by a few companies and and governments which is a which is a bad sign we've seen you know money being taken advantage of when controlled by centralized entities we've seen it in in you know Waymart Germany and Argentina and so many other places we've seen it in Tech platforms things like Facebook and Twitter in the 2010s when they you know ripped away API oxis from all the devs and so we had Bitcoin as a replacement for for money and we had ethereum as a replacement for you know for technology platforms and and I really think we need a decentralized alternative to AI uh and so that's really the a couple of the

underpinnings that you know we've thought about as to why now ai is ready and we have the cryptography uh and and cryptocurrencies that are technologically developed enough to be able to merge these two things together and you we can go into that that more I'm sure later on yeah maybe we can dig so there are features that we can talk about there's agents and um self-owned models and data and verifiability and crypto incentivized AI behaviors um local and peer-to-peer inference there's decentralized gpus I think of these all as things that could be unlocked but then there's this broader like the problem statement that I think we're trying to solve and I

think n you hit the nail on the head um and it makes me think of this the Peter teal quote right from maybe I think he said it five or six years ago where he said crypto is decentralizing AI is centralizing or if you want to frame it more ideologically right crypto is libertarian AI is communist um Anand how do you think about this this like o like this overwhelming problem statement that we are trying to where trying to solve where AI what AI will ultimately do is make the Googles and Amazon and Facebooks of the world a lot more powerful than they are today yeah no you're right I think NJ hit the nail in the head right like this is is um when it comes to um well I'll see two things right one of which is you

know today the state of llms we're looking at what 200,000 years worth of data that's been used to train these llms and you know to piggy back off neog's point the why now is also because we have all this data right like I remember taking a programming class in 1999 which was technically about AI but it was purely about just learning how to code and lisp um and you know that that was we were like yeah AI is here this is 2000 this is when AI is going to happen and you know but when it took us all this data and the ability for us to access this data uh but yes you know now the second thing being that to your point a lot of our human behavior is being monetized whether it's intense it's searches it's our personal

behaviors it's being monetized in ways in which um maybe we didn't foresee right and these have become large monopolies so the real question in front of us is like do we when it comes to something like AI or comes from future generations and this is you know maybe to some extent and there's some chatter about this today that the current state of AI has sort of as toed based on human intelligence but that's maybe the promise looking forward is that it will Leap Frog human intelligence which is sort of like you know the maybe part of the the excitement and the fear at the same time but if if if and when that rather when that leap frogging happens do we want to yield control back to centralized entities U especially if these are tools that we're going to

continue to live and see into perpetuity do we want the governance to be controlled by large entities or do we want to have a sense of ownership around it so Agreed 100% And I I feel like when I first met NJ and you know this was like the why out for him to to to move from what he's doing to what he's doing today was if it's not me if it's not us you know then who else is it going to be and crypto with sort of the backdrop AI sort of the big problem statement and the the repercussions of this is just too large for us to yield control back to the big Power so um yeah in agreement there what is the so I was trying to explain this actually to someone yesterday there maybe 65 or 70 years old and I was explaining how AI is the

centralizing factor and they said great yeah Amazon no they said great so Amazon's done a pretty good job with my groceries so far uh you know Facebook's done a good job as a social Marketplace like why should I care about that um why does it why why is it a bad thing that it's a centralizing uh Force here so I don't know if that who who to ask that question but would just be curious how you guys think about that I'm happy to start a quick stab and then um I'm sure you have a bunch as well uh I think when we talk about crypto AI you know Anand and I have had a bunch of discussions about this question basically like does crypto AI matter outside of crypto AI does it matter to AI people and um historically

the answer has been you know no for the most part uh I would venture out and say the average AI researcher engineer what they care about when they're going to join an AI company is they just want to create the best model possible they are really you know fascinated and and interested in how do we improve the you know artificial intelligence quotient but as we've seen with a couple of big events you know it takes the breaking of a centralized system to you know pill people on why they are bad or why there are issues with them and so two big events really happened that I I I think catalyzed even within the AI

realm a category of people interested in decentralized AI I mean at least two that that I can point to but there's certainly more one big one was the open AI Fiasco in November which everyone remembers where you know separately elected board tried to kick out you know kick out Sam for you know some reason that we haven't really found out yet and you know for one or two weeks every single AI friend of mine was not sure if they could even build on open AI anymore and to have that the you know the best model in the world not you know you're not sure about the the sanctity of the the platform underneath is is pretty bad so that's one is now being able to rip away access to models and and make sure

that you know through crypto you can you know more easily access distribution U the second one was earlier this year when we saw Bard Google's Google's Bard assistant making highly sort of politicized responses to questions that people would ask the the the chatbot and I think what that highlighted more so than that the answers were you know quote unquote wrong was that the the answers were tilted to how the developers of the model wanted the answers to be and I think what I care about in crypto is that we're pushing for a user owned operated internet and so it's ideal if

users are able to instead pick how they want the political leanings of the model to be or how they want it to act and interact and so seeing those events I think cause a lot of people in the AI Community to start thinking about hey we should start doing open source models we should start making it easier to do um you know local development of models with you know gpus in a box at your house and it also you know catalyzed a bunch of people like you know Anand and myself and and and many others to go and pursue you know getting more involved in the space and so those were you know a couple of reasons that come to mind for me as to um you ask that that question yeah it's I mean those those

are like the big cataclysmic events over the last like six months and I have a feeling we'll see more of these right as we look forward uh but generally speaking you know I at steady state I I I don't think the consumers should care about this like that is that's fair right we do have you know in fully admitting that in the world of crypto like we do we have crypto speak and you know it feels like a very isolated Community today but yes you know I don't think the average user should care about this but if you look at uh I guess just two more points on this one of which is when we start looking at spe specific nuanced Fields uh legal Finance uh you know um medical Etc um where your data is being used uh as you know basically

AI is going to help you in some very codifiable interesting way it is going to start to matter you're going to want to care about why this model is behaving the way it is why is it hallucinating what are the what was what the factors that went in and whether the output is biased or not and so and then you look at sort of The Primitives that we've grown up with in the world of crypto um transparency auditability verifiability all these things that we throw around these feel like absolute necessary Primitives if you want to put AI to work in in very Enterprise in an Enterprise grade scale so agree with you on the State of Affairs today hopefully the end user doesn't care the but there's certain systems where this will start to

matter and it's it's creeping up very quickly NJ I'm gonna ask you a really smooth brain question here which will show my uh lack of understanding of all this stuff but that's all right how is the uh so I listened to the dwares podcast with uh with uh Zuckerberg and yeah talking about uh uh open sourcing llama 3 I think it llama 3 and then there's um I was reading about the stability AI like rise that they did and um I mean basically What's Happening Here is like you have these kind of closed Source models now there's these open source models and so how is something like like when you think about the platform risk very much uh it reminds me of remember everyone built on Twitter and then or everyone built on Facebook and then they all got booted but when these models are open source

like llama like that platform risk doesn't really exist anymore in in my again smooth brain understanding so like how is this uh how is how is that different than like what's happening with crypto models are are are really only one part of the stack of building an ml application um the the very simple way that you know that we kind of talk about a lot in in some of our presentations externally uh is is we think of the AI workflow is sort of four levels the you know the first level being the compute itself so these are the compute that run the models this is when you train a model or you do inference on a Model you

know actually getting the results um the second layer is the models themselves so you know as you reference Llama Or stability or mistol or you know whatever you know new kind of model that exists on top of that is the data so the data that goes in and actually feeds the models which is also I think a very important component of building one of these systems and then finally is the applications so yes I I think it's great that Facebook stability have released a lot of um a lot of work you know open source and publicly if you go and use some of those models if you go and use Facebooks for example the way that Facebook was able to get it out the door like their legal

team allowed them to release it was they had to do this thing called red teaming which is basically going and removing answers to racy questions so if you ask it about a gun or a political candidate or something like that um it's not going to give an answer so this is I think a step in the right direction but it's not a fully open model yet because who's to say what you you know should and should not say and right now you know it makes sense it's a government trying to you know trying to do Cy on their on the on the products they release and so thinking about building an AI application sometimes you may want an understanding

of what data went into the model and how is actually being used you may want to use a certain class of of um you know answers that may not be available to you um so open source is like a very important piece and I'm I'm glad those companies are building what they're building but all the other factors we we still I think need for you know many different use cases to be decentralized so let's say you do have Facebook's llama but then you still have to run it on you know one of five places uh you know a couple of cloud providers or a couple of GPU as a service providers and you don't get various guarantees that you may want whether you're building a crypto AI

application or not privacy or computational Integrity censorship resistance and and those sorts of things got it Anan from the investors's point of view um maybe we can get into to some of the like yeah I guess how do you think about investing in this space and there's the like whenever you've got the I don't know noraj I appreciate you simplifying it for me like the compute the models the data and the applications uh and on from the Investor's point of view like are all of those layers exciting is one of those layers more exciting than the rest how do you think about this yeah they're um I mean the space is so nent right now that you know there's uh there's utility at the topmost layer

with applications that can really break out and have an impact here and of course then you start of judging it with the same lens that you would sort of an application right where where does the defensibility lie and you know typical sort of network effects will drive traction and maybe that becomes the way in which a company breaks out and we start to see some of these today where they're either literally putting agentic platforms to work uh using transparent models and or creating companion products and using some onchain Primitives like defi Etc so it's like interesting spring of things that haven't been experimented with before but it's still very early because when we think about applications on chain naturally we gravitate towards dii nfts and and and memes and like that becomes

sort of like the uh and you know we have some consumer breakouts today like foraster and some others but for the most part it's like you know we can name these off the you know very very quickly so I think it's it's early there to n's point it started with like the most acute use cases I think last year right like when we started to realize that the the horsepower needed to train large foundational models is being throttled uh and and being limited because you you need to either commit to spending seven figures a month to be able to train models or you don't get access to those you know centralized entities at all so like where would you go so naturally the painkiller use case uh became that you know can we have decentralized compute networks to be able to train or fine

tune models so that you know we started there at the compute layer as neaj mentioned and then we were like you know now we data there's many different ways in which we can access data put blockchain incentivized systems to work to access data data market places so on and so forth so to to Really back and use sort of Nag's mental model I would say the Investments so far have been sort of like following that stack sequence very very systematically and so I would say compute networks do there we've seen a lot of those you mentioned a few of those as we started this uh podcast and then data has been maybe an interesting area folks like I've been thinking a lot about that and then we're now starting to unpack various application areas and and rituals definitely uh you know far

ahead here in sort of opening up the ability for applications to get built right so that's going to be the next interesting wave that kind of comes up as we look into the second half of this year um new Raj Y is you could have gone and built you could have built a bunch of stuff in the AI World um why is ritual what you decide to build um to give a little bit of back history on what I used to do at Poly chain the way that I first you know went to polychain was by way of working in a cryptography lab so I was working in a cryptography lab that um did work on a bunch of different privacy cryptocurrencies Monero zcash things like that and when I

joined poly chain especially early on part of my job was to just go find interesting research advance Ms and either try to convince the founders to go and productionize it um or find companies building those those new advancements and part of the thesis was new almost like what will developers be doing in the future and how do we predict you know what'll happen then with the technologies that are that are developing today and so went through the gauntlet of a bunch of ideas uh at polychain you know as early on as new lay one networks in 2018 to ZK and um layer 2s and

privacy and so in 2022 I started paying close attention to AI because after I read the Transformer paper and started playing around with some of the work in the space I got very similarly excited as to when I first discovered crypto so I knew that there was probably something interesting to look at and started you know naturally thinking about is there a cross-section between the two spaces here and after a couple of months of of research alongside my co-founder and and some members of our team and outside the team um it became very clear that there was and that this was a brand new area and I very much like New Frontier markets

those are the most exciting for me I prefer you know one to you zero to one type of bets rather than you know going and competing in a you know crowded I don't know crowded layer 2 space or something like that um we really wanted to find a brand new area that developers would be using in two to three years not to mention the the kind of backdrop again of the increased centralization alongside the increased usage of AI and so largely all of those pieces made it to be a very exciting you know kind of problem to work on Big Market very difficult technology um early and a lot of smart people that you know that that I've

learned from and and um are you know building in the space nice what are the when you think of the like real I guess you have to put time scales on this there's like what's exciting now what's exciting in five years maybe what's exciting like the endless possibilities in you know 10 years and Beyond but when you think about the maybe uh let's put a 12 to 24 month time frame on this like what are the possibilities that excite you guys like the things that I was jotting down before this was um like yeah decentralized gpus kind of like the Uber again these are things I've I've heard and read about but I don't know if they're actually real that I'd like your guys' like help understanding if they're real there's the Uber and Airbnb for gpus there's like doing more local and P2P inference

there's using crypto to incentivize AI behaviors there's probably some sort of verifiability to be like this media asset is real um there's probably like self-owned models and data like I've got all my data that should be worth something uh and then there's like agents using stable coins if you had to pick some of those like what are what excites you what's fluff what's real um and on maybe I'd throw this this first one to you yeah um 12 to 24 months I think one of the things that you mentioned has probably been top of mind for for at least maybe in our bubbles and our circuits has been fighting deep fakes uh which is sort of like the the reactive

measure and the proactive measure being how do we how do we use ZK to actually codify the source or authenticity of certain media because I guess somewhat like the blast radius of problems that have come up with AI have been it's awesome you can generate images uh that you know that fit certain characteristics based on certain prompts but then again it's really hard to discern what's real and what's not and that media has gten out of control so that's definitely one that's been interesting in top of mind and there's been I guess a lot of research that's gone into this everything from audio to to images and some now coming up with video and then that the reactive piece is actually quite challenging to do but I think there's there's some work that's probably very much in front of us here

today um there the uh I definitely feel like I think going back to the question that you started with right like the you know why this why now some of the thing so motivation motivating factor for me you know I think someone Raj you know and and maybe some others I I've been sort of like peripherally involved in the crypto space the last 12 years and there have been various events that have led to adoption of crypto networks over the years and if I were to forecast out I'd say that you know with a certain set of like daily active wallets or monthly active wallets we've gone to this level of transaction velocity and change which substantiates the T that we have today which is like as of today maybe like 2.3

trillion or whatever that is right so again maybe putting a more financial hat on like what what's going to get us to that next order of magnitude which means that all the work that we've been putting in is is actually being used massively at scale and uh you combine that with the fact that I've always had a tough time connecting the dots between like oh we need to get the next million 10 million users on chain and I I think blockchain networks are beautifully suited for agents to participate right so now kind of let me L the plane by saying your point about agents using Stables agents paying one another agents uh you know I shared this uh this paper with nage I'm like this is a fascinating Concept in social science agents putting humans to work and compensating humans

for doing real world work uh you know like and this sounds like a game or a toy but you know to quote christien right A lot of these things start up start off looking like toys but could have practical use cases down the road so um again to to summarize I'd say agents are a big part of this I'd say more more pressing or topical today is deep fakes fighting misinformation disinformation connected to that it's like things like proof of humanity um and uh yeah you know there's going to be some interesting game like experiences that come out of this as well so I'm I think that will spark some Innovation equipment can you say more about the agents putting humans to work idea yeah I mean uh at a high level this was like you know some

like so this uh the paper does a really good job of this and and I hope I don't butcher too much but how can we generate and test like social hypotheses social scientific hypotheses using large language models right so they call these things like structural causal models or scms so the combination of these two effectively means agents are coming up with hypotheses and saying hey humans go do this work and when you do this work off chain you will get compensated for it and then that information is kind of really back for agents to assimilate information that from the real world that they can't otherwise get because everything they going to be doing happens within the silo of online and onchain so it's a really interesting like you know reinforcement learning

concept that that really hasn't been done yet and by the way it's got a fair amount of critique as well like it's it's a it's something that can really get out of control very quickly but again it's like you're you know at some point these systems are going to get smart enough to be able to put us to work by the way maybe not too dissimilar I remember talking to Ilia from near about this maybe about a year ago and his his sort of big quote was that at some point we'll all be working for AI or agentic systems like we'll be doing the work whereas and I think his theory was that like a maybe there's layers of management that get replaced by AI right and so maybe this isn't too far out like I think what I'm proposing all this paper proposing is more of a a science

experiment appears more game likee but yeah there are there are ways in which yes you know there may be tools that tell us like by the way this is set of what your day looks like hit these goals in these milestones and you get compensated for yeah the two folks who have talked about that on the Empire podcast are um are Ilia is one of them and then um we had Rune from maker uh from out talking about that as well so uh newaj what are your thoughts on this whole AI agents stable coins when are AI agents GNA be actually can can you just almost break down like what AI agents are I I have an idea of what they are but can you can you break it down sure every everyone has their own U their own answer to this question but um

the way that I would describe it at a high level to like give a framework for what it is is agents are pieces of software or computer systems it could be a da it's basically a self-contained entity that is able to take actions on the behalf of someone or or multiple someone or multiple people um without the user explicitly programming them to do that task so a very simple agent could be you know let's pretend that you know I run an office with 20 people here in New York and an agent might look like you know if the bot sees that you know I

have meetings with 11 people today maybe it'll it'll get me you know it'll order Starbucks for me in the morning you know for 11 people and and order to the office before they all come in something like that that's something you could do today with um you know with with open Ai and stringing together a couple of apis and so that I think can be very valuable in a crypto context um you're now able to apply it to various different you know actions in a crypto context you know one might be an agent might be able to tell you that hey your collateral and your maker out position is getting low and you know you should top it up or you know I'm

happy to top it up for you uh or hey your six friends are buying this nft you might want to buy it and a whole bunch of other things things it allows it it allows you to almost be predictive about the tasks you're going to do and someone can execute it on your behalf so that's how I would I would generally kind of slice and dice the the agents's question at least at a at a high level that's interesting what are other Naraj what are other areas that you are let's go to decentralized uh gpus tell me real real uh exciting or not exciting uh I find exciting um so yeah so this is the uh I call it GPU as a

service company or a lot of people call it Airbnb for gpus is this aosh yeah I would say aosh probably fits into this um this is maybe one of the the bigger areas of crypto aai in terms of number of teams really the people are here operating on different um different thesis as to why this is an interesting category some people are saying the big GPU as a service you know centralized GPU as a service companies companies like Lambda Labs or cor weave are good but you can't get access to enough gpus so there's a supply crunch or they're only offering certain classes of gpus

things like A1 100s and h100s which are the kind of upper end you know last generation Nvidia Enterprise chips that are widely used for both training and and for inference so they're saying hey there's a shortage and it's hard to get access maybe you should start using lower grade gpus of which we can Bridge into a bigger supply whether it's because you know it's a crypto thing and a bunch of eth miners used to use gpus to mine eth or people are proving you know ZK circuits with gpus or doing if FH workloads of gpus and a whole bunch of other stuff so gpus are these like special purpose computers that are really good at executing very simple

tasks um in parallel and so in a in a ZK system it's doing these these multiscalar multiplications or fast 4ia transforms and in machine learning they are doing uh B basically Matrix multiplications and so you can reuse that Hardware in the you know in the GPU as a service context the big thing to win here is that AI is growing very massively so there's a very big Market to win here if you can cut out a piece of the AWS gcp they're building more of a hosted type of solution or Lambda Labs core weave which is they say bare metal is what it's

called there's a pretty big Market to win we're very early I think one of the challenges is that certainly you can incentivize new Supply to come aboard and and bring new devices on um but but Bridging the web two demand to the web 3 Supply I think is like one of the the bigger questions and so I think over the next year we're going to see how that starts to play out I don't want to make a prejudgment because it's it's very early a lot of these networks didn't even exist two years ago uh and this is a problem that we're trying to solve we plug into GPU as a service companies and are basically trying to generate new forms of demand for you know you know ml workloads basically on chain and create

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onto an L2 that I've ever ever had uh you can you can try it out it's engine nn. Kinto doxyz I would really recommend going through the whole onboarding flow just to see what the future of crypto can feel like and what it probably will look like in the future go on board nn. Kinto doxyz let me know what you think and if you want to chat with their founder rone happy to make the intro hey everyone Jason here I know you've been hearing a lot about the intersection of crypto and Ai and that's why I'm really excited to share our newest partner and sponsored Empire scale a high performance modular blockchain that's revolutionizing gaming and AI with zero fees and instant finality scale's unique

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sponsoring Empire we're excited to partner with you guys bridge over to scale if you're listening to this at scale dospace ecosystem follow the journey along with scale on X at scale Network that's at scale Network big thanks again to scale for sponsoring Empire remember in 2020 in defi summer and then starting in 2021 everyone's like all right great like defi defi is booming the institutions are coming the institutions are going to play in Defi and they never really did come and that was fine though that was fine and um I think there's always this like aspect of crypto where people love to say like that big group of people outside of crypto they're coming in but in reality the best products that get built are for

deeply crypto native folks and it's an industry that's built very bottoms up I'd be curious to get um both of your takes on like do we need will will will crypto I've heard one side of the argument that says like AI will be the thing that helps crypto cross the chasm because yeah Google bard is like I don't know censoring X Y and Z or I don't know there's these uh we can't tell if the I don't proof of proof of Humanity or something like that and like worldcoin is going to help with this or the other side of the argument is look it's all going to be Crypton it's it's crypto native all the way up um how do you how do you guys think about that yeah I I I'll I'll take a stab at it and maybe you know um you know having

spent time with nage and and uh uh and team ritual but also folks like Jensen for example uh who also you know they weren't necessarily crypto native or the team behind Sahara which is like you an academic team um that focused on AI and NLP uh prior to this for cify from Austin I mean these folks are all mostly AI native and so I'd say that um I mean just my mental framework for like you know what is going to you know will we get this utility happening outside of the crypto world for me I think it needs to start with talent that believes that the Primitives that exist in crypto can are are the are the ones that really exist for us to build a beautiful

decentralized AI Network right so the fact that this talent's kind of coming in in in waves which uh which makes me feel really happy is I think probably the first way to get started like we' seeing sort of like neet new Talent flowing in folks are like new to crypto but have you know credible AI backgrounds I think that's like the first thing and the second thing you know again like uh the the kind of tools that the likes of ritual and others are building are really for to enable developers to build things on top of their stack right and at steady state My Hope Is that the average Web Two developer and again this is yet to be proven uh and you know Raj and I talk about this quite a bit which is like how do we get the average developer who needs to use who needs to perform some

kind of inference how do they use a stack when they don't really care about the underlying mechanics whether that's a crypto incentivized decentralized deepen Network or to centralize enery like they they shouldn't have to care about this right so I think that's that that's sort of like the end State we want to get to um but you also like lastly I'll say this by going back to talent and maybe slightly more philosophical but I and I'm going to butcher this because I think Mark and reeson said this very well in a very like you know concise way but it was something like you know the best Founders out there sort of will their perception of the reality and you know when I first started talking to Raj about what he was thinking behind ritual is like if I don't do this now like I mean this is my this is my calling like

I need to go do this and I'm going to make this happen because this needs to exist and if I don't do this I'm sure someone else will but I want to be a part of this wave that makes this happen and I think with the kind of talent that's coming in which is creating this beautiful Network effect of more talent coming into crypto I feel like we're going to get this steady state where like this layer as to what where what stack this is running on is going to get OB fiscated and but it hasn't happened yet but that's sort of the challenge that's in front of us and I feel like we have the the right people to go tackle this so a more philosophical sentiment on why I'm bullish in the sector yeah I I would agree with a lot of that I I

think the the way that you framed it uh is exactly right um it's not often that you can just take crypto and like fit it into a product and then new users will come it does have to be a more Bottoms Up kind of within the community emergent approach and you know if you go back and look at when ethereum first came out many people couldn't even begin to you know guess what the use cases would be and you know three four years later we had defi we had nfts and and you even four years past that it's a or eight years past that it's such a wide Market um and I think you know as we're laying down these very early Primitives you

know connecting smart contracts to blockchains and decentralized training and decentralized verifiability privacy um I think we're going to see some very exciting emerging behaviors start to come about on the application side and I I think I think the crypto user base is a very good user base to build for first in many ways it's a really good way if you're trying to build something important in AI it's like a brand new tact rather than use the same distribution path that everyone in AI is using go and talk to a brand new set of users that tend to spend more money on products tend to be you know at the early days made more critical of the

products they use so you can really you know test if your your building something valuable as if people are using what you're building and then ultimately seeing for the you know the emerging properties of what you're building if there's something valuable that users can take away um and so certainly that's like a a very big Focus for us is you know making sure that we can again cross the chasm have that chat GPT moment for crypto and maybe AI is part of that story for uh for you know ultimate crypto adoption H who will what do you think that moment will be like you remember you remember 2018 and 2019 after icos and everyone basically said what is eth good for

anymore and the price fell from what 17 or 1800 bucks all the way to the low of like 85 and everyone's just like yeah maybe eth isn't good for anything and then defi summer hit and we said ah eth is good for something what is the um what is the like defi summer moment gonna be for for what are we calling it D de Dei or something for decentralized AI I think the fir the first thing will just be being able to play with it um crypto AI is unique in that defi summer happened after we had defi smart contracts for like three years I think um you know Dharma launched in 2017 and

uh we had ethland and compound came out in 2018 so there's a you know dydx there's a whole bunch of things that started then and I think it took the combination of the creation of um you know basically liquidity mining from compound and the launch of Unis swap the growth of the longtail to really carve out a market to where defi was a valuable asset um when we take the same you know lens that you used before around you know yeah defi you know institutions didn't really use I think people originally the thesis of defi was it's like a brand new from Bottoms Up you know correct by

construction Financial system and so it should just be net better for the traditional Financial system to use but the traditional Financial system is so full of you know outside of just the te technology there's lobbying in place and broken systems and relationships that a defi is not going to overtake it overnight I think the the better way is the tro horse approach which is make the crypto user base really really you know wealthy influential using a lot of products basically they are their own sort of force and then now they're already using defi um they don't need to be converted into anything they're already just a natural user of Defi and

for something like AI largely I do think you know one of these early use cases will become quite big agents to me is a very exciting opportunity that we have in front of us in the web two space you know this is also you know what people are very excited about on the on the traditional Venture side um you know we we've talked about this example a few times um which is being able to interact with blockchains with natural language will become a very very interesting and valuable Crypton native thing for users to be able to do so an example that I I usually give is let's say that you wanted to take out you know 3x levered

exposure to Apple with Dia collateral and then at at some price point you should stop out and close out the position to you know have some safety or something around it normally to do that in defi it would take like 10 different smart contracts and clicking a bunch of interfaces but I said that to you in one sentence and I I think the power is being able to take that one sentence and convert it into some sort of you know form of intent and you there's a bunch of companies building on the intent side and then being able to now interact with blockchains in a way that's actually usable by Regular People and not just people that are very in it uh and so I

think being able to you know work along the side of agentic sort of emergent applications as well as being able to interact with blockchains in an entirely new way are going to be the pathway towards finding the emergent you know Dai use cases you you were nodding your head there you want to yeah I I mean it's so well put I mean I think the I don't think this is an or like it's our defy or some decentralized AI application I think it's an an right you have I think what n distinctly said is that uh you know these sorts of llms and and uh llms could be the ux unlock we're looking for right you combine intents which is sort

of a framework that exists today as a primitive on ethereum you combine that with natural language and you're able to create something beautiful and then furthermore if you have like agentic systems that are can truly process who you are your risk threshold your your ability to put certain amount of capital to work and and and make that happen for you then you have this really interesting flywheel happening but this is all sort of converging today so um that that could be that's like I went narrow into one use case around like putting def work with llms with agents but then like there's other possibilities that could also you know substantiate this right we we we touched on this briefly things like you know where private data and the ability to

perform actions on it will start to matter right things like you know privacy preserving machine learning using encryption techniques like fully homomorphic encryption on such data um and and being able to use the blockchain for consensus it's uh these are all sort of things that I think will augment and and you know start start to unlock utility in ways which you know they may not have the consumer feel to it but I think they'll have some Enterprise grade feel that is going to unlock some net new opportunity so these are also exciting areas that that I've been looking at yeah who's using uh what non crypto companies are using crypto AI companies products right now uh I I can name quite a few so like you know there's an really interesting

integration that happened with this company called brvd basically they give you the ability to spin up like Jupiter notebooks which are essential forms to start to do machine learning training of data so brev Dev is unlocking the ability for any developer to use a cautious decentralized compute Network to be able to put their gpus to work uh so this is kind of like you know multi-tiered in some ways right so developers using brev Dev brev dev's got the ability to spin up h100s uh that are running on the K Network I think that's number one and I've seen all the way from that like very inference systems um you know hey by the way like I think n alluded to this earlier right like there are certain things that have been extracted away from certain models today

because of which you can do certain things right like whether it's not safe for work stuff all the way to specific nuanced utility of models for for something that may be very very hyp specific so I have seen examples of where like you know I want to create my specific companion or character that might not be um you know centralized entity AI kosher today how do I how do I create or spin up something like that where I can have a companion whether I want to share personal details with them this is my AI Wu those are the kind of scenarios we've seen crop up so I just got I give you a little bit of a spectrum there on the latter I'd say there's quite a few of these the names sort of Escape me but at least one example where developers are putting you

know some of the backend systems to work today h what is this company mentioned in the notes noose no us n oh yeah yeah news research is another interesting company uh they are yeah there a bunch of like AI experts who been uh you who spun up a big tenser subnet but they're primarily in know the field of synthetic data generation and being able to get llms to become smarter because of the work they're doing in creating synthetic data um but uh yeah you know another example of talent that's come in to work on crypto in in a very credible way and let's say research primarily today can I like run through some of the projects that I see on the

timeline all the time and I'd love to get your guys's takes on them I don't know how much you guys can can share if you guys I'm sure there's Back stories with a lot of these companies but um all right I see Martin scy posting all the time about IET what is IET real fake tell me about IET so IET is building a way to plug in in effect it's a GPU as a service network so allows you to um plug into this network of gpus that uh you know supposedly come from a number of different data centers and you can then use inside of your applications so in some ways you can think of it as a drop in replacement to uh to Lambda or something like that um I think the

controversy was around um you know fraudulent gpus on the network and um Martin I don't know if he's building in AI crypto but I know he's very interested in crypto and at least building you know adjacently to it um and I think he had issues was setting it up and was you know kind of diving deep into the the backstory of IET and things like that um I haven't followed too closely but that that's uh that's what I've learned and and read so far how about go ahead yeah no I was just going to say that um this problem said it's it's a really interesting topic that got UN unraveled in some ways which is the beauty of sort of decentralized networks

there's there's a little bit of a double- Ed sword right the we when you're joining a permissionless network either on the supply side and or if you're on the demand side like Martin was trying to put some of these networks to work and you need to have this level of transparency that exists but um it got a little out of control all this is say that maybe a call to action is around sort of reputation systems or being able to really understand what's happening these decentralized physical infrastructure networks is going to be probably going to start to get Paramount right so that was sort of a big takeaway for me because when it comes to you're using a central using AWS there is an SLA this terms of service on like what you pay is what you get with

decentralized networks we need more transparency here that needs to emerge so that was sort of like I'm glad we red this problem today because there's more work to be done to ensure that we're providing a level of transparency that uh that doesn't exist yet how about bit tensor yeah I I I could start here you bit tensor is uh is fascinating I would say it's a Marketplace for generalized compute um that's sort of like maybe the high level tagline um what's become interesting is you know within bit cancer you have these various subnets of which there's like a limited set that you can have today and each of these subnets has a very specific purpose uh for for why it exists in the bit tenser

ecosystem it can be anything from file storage to decentralized compute to you know very specific inference you know hey provide a prompt to get audio back something along those lines and each subnets is very opinionated about the kind of work that that exists in that realm so I would say that and you know I'm sure Naraj and the poly chain team have have more background and sort of like the Genesis story of bit tenser but uh I would say again you know maybe a little it's it's been really fascinating because a lot of folks have gravitated towards it being able to spin up these subnets and actually start to put various resources to work uh news is one of them uh we've had you know prediction subnets that have come up now we've got companies like virtuals launching

agenting systems on there so yeah it's it's a really interesting test harness for a lot of uh sort of AI crypto uh projects um and yeah at at the core of all this is sort of like their blockchain consensus system so I I hope I did it justice but uh it's just I would think of it as like you know several different sort of nation states that have a consensus system behind them which is which is the bit tenser you know um contestor Network I won uh I won't play 20 Questions asking you guys about every AI crypto company but um Naraj is someone who's like deeply building in this space um and I'm over here just scrolling on Twitter about it what um what what feels very obvious to you about cryp like the intersection of crypto and AI that maybe doesn't feel as

obvious to to most of the rest of the world yet I think one of the big um I don't know if they're mistakes but one of the big oversights that a lot of crypto VC's made over the past one year about crypto AI is they kind of they basically looked at the previous attempts at crypto AI in 2017 and 2021 and basically wrote off the category um if you went to any you know competent crypto VC you know even one and a half months ago I mean not all of them but but most of them most of them hadn't looked at the space at all um they you

know if you were to ask them what are you doing in crypto AI um they would have said oh that's you know there's nothing interesting there that's just a meme those are just meme coins and you know fast forward a year later and every single fund is is now they have a crypto AI strategy and they're writing articles about it so I think you know in some ways almost the pride of the VCS made them Overlook what was a very exciting opportunity to invest I still think there's a lot of exciting things to come from now but that again my philosophy in crypto investing is that you know you you actually do want to be early you know it's it's not like traditional Venture where you know seeing the the present clearly is the most important thing I

think in crypto given how cyclical it is and how her driven it is and narrative driven it is um you being early is being on time uh so that I think is one of the the bigger mistakes uh or oversights that that I saw that people didn't didn't get right n you have anything for that question uh yeah I I i' would say that I mean maybe this is a little bit further down the in the weeds right I um which is if you think about various topics and and conflating various different things you know so like in the spirit of what you asked I'd say I I see uh open source and decentralization getting conflated

for one another quite a bit right which is like you know I would say you know we really body open source we and of course let me sorry let me unpack that even more like when it comes to things like llms you know there's you know this the difference open source and open weights says open source open weights decentralization so I think we we latch onto some narratives very quickly so in terms of like what we Overlook I would say that uh the core tenants of decentralization are are almost essential uh to me for for AI to be functioning and for us to promote research and bring in diversity of thought and um and ensure that we're not sort of like tethered or tied down by

the confines and and guardrails of like big Tech right so uh sorry to keep paring this narrative but I think that's that's important so that's decentralization Primitives on the other hand open source is a is truly like the Tailwinds that are necessary for this Innovation to happen right and the the one thing that I'm starting to see a lot more of you know just coming coming back to Talent open source I you know historic for as long as you know you've been a programmer you've got youve you've understood open source you've understood licensing behind it but when these two forces come together open source plus decentralization it's actually like a very very powerful tool and so um there's inherent questions today you know I I've written a lot of Open Source Code and I've had questions like hey you

know is how does orance have contributed a bunch to like stack Overflow which is now obviously you know that technology been superseded by llms but uh how do you get compensated for that like what is what is the what is the framework that you use to compensate really credible developers uh who who building things and open or or answering questions Etc but now we're having these Primitives come together you're being rewarded for your work you can you can launch a new you know a fine tune model on chain and get compensated for it and so these things are getting unlocked so go come back to your question start along with the way of saying what we're overseeing I think we we think we latch on to narratives like what is the utility here but to me as we look at sort of Paradigm shifts over the last 20

years when these sort of platforms get built whether it's Cloud whether it's mobile it's blockchains when developers flock in and they start to see a Sandbox and they're like wow we can do something creative here we can monetize this unlik anything we've ever seen before suddenly that just opens up an application space unlike anything else right so we saw this obviously you know several examples of this over the last couple of decades so this is this gets me a lot of optimism um and to n's point and feels it felt contrarian maybe a few years ago it still feels contrar now I would say nage even to your point I still see a lot of investors like yeah this is thematically it feels like something we're just latching on to because you know of X Y and Z but uh I I just see an

opportunity here to go build some really cool that hasn't been done before love it that's great uh the data in these llms is like I mean it's feel like the two things that are working right now the the like NLP which I guess NLP is is you know now it's just these feel like it used to be called NLP and now it's the big language models um so it's like it's text and then it's computer vision it's the CV side of things what do you think about and on the language side of on the on these large language models it's like it's a it's a lot of the a lot of the data is coming from either like social platforms or just like the the internet basically uh Naraj what do you think about leveraging the amount of data that the blockchains are spitting off like

the data stack today I mean like the l1's like l On's and l2s like I mean spit off boatloads of data and then you know Alchemy and INF fur and quick node and stuff clean it and then you've got the API providers and then folks that on top of those and stuff like that but yeah how do you think about using like blockchain native data in some of these AI systems and like what what will come from that I certainly think there's a lot of interesting user applications for using blockchain data inside of an l M um we talked about the example of the human language interface and so that would take advantage of you know smart

contract data and and block data that you could then leverage uh inside of an application um I even think using crypto as a substrate to gather more data will become very valuable um you know there are companies building in the you know label to earn you know category you could call it or contributors are basically rating if models are good or not like the responses from the models are good or not and then using that to you know to basically reinforce the decision- making of that model um and so that is all to say you know there's there's so much interesting thing you know interesting

surface area to build in um there's a a company called Vanna vanana that is trying to B basically do an experiment around paying users for their data so they're they're creating this subreddit called I think it's called Data Dow and they're experimenting with ways to pay people to submit their data because one of the challenges um you know the New York Times is in a lawsuit with open AI over the use of you know their writings inside of the open AI you know gp4 system and there's this big question around how do you do attribution and how do you pay someone you know if you do use their data in your model and you

know these these systems are lacking access to our personal user data so if you can bridge and you know allow people to get compensated for bringing their Facebook data or their Spotify data um both web two data but then also you know back to your point web 3 data you know if I could use my forecaster data or my Sona data or you know whatever else new you know social system inside of a crypto llm there I think could be a lot of interesting use cases around recommendation and um an ultimately interfacing with these systems Roger if you guys are wildly successful like let's say everything goes right for five years in a row what what is the how how how is crypto

different or how is the world different if ritual Just Nails everything for the next five years I I think if we nail everything decentralize AI will be a real credible alternative to centralized AI because I think the backdrop today is that centralized AI is going to win it's a monopoly business they have all the resources and the talent and the attention and the regulatory capture um so how could crypto AI win and I think you know there's a lot of really interesting approaches happening in the crypto a landscape you know I like the direction that that we're taking to go about on this this pathway uh and in five years people are pulling models

from decentralized AI systems they're building on decentralized AI platforms they're contributing data into um you decentralized AI systems and and you know run the whole gamut of of you know mix and match for for Building Products so ultimately I think it's it's pushing towards uh you know world domination we didn't get into it this this podcast TR but if AI continues to permeate the market as it has we're going to have a billion people using AI in 3 to four years and inevitably it will be used to manipulate people or to create propaganda and those things will be used to tilt people's opinions of you know

public favor in governments and corporations how they spend their money who they interact with what they do and so ultimately it's it's both like we're fighting it from like a market standpoint like there's Better Properties here it's cheaper whatever but there's also a very fundamental values difference that I I think is very important and and I hope that you know we can have you know help the world understand the the you know the kind of the underlying problems that that exist today and on on that note I saw you putting the notes agents could drive more transaction volume on chain than humans ever have um yeah would love to just

hear you expand on this yeah you know I I think this is the uh um you know we were chatting about this a little bit earlier right we in some ways we have this like complex you know user experience customer experience problem with blockchains as we know them today you to all a wallet you need to know how to transfer Fiat to crypto to get onto a chain to be able to interact with defi it's like you know doing one of these things while hopping on one foot and like you know it's it's it's complicated right so uh and Raj said this really well right like we how can we unlock the ability to use natural language plus intense and and with llms to be able to do things on chain and then you know maybe taking one step further from there um you know can these

agents uh act on our behalf and to to do some credible work but that's again assisting humans in one way because again you know asaj said there's many different definitions of Agents but at steady state there could be many many such agents for a single human being that are doing various things for you whether it's activity on chain or whether they're doing some work offchain for which we just need verifiability and therefore they need to run on decentralized networks and so um and then of course they could be tasking one another they could be doing things they could be putting humans to work as we talked about on this podcast and for all these reasons the transaction velocity is going to go up and so the metrics for me are you know how do we drive transaction velocity and then

commensurately that increases crypto tamam and you know as as and I think in some ways like we've been we we're kind of born into this world of crypto and and believing that like you know number continues to go up but obviously the price going up is one way in which you know the time goes up but transaction velocity is the second piece and so if agents truly start to interact and put the blockchain to work in ways in which humans have not been able to do so do so far that substantiates the the you know it it realizes the true utility of this network so that's what keeps me again there's a lot lot of work to do here uh and I'm I'm more optimistic than not that we can make that happen so that's that's the that's a steady state world that I see in front of

us maybe we can just end with a closing thought to like tie all this together which is kind of what we started with in in a sense but I guess I'd ask both you guys the same question to close this so either one of you guys can start but if someone someone's listening to this they're like I think I get it but give me the summary like why does AI need need a blockchain how do you think about that so the the summary that I would give is AI and crypto have these biral benefits to which you get when you when you combine them and they're technologies that are

both entering some degree of maturity to which it makes sense to combine them and creates these interesting emergent properties crypto provides you tools for self- sovereignty it's ultimately a way for you to control your data your assets your identity and use that in a portable way across a wide arrange of applications defi nfts gaming Etc and we've seen many interesting benefits for doing that and and users in many of those different categories and then we have ai ai is this tool today that provides you infinite abundance this you know you know it's intelligence

it's giving you the ability to ask a question about anything and expect a reasonably intelligent response back maybe you can't ask ask it a highly you know deep you know PhD level physics question but you can ask it you know really anything else you can ask it for you know help with writing a letter or a accounting or or really anything else and so being able to combine those things you take this highly intelligent highly powerful new capability and combine it with these guard rails that now allow you to give power back to the users and create AI systems that are owned by the users you can incentivize

different pieces of the stack to help grow the um the networks themselves whether it's in incentivizing people at the compute layer at the models layer or at the data layer or ultimately at the application layer and you know crypto can definitely help AI um in providing these guard rails and I think what's emerging is AI being able to help crypto and we've talked about some of the use cases natural language interfaces web 3 agents um others are smart defi autonomously generated nfts unique gaming experiences that are generated in real time time and a whole bunch of others so that would be you know

generally my thesis on AI crypto and and you know what I find interesting about it at a high level yeah um you know the the first s of the instinctive reaction that comes to mind is obviously like you got of like who are you talking to right like in the instinctive like you shouldn't have to care like you know I you don't want to have the average person thinking about what's the what's the underlying system here that's driving my you know what is this what is the stack built on right like today we we conduct queries on the internet and like whether it's Google whatever the case might be but we don't really think about the stack behind it but it is going to start to matter and that's that that's where sort of the rubber meets the road right so um and I was uh I was thinking back like I

think there's a there's a book called The Diamond age right uh and I think in this book that you know humans are paired with an AI device from birth it's a it's a science fiction book and um now you know we don't have these problems that EX today but I think the azimoff quote is something like today's science fiction is tomorrow's science fact right so I think very soon we're going to have these sorts of devices this is already happening we have these Hardware devices that are coming out every day and we're going to start to increasingly rely on them I mean I use full self driving on my Tesla um you know almost invariably every single day and so AI systems are going to premate our lives very very closely so if that's sort of the backdrop and we're birthed with you know my daughter's 11 she's going to start

you know she uses perplexity or Cil and like these kinds of like augmenting search engines more than you know I think any other system today so the real question is you know in front of us like do we want to let these AI systems be run by big centralized entities where the the profit systems are are monopolistic in nature and they're not clear as to how they're using our data like do we want to continue to perpetuate the problems that have existed in the past and I think that's the that's s like the underlying issue we're trying to prevent with these systems so I would say for the user probably doesn't care but it will start to become important when you're when we're talking about just artificial intelligence right which will start to prute our lives more and more so that is

where I hope again I don't mean to sound like um you know like Doom and Gloom here because things can go really bad but I think the opportunity for us to build things and and create these guard rails as as NJ mentioned because these Primitives is going to become start to become more important so let's start with those as the fundamental building blocks as opposed to again power aggregating in a centralized fashion and I think we'll have we we'll kind of like create a future that we're all sort of proud to live in so that's the that's the call to action for me I love it good place to end Anand Naraj thank you guys appreciate it thank you so much yeah appreciate it [Music]