Fabric Ventures' Investment Thesis Since the Dawn of Bitcoin to AI - Richard Muirhead. Ep. 554

Transcript

Bitcoin is digital gold that was actually where we thinking about it at the at the time uh deploying Bitcoin and uh you'll you'll do well kind of thing we were um fully open to the opp opportunity of of decentralized Finance in a sense defy hopefully will become useful by being applied as a primitive as a building block to the applications and marketplaces we're trying to build and then in that way we'll see it become much bigger the open movement the ability to share data um the ability to share research that has been the you know the origin that has been the Petry dish from which all the notable inventions have have come I I think that the other side of the the the impact of AI on web 3 uh the just a very specific one is that if we look at the way in

which AI co-pilots are tracking and their ability to create applications that we're going to go from a situation where there are to relatively few solidity programmers and it's incredibly hard to audit U smart contracts to a world where welcome to epicenter the show which talks about the Technologies projects and people driving decentralization and the global blockchain Revolution I'm Sebastian and I'm here with my co-host freder erns today we're talking with Richard Murad who is co-founder at fabric Ventures and also on the near Foundation Council so fabric has been a longtime VC in the web 3 in crypto industry and you know it's been a long time coming since we should have had Richard on the show but you

know 10 and a half years later here he is to share Fabric's latest thesis which is about the intersection of crypto anai and we'll also get in some other topics like investing in crypto and you know as a emerging manager I'm also very interested in asking Richard a bunch of uh questions about how he runs this fund so this is also sort of a good opportunity here to to learn about crypto investing before we talk to Richard here are sponsors this week this episode is brought to you by gsis nosis builds decentralized infrastructure for the ethereum ecosystem with a rich history dating back to 2015 and products like safe cow swap or nosis chain nosis combines needs

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high yield staking to your own customers using their API your assets always remain in your custody so you can have complete Peace of Mind start sing today at chorus. one Richard thanks for joining us on the show this week fantastic to be here um uh don't tell anybody that it took me 10 and a half years to get on the show because um they might make a a jab at my punctuality um um and and and also actually something you reminded me said just then sorry reminded me of Harry stebbings with his 20-minute BC show uh where he he has done an incredible job of getting great guests on and talking to them about the the art of venture

investing and build that into a great franchise so I wouldn't be shy of that that seems like a a fantastic way to go not that I necessarily have anything to to add add to the picture and also I almost appeared on his his show right at the be very beginning but it didn't happen and so maybe I'll have to wait until he's on his 10th year as well before I get to do that well let's hope not uh I mean actually I mean that that that's sort of not entirely true because you were on our 10year anniversary show uh you appeared there for a brief moment but it wasn't like a proper interview uh but as I understood as I've learned I guess like fairly recently actually uh you've been listening to epicenter since pretty much since the beginning right yeah somewhere I mean I was I look back at

some of the episodes to kind of um sort of reacquaint myself but I know that um I kind of got the the the bug somewhere went got suck down the rabbit hole or the Wormhole as we we actually like to call it here at fabric um in um in in the kind of spring of 2013 having kind of spent a a little a little while uh building up to that um but I know that I then got pulled into kind of uh running one of my sort of portfolio companies in 2014 and I don't know somewhere between the kind of the Autumn and the spring epicenter became a a sort of staple part of my kind of stress relieving sort of jogging routine and reminding myself that that that I could get back to the

uh the kind of romantic glories of of uh decentralization and Bitcoin at some point which I which I finally did yeah cool and uh I I think a lot of people were listening to epicenter while running back then including myself i' I'd re listen to episodes uh sometimes like while while while going out for runs when I used to run which is something I haven't done in a long time but um yeah maybe let's you know for for folks who don't know you dive into your background a little bit so I mean fabric has been around I think since 2015 2016 uh what what were you doing before that and how did you get involved in I mean how did you start a crypto fund basically at the moment of kind of

self-indulgence to tell a classic crypto and origin story but I'll I'll try to keep it on point and entertaining um uh and yeah I've been in it long enough that I've heard a lot of crypto origin stories so I did engineering at University and and kind of always wanted to start a a company of some description and I kind of fell in love with software the general power of software I mean I tried my handed it when I was kind of you know 9 10 11 12 as I think as many folks do discovered um actually got my first computer from Clyde Sinclair if you know who he is directly his his parents were were neighbors they got the zx81 back in kind of 1981 um anyway he's famous in the in in

England at least as one of the early um you know major protagonist stakeholders in in the the PC Revolution um and but I quickly discovered that I was not of the I didn't have strong aptitude for software development itself um and I I came out of University and um did some strategy Consulting part of which was in the Telecom space and essentially uh along with my brother Charlie had an an epiphany uh that there was immense power in the openness and permissionless nature of the IP protocol uh Internet Protocol data networks that were um rising up in the early '90s um but that

if we were going to use them to run the world's economy uh that they you know maybe need to be fixed for things like security and quality of service and so forth and um actually with the advice of someone who turned out to be a long-term collaborator uh Steven Waterhouse s uh um we who was an adviser uh we built a a software company to run these very large scale IP data networks um and you and critically I think in this question of kind of getting into um the crypto decentralization space we we we were quite early it turns out with using open- Source software kind of in Anger at an Enterprise or a kind of a carrier uh scale so we used U um an open source

instantiation of of corber actually it's called Omni orb at it was a publish subscribe kind of middleware um and we use that in order to build you know this product um and and ultimately I IPO London Stock Exchange and then and NASDAQ and then did a merger and then so to Oracle and that software is still being used today actually to manage large you know IP networks and came out of that um had a brief sort of got a taste and this is related again to this question of getting into Venture I got um seduced somewhat to spending some time with Axel Paras uh who are obviously pretty storied and and and famous and Infamous these days not least for Facebook um back uh Now 23 years ago when they were setting up their uh

London office uh actually it came about uh and this is I from I found interesting I actually reenergized this connection just last week at an event I I I basically ended up ordering a margarita at a bar with um Rob Glazer who ran real networks for those of you um who remember real networks from last century um and it's still running today um and and Jim Brier from Axel Partners it turns out and he just said hey you should meet my partner Kevin k is setting up in London and for me that interestingly that's a one of those fortuitous connections we should always be kind of striving to kind of make um I incubated a company there um at Axel parner both getting an understanding of what it takes to get build a new company

from scratch the kind of somewhat daunting task of looking at the blank sheet of paper but also learning about the Silicon Valley flavor of venture investing uh which I think is still something that we shouldn't necessarily just be looking to ape or copy in the rest of the world we should be you know plowing our own sort of Farrow but of course we can be inspired by and but also built a a second company that used machine learning Primitives to augment the function of quite sort of of knowledge workers operating actually in the it management space um and one of the things we encountered there was a kind of coordination problem incentivization and coordination problem so how to get people to give up their data um you know they kind of hard one

data um for how to operate a particular part of the kind of back office of a of a bank for example um when actually that very same data was was the way they were kind of Clinging On to their job because it Protected Their kind of little fom they had and so through those I know those threads that are kind of fully apparent but you know early work with open- Source software looking at machine learning priva before they became famous with the like Alex n and emish n and so forth at the beginning of last decade um and looking at incentives structures and collaboration with people when I stumbled into uh Bitcoin uh and I I genuinely don't know who was but I met somebody

who was involved in Bitcoin as early as January 2009 uh but I really don't know who who who who that was I can remember the type of person was in in Switzerland and and then it it was re-energized as a conversation by my friend and colleague uh Steven waterhous aka7 um in the spring of 2013 and um and for me just very quickly the kind of the the shoe dropped um not just you know should we say into their native money uh you know not just the kind of the kind of accessibility arguably the possibilities for of the blockchain but also I can remember particularly um really getting excited by the concept of instantiating you know if not laws but

organizational principles into code in uh in in what we called Dax and then became Dows in in 13 then in terms of investing I kind of somewhat reluctantly hung out my kind of my uh proverbial soccer boots some 2009 2010 when I sold my second company to BMC and and then decided agel investing and was looking for um a thesis that was felt sufficiently impactful in some senses sufficiently crazy uh that it that it really kind of you know just might work and and so that's what Bitcoin blockchain you know know crypto r large web web 3 open web let's we may we get

into that's what they became and that's kind of the the Genesis of fabric were you inclined to kind of start another company as a Founder rather than kind of a fund oh that gave me severe heartbreak um the concept of not um starting another company again and in some senses I have both I have successfully scratched that itch by building fabric um uh over the these last years um but in some other senses it probably gets in the way of of me focusing just on on the investing and certainly we have experimented a lot with quite Hands-On you know activities you know researching what's going on hacking around here and

there and some of the kind of products mining staking validating nothing that we have scaled particularly within fabric but we try and keep our hand in in that in that regard so um so I think but yeah but it was a bit of a heartache definitely to kind of not not to not build another company because whatever you do and look at you know I I I did not have household name success I had some okay success but I felt like I had way more uh kind of like tie tracks in my back and scars on my you know scar tissue from things that had not quite gone the way I wanted them to then I had as a successor so you're like oh next time I'm going to really do it just right and we're going to kind of get escape velocity but yeah it was it's a

good question freder Rich can we talk about your fun thesis for for for a bit so I mean you started um a number of years back and it kind of changed over time so maybe maybe tell us where you started and where you're at now yeah absolutely so I mean think inevitably these things get a little blurred over over time and you tend to have kind of the clarity of hindsight uh and I but I'll try to avoid that as as as much as possible I kind of mentioned that that we were looking looking for a thesis I found to start a venture firm in Europe was quite challenging if you didn't have tens of millions of your own money to deploy in it and back sort of 105 years ago so having uh I used my kind of company starting kind of instincts that

having a a focus a distinctive specialization and trying to sort of catch a wave would be a good way to to tackle it so was kind of on the hunt for something um and uh I had in as I also mentioned in the back of my mind some of the um you know the principles of you know digital money should we call it some of the the power of getting people to collaborate and share their data but I um had not looked too deeply at what was going on with Bitcoin and then um I was uh exchanging messages with with seven in the spring of 2013 you know asking and he was over in Silicon Valley and I was in um South Kensington basically in

London and I was like you know what are you up to over there and there were two things he said he said he was looking a lot of at VR and Bitcoin and and and so as a result of that conversation I sort of sort of dove in um uh and blockchain.info blockchain.com was was obviously a big company you know over here that was kind of active and that was one of my first ports of call um and it was made safe and there was a whole bunch of other people who are active um and we ended up working together on the investment and bit stab in um the Autumn of that year but in terms of the thesis when we were thinking about how to benefit you know to to deploy Capital to benefit from the space there was still a little bit of a back stop Instinct that

you know look Bitcoin is digital gold that was actually the way we're thinking about it at the at the time uh deploying Bitcoin and uh you'll you'll do well kind of thing and actually of course it'd be interesting I mean we're talking like between a price of some $98 to 400 you would have done pretty pretty pretty well in compar comparison to any FS of course that is partly Hinds because you can't say oh you should have just done that cuz that would be a very concentrated bet to to take with the diversification and it and and it and on that point it did feel at that time that there was um I I tried to conceive of all of the different things you might invest in the projects to invest in in order to build a portfolio as an investor and it felt relatively Limited

at that point in time and I think of course it would it really took um sort of January February 2014 when kind of G we were co-hosted an event with coin scrum and and he involved you know announced um he presented a theum for the first time and then you started seeing this obviously the shift to kind of generalize smart contract platforms and then being a apps be able to be built on top of that and obviously the defi world we know um that started to to to make it look like the thesis you could have a thesis just around that space um I think then of course and this is one of the things I think everybody in this space has to wrestle with when when the price is up everybody is massively positive and and often ere exuberant um and thinks that anything is

possible uh and of course actually I found ironically it's at that point in time that limited partners or folks who are bit detached from the space tend to get jolted into action to look at investing of course it is ironic because of course maybe it's when the price is not so high that you want to be preparing to to deploy um and you know we we went through that um winter of 1415 um when everybody sort of started concocting the the kind of it's not Bitcoin it's blockchain kind of narrative and going a little bit sort of B2B you know let's look at how that can be deployed um in companies like R3 looking at the kind of uh the back office for for banks and so forth I I

think whil we definitely didn't dismiss that we um remained Believers uh in the the openness permissionless and so forth of the the kind of the public blockchain movement it actually reminded me of when in I would would have been like 96 997 or something um there was there was this Chief scientist of of unet one of the powerful internet service providers at the time I remember sort of spending some time with him um and he was collaborating with IBM and IBM was trying to get everybody to build sort of sort of private internets uh to solve you know Supply chain problems and to uh prop share information between you know

with GE and Ford and all of the kind of clients and it was the equivalent of a kind of permissioned blockchain and those projects didn't go anywhere yeah I mean ultimately there was the adoption of the underlying Technologies um but those projects went nowhere and it's and it's and so I think for me it it echoed that and so we kind of remained kind of on the kind of public uh Direction so both Max merch and then J and tar those forthcoming years joined and Julia in particular was very early looking at the the defi space and looking at the Arbitrage of opportunities before between exchanges for example you know prior to that something that that occurred to us but you know other people exploited or or took advantage or profited from um uh in a way that that I

certainly never did um and so we were um fully open to the opp opportunity of of decentralized Finance um I think uh it's an interesting question where we we've reached with the the um maturity of that I think we may be at some kind of local top but I think it's it's really a component of something much much bigger uh I guess the only other thing worth mentioning in terms of our thesis is that just because it had because of the nature of where i' come from in terms of building companies that try to you know harness data to to to uh you know gather from know people in kind of networks I um we always saw uh ultimately

Bitcoin blockchain decentralized data structures uh the coordinating power thereof of tokens that are n to them as a way of organizing the world's data from the bottom up the the the emergent power properties of those networks are the powerful thing that if we're going to have a chance of getting the right data to the right you know algorithm at the right time in the right format so that we could really all all benefit to the maximum from you know what we now see accelerating in the world of AI then there's a beautiful marriage between those two uh movements and that was for a long time in accord of what we pitched and it's gone in and out of favor but it

certainly seems to be much more in favor today so let's talk about the AI thesis uh you know as we were preparing for this I I was reminded that in like 2017 18 there was a moment where blockchain and AI that narrative had emerged amongst you know all the other narratives at the time defi this this Enterprise blockchain uh idea that was floating around in the 2015s to I guess like 1718 area and I remember at the time I remember that narrative just feeling very cringe to to a lot of us folks building in Define permissionless networks and we had people pitch us

ideas for the podcast and maybe sponsors and stuff like people reaching out to us to be on the show uh you know sort of pitching this idea of like Ai and blockchain are the perfect Technologies but it just felt so cringe at the time and to me at least I I didn't see any sort of promise or or or utility in those two technologies merging and somehow becoming complimentary to each other uh what's different now and why is it why is this narrative now making a Resurgence and what what what sort of specific technological advancements perhaps have now made it actually interesting and and something worth looking at yeah so so I guess one of the things I draw from that actually is that that

um we all battle you know Market's High Market's low with the emotions attached to that we also battle with the fact that you know trying to sort of actually just stick to what we believe might be right and trying to ignore the other PE the opinions of other people which might be you know just fighting that instinct of of uh you know U shying away from what feels a little sort of you know cringey should we say um although that being said of course you know and I mean we probably wouldn't get into but ai's got a long history when it the kind of the dawn of the AI AG has been Herald heralded and it's turned out to be a kind of a a false Horizon uh you know going back Decades of course um and I think that you know it's pretty well documented one of the

things that is different has turned out to be different now is that you know just the computational power and the quantity of data available to train then some Innovations in you know the types of AI being you know generally used obviously notably the trans Transformer um style you know llms they um that is really kind of be taking things to the next level in terms of uh the wow factor of anybody using G gpt3 level at GPD 4 um so obviously that is that mainstreaming makes a different on the AI side I think in terms of the kind of the connection between the two I think first starting with the the kind of web

three side of things um you know I think there's often in a sense a similar challenge later the to the feat of web 3 which is like when are we going to have mainstream apps uh when's that going to happen and and and I often sort of get into and go hold on a second can we just calibrate uh you know how long it's actually been and how far we've come you know just take a measure how many daps been built how many developers being involved uh how sophisticated a web 3 stack that's been built and and say best part of 3 trillion in in in market cap that is has kind of been uh sort of generated in value that that feels like a uh pretty impressive and you know that

um that I think that work that has gone in to build a web three stack that it that truly can scale to support should we say native onchain payments uh to to support sort of consumer grade uh applications that has the levels of abstraction in it so that um you don't have to care about which L2 you're on or indeed preferably which L1 you're on um and or or in uh about specific to the naming service of of you know the for mentioned L1 you know I think we we forget about how much um has happened and I think we do does feel like we're at a a Tipping Point uh there and then I think that um all of the work that's

gone into creating the defi ecosystem uh we always thought about those as kind of necessary Primitives or building blocks in that overall stack you know this is one you know this is a the first time we've had a wave of software that has the ability to make and keep Financial promises which sounds like a pretty powerful uh you know tool um and and I think that's where um the marriage with um AI comes comes about because um we've seen and I think really comes about because AI um we've seen how the choke point for that has been the capital required not so much the electricity consumed but the sheer Capital required

to buy the gpus and get them in a timely fashion in order to train uh models um uh there are all sorts of Cho points around um electricity distribution and even generation if you want to have that as sort of native geography that are emerging but but I think it's going to turn down and to to to data um and that you know a lot of the kind of op sourced and commonly available data sets that are of the scale required for llms has already been consumed but there's a huge amount that is still trapped in for example social media and I think famous of you know Zuckerberg said you know we're not training llama 3 on our social data but if we can find a way in which

we can respect people's priv Y and perhaps even reward people incentivize people and reward them for sharing that data um that's a huge Treasure Trove of opportunity and I think we can then obviously go beyond social uh network data to Health Data and and and the like and maybe deeper personal financial data and and so I think that's the opportunity now the maturity of the stack now that is there and then it's the opportunity to use those you know the capabilities of that stack go and use token economics to incentivize the sharing of that data I I think one of the most interesting applications for crypto and

AI at least the one the one that I find the most useful uh is this idea of user owned AI or um where blockchains effectively act as a way for uh users to own their data um to uh leverage their data if they wish to sell their data to um to organizations and and folks building models I think this this this notion is kind of uh also emerged previously in in in crypto when talking about social networks and creating data networks effectively I think I think that's one

of the most interesting sort of intersection of crypto and AI aside from from the obvious you know Marketplace for compute for compute right and Marketplace for gpus which is an sort of obvious uh use case in the case of of of um of user owned AI you given how we've seen web 2 aggregate to very large players and those have become very powerful and and in and specifically in the AI vertical have become very powerful do do you think that it's even possible or conceivable that you know we have user generated AI or user owned AI in like in 10 years that that is even a

a significant enough portion of the AI Market to even matter I I hope it's possible uh it's been characterized by uh Michael Casey and his co-author as kind of our greatest fight um I think it is it's a recent book and and look um if we if we go back and look at it it it's it's clear that the um if you follow the money the the the natural concentrating tendency of capitalism we've seen very evident in web 2 and that this is already you know is clearly further exaggerated uh in uh with the econ prevalence of of or the rise of AI uh and like it's just driven by with cement

again um that there are okay step back a bit the the open movement the ability to share data um the ability to share research that has been the you know the origin that has been the petri dish from which all the notable inventions have have come but what happens unfortunately obviously and we can observe this is that there are a few Milestones reached in that research and the aggregation you know using the benefit of that data and then people close off their models um I think just recently uh fris sh from Google went as far as to say that you know along the lines of open a I has put back Frontier research in AI by several years three four five years since it

closed down through its actions the publishing of that research um and also by virtue of the fact that it has popularized lamp so much that sucking the oxygen away from other uh forms of of research so I think we need to remember the power of openness that's there that if we're not careful this concentrating Force you know um uh you know steals from us um and I I think that at every level of the stack and we would think of the stack as you know uh say say compute data um models talent and governance um you know at every layer there is the potential to use a a token economic driven model perhaps

combined with a new form of Open Source license for the for the models and the and the data that has been generated in order to give everybody a share however that's easy to Corner phrase somewhat as user end AI but there are many components to make that that that happen obviously um and you know I think at each layer you mentioned you know clearly we'll see you know Airbnb for gpus and and we've seen obviously there were great companies like you know um Jensen and protagonist like aash and and and so forth that are out there kind of building things the real challenges there of course of of getting and and it's always I was think of this a little bit as the martini problem I think it's I think it was 70s Martini out is like anytime any place

anywhere or something presentation of a martini but anyway it's it's the how do you get the right comp type of compute power power available at the right price in the right spot in the network at the right time to do what it needs to you know to do that's some of the challenges because there's the difference obviously between training for example High Compu and and and and inference you know a requirement for low latency you know that matching algorithm of supply and demand is very challenging and the same applies on you know on on the data set how do you then how do you get that to work and so that's what what people are kind of are wrestling with but I think this is a watershed moment either we get a bit of a vicious cycle where

everything gets extremely concentrated which I think there are very strong arguments philosophically is a Bad Thing uh power corrupts absolute power corrupts absolutely uh and without getting into kind of you know politics and the last sort of century or so and then secondly um so we can believe in philosophically that's the right thing to but secondly I think we can actually believe that um and I've been TR try thinking of the best way to kind of articulate this but because I think we've we've not seen it yet sort of win out we were an early investor for example in Ocean protocol which was looking to kind of Mari um you know create a data Marketplace and one

of the key things is that that that there is kind of No Easy Marketplace for a large Marketplace for for all types of data it's it's always about kind of very specific data in a specific tinier more you know more applied marketplace where the value is and then you have to be able to negotiate the value of the data at that point in time and a lot of companies that build software effectively are are doing that negotiation on behalf of that data set so we need to create something that's similar to that that allows for those collectives that own that data to to negotiate on the fly or the promise of the value of that data in ADV in advance and I think that's a it's area of research and of invention for I think

kind of for Founders and and and what that is in my mind's eye is a rather than this is a crude metaphor but kind of rather than saying we're going to concentrate everything around the Ford Motor Company and there's going to be one type of car and it's and by the way you can have any color as long as it's black and it's going to you know the the production engine is going to be fed and and the profits going to be concentrated like that what we need actually is is to ultimately end up with and I said it was you know a metaphor and analogy you want to end up with having all of the different variants of vehicle you could possibly imagine that fills out all of the utility curve um uh that that that exists in this in this space and we need

a much more adaptive um organic uh type of system then you're going to get from something that's command control and centralized and and and so forth and you need I think what you can get from all of the great work that's been done within the web 3 uh community so I think technically it could be much better than the the centralized alternative however if we don't find a way in which we make it economically better and not just economically better in the long term but in the short term for small groups of people you know to your point Sebastian it might be hard to win um because the they kind of follow the money forces are very

strong so that kind of covers a lot of the decentralized ownership aspects we've also seen projects and we ourselves at nosis have not been completely innocent in this at actually putting agents on chain right so in the beginning we did things like we said okay this is a prediction market I'll give you 10 die um this is how it works trade on it sort of thing but actually we've progressed to the point where we can just you know spin up an agent on chain and say here you have 100x make me some money and the the but goes out and does just that so um obviously there are very real concerns here as to how wise that is right do you want to put something that um that in principle

could compete with a human and have different set of things it optimizes for um on a chain that you can't turn off um do you have thoughts as to that Richard I mean I think look at I'm I don't fall into the camp of the uh there suddenly being um an acceleration towards the singularity um uh when these things um start teaching themselves um and and that happens overnight that being said the the ability to to teach itself an agent or a model to refine itself um you know that kind of second derivative that

is something for us to watch out for you know I think uh Mustafa suan for example would be kind of a in agreement on that and um but you know I will leave those those deeper elements of the kind of the precariousness of the of kind of the AI gift to th those who are focusing you know fully on it I mean but I will um I will say I guess where it comes up is do we want uh you know closed AI let call it that owned by corporations and governments with the choices made possibly by a very few people who who um uh who who has that power and who can harness that power or do we want something that is more openness open and

inspectable I think I give for the open and inspectable and wide widely distributed option and that you know maybe we even reach a point where we are in a dynamic equilibrium of of of mad as they call it of mutually assured destruction uh with with these things maybe that's some kind of end point we reach but but look you know knock on Words it it seems to been something that has actually in some respects at least helped out in the context of you know our transition from the kind of wartime second war time Cold War and and this sort of nuclear destruction again I'll touch for it a couple more times um so but but but I guess on the on the question of you know

do we want to give effectively kind of persistent or autonomy to agents on chain that can do things it feels like it might be uh fine and and indeed unless it can teach itself to adapt into something that you don't expect um and maybe that the problem is we don't know in advance whether that's going to happen I think it's going to be quite hard to predict what's going to happen with with markets I think they're going to become sort of increasingly you know uh uh perfect but maybe they're going to become increasingly volatile as as as well um and then I think um I I think that the other side of the the impact of AI on web 3 uh that just a very specific

one is that if we look at the way in which AI co-pilots are tracking and their ability to create applications that we're going to go from a situation where there are sort of relatively few solidity programmers and it's incredibly hard to audit U smart contracts to a world where um actually you know and we need to watch out for this that the vulnerabilities are possible to spot using AI perhap but obviously therefore we can use it to audit them and indeed it's possible to use multimodal um developer co-pilots to create you know a complete the complete stack of front end decentralized front ends middleware and smart contracts poor um you know uh whatever you know might

be some kind of whether it's a gig Marketplace or a um you know whether it's a a decentralized exchange of some description um and therefore the the kind of community strength that some of these l1s have sort of starts to fade into the background so I don't know what you've been thinking about um on that par particular topic Fred because you seem to be nodding your head a little bit that it's it could it could change the Dynamics the competitive Dynamics quite quickly yeah no I completely agree so I I totally see the dangers I think stopping is not a great option because because we can't force everything we can't force every every participant to kind of stop right so

kind of I'd rather we we with kind of like hopefully good intentions um are in the mix as well um because otherwise if you say oh this is a little bit too dangerous for me um if someone else continues that does you no good um you know in in the larger sense absolutely certainly there are people I respect on the ai ai side including Nathan bench um at Street Capital and um you know folks um uh you know who have commented that obviously the human cry around you know let's uh let's slow down on AI let's regulate it is a kind of classic form of kind of regulatory capture uh by you know big Tech um and you know it's self-

serving to say slow down if what you're doing is meanwhile you know having a hearty breakfast and getting ready to Sprint into the lead um you know you know uh so so I think uh yeah I would agree I think we need to we need to keep going and as many people need to keep going as possible um and it's ultimately going to be extremely hard to put the K back back in the bottle but I do think a lot of the principles around transparent you know uh you know governance decentralized governance incorruptibility of various you know points of governance Collective ownership modern mutualism if you will it's one of ter we like um a good principles you know and and in some from

web three to apply to Ai and like in some senses you know um you you might might think that it's hard to imagine of a bigger use case than in Reinventing money and the world's Financial system but actually sort of rein you know Reinventing you know and I think you know crypto still has this opportunity to reinvent our our relationship with our personal money but actually what's going to happen with AI is we're going to reinvent our relationship with the use of our personal data um and and I think the freedom to you know to have that personal relationship that direct relationship is like effect effectivly a human right um and but not just a human right in a kind of a kind of um it's

nice to have but but essential for the kind of balance we want in society yeah I agree I think uh I think the next 100 years years and maybe even less you know we'll we'll we'll see like tremendous societal shifts caused by AI um and and we need to really think as a society how how the data uh is used and and also like how the AI um is kept safe sort of aligned with our objectives as a species and um doesn't cause chaos which is a total order but um yeah let maybe shifting gears here a

little bit what other interesting Trends are you seeing in this space and I I'd like to ask you a little bit about defi because I mean like there's been tons of innovation in defi over the last you know four five six years uh but it appears as though Innovation is slowing down a little bit there's not very much that's sort of new it's like a lot of re uh rehashed ideas and optim optimizations uh do do you see D5 have we reached like the top or or or is there more Innovation to come in by way of like uh new types of applications that you know really redefine um our interaction with Finance so I think we're nowhere near

the top I think but I think that um that realizing that um the capital that defi can handle is not just your financial Capital but your Social Capital um and and and different um uh and that you know decentralized applications are going to be intrinsically social and they're going to have the ability to to also handle uh transactions within them um and how those all get intermingled I think is going to be the the the opportunity I mean we see people looking at building decentralized exchanges that can handle not just you know funable also but various combinations of non funable token um so I think that there

is um opportunity in that direction and I think you'll we'll see a collision between um should we say um ai's hunger for data decentralized social media and a way it it gives you the the ability to you know mint data that you own and defies you know ability to uh create marketplaces um and and I think that there's an intersection there that's very valuable and you're and also I guess it's not if you think about it's just not not just content data it's also things like Health Data so if um and we've seen how defi can you know and the

World Casino that we sort of once the you know the web 3 has sort of stumbled into um can be incredibly sort of good at at creating these highly liquid marketplaces even if it is with money that is quite hot as in it's there while the going is good and then it disappears and I think sort of one of the next challenges is to how to apply that to data sets that are actually where the the kind of value is less um you know volatile but you know that there's uh for example sort of Health Data it's more long lasting but you can use the principles of creating liquidity and and bootstrapping marketplaces that we've learned how to do on the defi side and and and have them kind of per permute

across so I think in a sense defi hopefully will become useful by being applied as a primitive as a building block to the applications and Market places we're trying to build and then in that way we'll see it become much bigger and I also think on its own legs I mean like I guess we could ask ourselves a question you know do we yet have an app and I think by the way as a sort of sidebar we probably feel the apps are disappearing but do we have you know a sidekick you know set of experiences continuous sort of streaming application experience that is sort of tuned into the value that we have and all the data that represents our credit score and that continuously surfaces for us um from you know

a a financial marketplace where there is you know not human intervention um and presents it to us for for whatever opportunity we're looking at at that particular point in time well that's not happened yet and that seems to me the the kind of the core still the core open finance or decentralized Finance opportunity and a lot of the ability to do that is only just um is any just coming to pass you you're talking about sort of this emerging use case of uh digital asset managers that make use of AI agents uh to find like sort of optimized positions

for one's portfolio that that that kind of use case yeah it could be optimizing the positions in your portfolio but it could just be be saying you know uh like I'm I'm going to buy some clothes for delivery tomorrow um I'm GNA um I need to use credit for that maybe I have free credit maybe it's only two days if I sort of s I'm going to return it but but to to negotiate the credit for you you know automatically in in the background as part of that transaction um also simultaneously of course like um capture a tokenized set of you know um uh information about that interaction that becomes attached it's part of your kind of data exhaust that becomes

attached to your profile which then in turn feeds feeds into a future possible offers of credit you will you'll be given sort of instantaneously next time uh you need to do that or indeed not just credit um incentives loyalty or whatever um I think that the the the Loyalty space w which was something I remember looking at a company called aom Matic best part of 15 years ago um which was looking to kind of use your transaction data across all of your different accounts to give you better you know loyalty you know we surely we want to get to the point where all of the information you know around who you are and how you transact is used productively for you hopefully um to you know to to give you the offers and the

loyalty and and so forth that you want and then on a kind of permissioned basis you get those offers that that you really you you care about rather than having a ad Revenue driven model that's sort of inbound it's more kind of permissioned kind of permissioned marketing that takes place so I think all of those are you know open Commerce open loyalty open payments uh you know and the mar the the defi marketplaces behind them they're all interwoven and I think we have have barely got anywhere with respect to those so far and there and within that is the kind of you know real world asset Maring to any concept that exists today um you know with that world is is um is tricky and

and the reason why obviously it's easier in the kind of World Casino cases when you have a fundable asset and it's all natively on chain and you're staying on chain that's the easiest place to get those marketplaces going um but I'm sure we will get there yeah so I'm speaking about Trends here maybe looking back in your uh Journey as as an investor in the space which which Trends which notable Trends uh did you did you see over the years that you you thought would play out like you thought would become a larger part of the industry but in ended up not and um you know what did what did you learn from uh from

those yeah I mean I think I think um we I just mentioned one which is I think the the Loyalty was one that we thought would uh there was a a a payments and loyalty company that we incubated that was Web Two called yo-yo I I remember trying to pitch my my partner ala fiz to make take that on chain back in I don't know 20 14 or 15 or something and um and you know none of that has is taken off as quickly as it might again you know it's I think it's really a a question of time timing rather than anything else um I I think that onchain games is another one that that that obviously I think has

got challenges to to take off and a lot of people know investors in cartridge a lot of people are doing a lot of work other firms like ltis and so forth to um to build the capabilities to make that work and have sort of AAA standard games that that um that can operate scalably kind of you know on on chain and indeed to to kind of allow people to own not just sort of uh buy um the various artifacts in those games and then build kind of sustainable token economies rather I think yeah I think the jury is still out on gaming it's yeah exactly it's not it's not it's not it's not happened so I think that's been on uh so I guess we've been impatient for that that take off I think um so I've always been bullish also on just generally the

power of token economics which I kind of mentioned earlier I think is an essential part of how we try and avert sort of sort of massive Cal or acute centralization of kind of AI systems but and and I think um uh I I do think that there's still a lot of work to be done to work out how to um build resilient sustainable token economic models and to Value them uh through different know stages because I do think it's fundamentally different from you know discounted cash flow quite linear economics of a centralized company versus the self rein forcing effects you get in something that is more akin to a city or a forest and it's

got a lot of all these different emergent properties uh and that that arguably or at least we would argue can be rather than inevitably going from kind of productive to extractive is is you know much talked about in our kind of sphere uh can be you know when we get that kind of platform power and platform risk can be uh more positive some game uh and more sustainable the longterm I think that's an area that we I guess I expected us to advance a little bit you know further in today but and but I think it's still still to come I mean we we were back as of um you know sare back in the day that was one of the ideas that that that was kind of elegantly simple and sort of was almost a kind of a a trite example of what would be

powerful on a kind of blockchain and uh has has gone well shout out to the Strat of Mafia here you go um and and then um I think uh one one that we missed I guess this is a little bit to do with a little bit to do with actually trying to apply a more typical Venture Capital approach to the space was that you know in venture capital in general uh in the sort of famous case study of this when um was it when when a6z backed bourbon that became Instagram and also pick please if I remember what it was called you know and then they ended up on a kind of collision path and obviously Instagram was kind of the the winner um you know that that VC's can only um can only back one player you have to pick

uh you know something to partner with and you're really kind of full on with that whereas I think in the kind of obviously l1s l2s and and all of the space a lot of a lot of folks have backed multiple different players and then there's been enormous the opposite direction there's been enormous value generated and possible returns distributions for Venture investors from a whole s of those l1s and l2s so that's been a bit you know I don't think everybody predicted that there would happen that it wouldn't all kind of become an ethereum game quickly or you know or some new you know winner uh and and and so forth so I think that that's been not NE I don't think anybody C well I we could chat to someone who said that they called that um but we but we we

didn't you know play right across the field like that so that was also kind of should we say a missed opportunity in that sense are there any specific felds uh where basically the company pitched you and you uh passed and wish you didn't uh I mean look there were definitely I mean at the top of my head there were two two companies that that um I by the way I can I'm I'm very bad at immediate recall of these things but the two ones that are that are on on my head is that you know we have a lot of time for the team at Jensen um and and we when we first saw them they were more enterpris and focus but we became decentralized and more more um uh you

know we think they're doing great things and and and and I guess the bit I'd like to emphasize is that in you know in talking to to them and to the founders B and Co that they um they're just very impressive Founders and individuals and that's a huge thing that we kind of you know index on and you've got to be very careful to to um to not talk yourself out of some of the challenges in these companies and then another another one um that we should have dug into more um probably is is lazy Ledger that became Celestia um uh where Mustafa actually um we had a discussion about him Jo joining us uh in a very early when he was still

at UCL so we knew him and we knew other people in the space but that that didn't happen so so and and look we're um as as already been discussing like kind of should we say deep in and deep in for AI and you know we we think that's an important part of the future and interoperable modular open blockchains you think that's also an important part of the future so so so we definitely kind of do was on pieces well I'm I'm going to I'm going to now spend the next few minutes that we have here asking my own selfish questions as a as an emerging uh manager of a VC fund uh so yeah the first thing I wanted to ask you is like you know crypto uh crypto valuations obviously

have um have a premium and that's because of the low time to liquidity something what one of the reasons at the same time you know VCS present themselves to teams as long-term aligned and like long-term supportive do you think that there's a a contradiction there where you know short short-term liquidity and the way market Cycles operate and it forces you if if your hand hit is as a fund to return cash to your investors return Capital um it is is the is the short-term Horizon of uh of of liquidity in crypto counter

to what a what a fund should you know in theory be providing to a team is also like long-term support um yeah how do you think about that and and specifically when it comes to exiting liquidity yeah look I mean so it's definitely something we've been wrestling with for six seven eight eight years um and obviously look it's a new frontier and so therefore there's no reason why it should there should be a um a an well understood or you know a quick or easy kind of answer um and at risk of kind of giving a kind of it depends or somewhere in the middle answer um I I I think that Venture firms should be you know Venture backers

should be thinking for the long term and backing those projects for the long term you know I think there's there's clearly a segment for which that makes you know total sense um I think and that makes sense for the uh for the projects because they want to know that you've got their backs through through thick and thin um you know there have been a you know when it comes to the question of when to sell um you know you you also have a duty obviously to your your limited partners to try and deliver returns and when you come to raise your next fund uh you're going to be ask where your distributions are so that there's a pressure on yourself uh to be able to achieve that that's definitely easy easier said in a sense than than to do for for a few

different reasons well number one that tension with the long-term interest of the project so I think what we try have tried to do is that is to you need to have that relationship with the project to understand how they are hedging and in some cases it may well be the case that they need to hedge uh they should be sensibly hedging their own uh treasury in order to you know provide for the a solid basis for you know the long-term sustainability of the project and certainly it's fair if there is that hedging going on for you to perhaps be doing similarly hedging your position at that point in time but that obviously involves a dialogue and historically mve that dialogue has not been not been there I think it you know it's there in

the future but it is a difficult difficult Dynamic to manage because projects may not want to talk about the fact that they are hedging um because that itself can have an impaact on on on pricing I mean there's another Dynamic for um for Venture investors which is that uh it can be said and it has been said that it's actually easier to buy than it is to sell um so you know so backing a great project and getting in uh is one thing but knowing when to decide that it's it's time to to to get off the the train um can be very hard as well because you think this there's more to go and then afterwards when the Market's coming down you can feel like

you're trying to catch a falling knife and whatever you hesitate so it's um so I think that muscle needs to be exercised there needs to be discipline around that so it's a different reason in which it's can be difficult to get the get it done um so you need to be sympathetic to the founder of the project be integral with it and then you need to um uh actually have the the the discipline internally the processes the people the the numbers the dashboard what to think about it and D structure it and I think it probably comes back to the fact that expectations are always key um if you can be as is a backer you could say look I'm with you through the Canin but if there is go if there is a point at which the market you know the liquidity has occurred and you've done

extremely well um uh with the with the kind of token price then it might make sense for us to hedge our position and this is how we're going to do it and we'll make that collaborative and so forth so I think communication and expectations be be crucial for making sure you remain aligned with with the founding founding team yeah that's helpful and I think uh yeah essentially you requires a a measured approach and and also proximity and communication with the founder uh that's helpful and one one other thing here like you know you you guys have to look at so many deals over the year like possibly thousands of deals uh invested in more than a hundred um uh what what what are the criteria that you look for

so like when a deal comes across your desk what are the main like three things that you look for that you know will will will jump out at you as like this is a potential 100x is it is it the team or is it weighted more towards the tech or or um or like really true product Innovation what what are the the main things that will jump out and you know cause you to say like okay this is a priority and like we should pursue this as possibly like you know going forward with this yeah I mean so so clearly this is a topic that comes up you know with in many VC oriented uh um should podcast or or conversations and um and and for

me at least um uh if you're talking about early stage investment uh at the end of the day it's you know just the team the team the team I mean it isn't because you need to see some evidence of um how they're thinking about their initial product offering is this a clean sharpened assertion Point that's going to get immediate traction and give them learning um and is that elegant in the way they constructed it and you need to see evidence that they thought about maybe not the initial Market but how they can tack to a you know to creating even a phenomenally sized sort of Market over time um but in a sense those are just evidence points that the team

you're talking to are just incredible they're not it's you it's not necessarily the answer you know the specific answer it's the it's what's gone into generating that answer and the fact that that indicates that they'll be able to come up with the next right answer when new data represents itself and they work out what to do and so so for me that's the the the kind of crucial thing I think one of the things to kind of to kind of to to get your head around as Al stage inv investor and and my friend FR Fred D I think he called his blog post he's he runs stride um you know talking about how I learned to get comfortable with risk in a bracet or something like that you know and it is it is about getting comfortable with

how how much risk there is and in fact particularly of course if you're building a venture portfolio we are actually looking for Investments for projects that are taking more risk that is than is reasonable for the founding team to be taking on a standard L basis because we we want every every single time that project to be really swinging to be totally extraordinary in the outcome that they produce um but it's not just risk it's also a kind of form of messiness that that I think can exist so and another actually thinking about it you both have these teams that are incredibly capable uh and and and have thought things through and can evidence that um but at the same time getting

comfortable um that there's great risk uncertainty and even messiness at this at the early stage of of those outfits so if if you if you if you I'm I'm actually the question is what you're maybe not looking for if you're looking for everything to be buttoned up then and if you're looking to ensure that you can then feel comfortable that that that things at the end of the day aren't going to go too wrong that's the wrong thing to be looking for we're looking that if a whole series if the sun the moon the stars and the whatever you know some other Celestial body kind of line up then how if that all happen how incredible it could then become that's what you're already uh attuned to but back back actually makes me think of

another point on actually quickly on this element of liquidity which is different and distinct for for uh the the few Capital allocators uh who are out there R you know putting lots of money into Venture at the moment in the world let Lear in Europe because we still do have a bit of a dir of that um looking forward to some interest rates rate costs um but the um but the the other thing is that the we've observed is that because of this kind of or organic more City likee uh positive sum setup of these networks that get built where you know to take the canonical example we don't know who Satoshi is we don't know who the founder is you don't have some key risks it uh that you might

have in normal startup projects and so that actually The Fallout rate the kind of Fallout the kind of go to zero rate is lower than you would see statistically from normal kind of startup up S um because of that kind of open collaborative communitybased nature I would I would posit um of of these projects and so yeah you got you got the earlier liquidity you've got the lower Fallout rate but you still nonetheless if you really want to deliver exceptional fund level returns need to be uh you know swing for the for the fences as the as the the proverbial phrase goes well thank you so much for that that's uh great insights and this has

been a really fantastic conversation so Richard thanks so much for finally coming on the podcast um hopefully we can get you on again in less than 10 years and uh yeah we'll we'll catch you soon well well thank you I I plan to still be uh building Fabric in 10 years but let's not leave it 10 years thank you thanks Richard thanks guys really really enjoyed it thank you very much