Podcast Transcript: CoinFund: picking the best investments in Web3 with Jake Brukhman

I’m Piers Ridyard, CEO of RDX Works a core developer of the decentralized finance protocol Radix a public Ledger entirely focused on bringing DeFi into the mainstream this is our podcast the DeFi download a show about decentralized finance and all things crypto where we dive into the details of the projects assets and services that are driving the DeFi Revolution today I'm joined by Jake Brukhman founder CEO managing partner of Queen fund coin fund is a crypto native investment firm and registered investment advisor the team specializes in portfolio management token design decentralized networks research trading Market Structure engineering's brand strategy law and regulation Investments have included Dapper Labs upshot the graph balancer and fuel Labs Jake thank you so much for coming on the show hey peers thank you so much for having me happy to be here so I think that would be interesting I think it's always interesting to hear like how investors got into the space like got into the job of investing as well as like how you came to found coin funds so I'd love to like just hear a bit about that of course so my my background is in mathematics and computer science and you know I'm generally like a pretty dual brained guy like mostly doing tech for work and and doing a little bit of like art and stuff on the side which by the way is one of the reasons why early to nfts because I'm actually a digital art Creator myself nice I my career for about 10 years or so was mostly in fintech and I had a student pure Tech at Amazon where I was a technical product manager and engineer and my parents were technologists on Wall Street so this idea of like marrying technology and finance was always you know from inception you might say like on my radar yeah so when I when I saw kind of Bitcoin back in 2011 and then subsequently ethereum in 2015 you know I it's really like this intersection of of finance and Tech really spoke to me and it was you know I was following Bitcoin for for a number of years but it really wasn't until vitalik's white paper for ethereum that that there was like a light bulb but wait a minute this is a new digital asset class and so as a tech person my first inclination was like if I want to work in this space full time maybe I should start a tech startup but it was also very obvious that we were so early in the Innovation curve of blockchain technology and there would be so much innovation and so many technologies would be obsolete before we got it got to the right answer by the way we're not done with that process quite yet not even close that it became obvious to me that I should become an investor it was always an interest of mine I was always like looking for alternative acid classes to the best that I was doing like like peer-to-peer lending back in like 2006 as a form of investment but I also wanted I didn't want to forget the text side like I wanted to help build these things I wanted to be alongside the founders as they were doing it and so coin fund was a way for us to you know help blockchain technology develop get adopted and practical responsible ways but also be an investor who was hands-on helping to build the things and and helping the founders achieve like a longer term success than what they were doing so that's we're now seven and a half years full-time investors in in blockchains our seven year site anniversary congratulations I like the story it glosses over some like clearly tricky bits right because like the first thing being like I decided I'm going to be an investor like being an investor is hard right you've got to raise funds you've got to get your you got to get your first I mean it's like it's a lot like starting a starting a startup in some ways is you've got to convince other people to give you money to build something that will deliver them more value than yeah so so you bring up an excellent point I'm happy to like double click on that for a second so my last job in Trad world was this was the CTO a CTO basically you know an alternative data company and what that company focused on was studying private technology companies prior to them going public and really doing it in a very like data-driven quantitative way right so we we do things like you know we look up like all the publicly available data about for example Uber right like we'd you know we'd look at all the historic rates What cities were they and what time how many taxis did they have registered in New York because New York keeps track of that right and we would like really like go down and really understand deeply technology companies and this was really like the precursor of me getting into you know early stage Tech investing but you're totally right like as an engineer I'm a quote unquote like fake investor in the sense that I became an investor like through crypto and learned everything that I know about it you know by actually doing it and so how did you get like what was the what was the first money into coin fund was that your own capital and like a friends and family or did you go out and actually get some initial like bigger LPS from people that you were pitching even at the start no I mean it was impossible at that you know in 2015 first of all there's no institutions writing checks whatsoever right into this space you know High net worth individuals were incredibly skeptical and thought this was like probably a scam and so our first fund was was very much friends and family money like my dad was the first investor in you know besides myself a bunch of our friends from from Brooklyn and some some of the early folks who later became you know important let's say co-founders at coinfund were investors in that first fund but it was was you know it was a small thing it was an experiment and you know it actually Remains the best performing coin fund quote unquote today so what was the what was the what was the total size of the fund one and then what was the what was the ROI it was less than a million bucks let me put it that way yes okay yeah yeah it did like so far it's actually still being liquid but it's then like 40x cash on cash and still has a bunch more juice that's amazing So like I think also really inspirational right like anyone who's thinking I can never I could never like build an investment fund I'm super interested in investing it like being early and having high conviction is clearly and and getting getting some other people to believe in you I think is a key part of this as well right getting other people to put money in even if it's friends and family even if it's just like a small number of people that also changes your perspective I imagine on how you're investing how you're thinking about allocating capital I mean I would say that in those early days we're very much in in learning mode and the idea was that there was a bunch of opportunities in the market a lot of the opportunities were like Highly Questionable some of the opportunities were what would go on to become you know incredibly large things large networks you know have in insane returns right and the idea in those days was to try to get to the truth of it right to apply the scientific method to give every project a chance to evaluate it on its technology and its merits on its team you know and and again like that meant that that fund was very early in ethereum in Bitcoin in some of the kind of early attempts to create you know what we have called daps so for example you know one of our first Investments was auger which is it was a decentralized platform for for prediction I mean I know I know you guys have been around like through that period because right you know I've known your name I've known Radix for like many many years and we actually spoke on the phone like back in must have been early 16 or something like that but wow yeah yeah and and so you know it it was a learning it was a learning mode and a lot of things about the market change a lot of the quality of Founders I think has improved a lot of the processes have become standardized you know and back then we were kind of you know pretty much the only crypto fund and today there's hundreds of them so like looking back at that time that history obviously for for a traditional investor there's the the three things that generally talked about which is like Team technology and traction for early stage early stage two mid-stage Investments what what are the patterns that you see in crypto that you just don't see elsewhere and that you guys look for in addition to those things I mean this is an excellent excellent question so like at some point I published a blog post which literally is what we look for the nine core value propositions of crypto networks and the idea is to just speak a little bit to our core thesis right and the core thesis is that to answer the question of what can blockchain technology do Beyond just cryptocurrency beyond just Bitcoin I mean I think that I think that the general answer at this point you know seven and a half years later is that they is that blockchain technology can create open public permissionless decentralized user-owned and user governed networks and essentially those are public goods at its very base what this shift is is creating a new way that products and services can come to Market not necessarily just through a corporation which is hierarchical and as a CEO but also thinking about you know can we do this in a more distributed way and by the way the results of that experiment are definitely like mixed it's not clear that you know hierarchical organizations aren't the best at producing products but what blockchains do better than corporations is things like transparency security ownership Capital formation and like all these like really competitive angles that can be used to compete with traditional companies and so to answer your question what we look for like what fits into the crypto mandate for a coin fund investment is a gamut of things like on one side of those of that gamut is a very decentralized network and on the other side is a very centralized technology company with Equity but what they all have in common is that they use some of these value propositions of blockchain Technologies in a way that they can compete with whoever came before and that's the thing that we're investing in and this shift to like a different operating system of of doing things that's really interesting you you guys are also looking at the overlap or you personally looking at the overlap between crypto and AI and for me I've always been quite skeptical about that just from the point of view of it feels it like there was a lot of projects I mean just going back to 2015 2016 there's a lot of projects that tried to mash those to almost buzzwords together and a lot of the time it is like when you looked at it it was only skin deep so what what are you seeing as the insight or is the thing that is going to make the overlap between crypto and AI work from a like deep value delivery point of view openness is the short answer right so if you look at how like AI is not a new field I mean it's obviously been around for decades it's not a new field even in terms of kind of the most up-to-date models that we deal with you know deep learning and and some of the models that we're seeing play out right now these are all things that have been kind of coming to market for for 10 years there's multi-billion dollar Enterprise AI companies right now right this is not a new field but what is new is this idea that you know every big model that came well I should I should take a step back so one one Innovation that's happened like fairly recently is that people started creating these like larger more General models that have turned out to be better at specific tasks than specific models made for those tests and we call those Foundation models and an example would be like Dolly too dolly two just went and learned all of these images and now it can translate text into images and this is what's called generative AI this is the hot thing right now everyone's creating AI outputs everyone knows that it's not just limited to images it could be videos it could be 3D models it could be audio it could be podcasts one day you watch out Piers right but the point is that these models because they're so big they require you know like large amounts of computation sometimes to the tune of you know a million dollars or 10 million dollars or 15 million dollars they are for the moment they're kind of like in the realm of proprietary big tech companies these are the people who have the AI Talent who create the models they have the best clean data sets they have 50 million dollars to blow on a neural network computation and training right but what's happened like literally in the last couple of weeks like maybe last two months or so is that a company called stability AI is has created you know what is essentially an a dolly competitor but that is more efficient and it's open it's source code is open its model weights are open people can refine the models people have optimized the model so now you can run it literally on your desktop on your Mac M1 laptop right and what we're seeing is that the effect of this openness is that the innovation in AI is going like this I'm making a a hand gesture which is means inflection point growing very fast right and so like that is awesome but it's also like very difficult to monetize in traditional ways right so if these models are open and and like anyone can compute them and anyone can crowdfund money to compute such a model you know it's not as interesting anymore it doesn't capture as much value in other words in like a lot of the products around these models a lot of the ways that you can use stable diffusion today you know are these like open source ways like you download you know an app on your desktop where you download some some GitHub package and kind of install it on your computer and then you and then you deal with it and and so why I think web3 is interesting here is because web3 is precisely the technology that can allow you to work with open Technologies but can take but have them continue to be valuable right and I have a whole like podcast unless I did elsewhere like looking at you know blockchains is public there's common goods technology right right and so like take a look at a Luther AI or or lay on right these are open data sets that are critical to creating these large models and these open data sets are even used by closed proprietary models that live inside of big companies but these open organizations that create these data sets they're composed of Highly qualified individuals that are you know working in a non-profit capacity or you know they're just kind of like privately funded you know for the common good to do these things but we could do so much better potentially with web 3 Primitives we could do things like tokenization we could crowdfund the computation of these models and then give discounts and early access to the crowdfunder so like kind of a Kickstarter model we can use Dows to create more distributed ownership of open data sets we can use other forms of tokenizations like for example governance tokens to kind of govern what goes into a data set like recently I know I'm going on about this but but recently like a lot of artists have come forward and they said hey we didn't necessarily consent to having our art be used by these models but now what people can do is they can put our name into Dolly too and generate something that looks like our artwork but we never gave permission for this right so there's a whole like AI safety issue AI governance issue that could potentially be solved you know in a web three-way and that's that's what I'm like really interested in and then I'll say like one last thing you know and then I'll and then please ask me questions obvious use cases of web 3 is creating large-scale highly efficient cheap and effective computation networks and we actually made our first investment in this area last year with a company called Jensen AI this is a decentralized network for training neural models neural network models excuse me okay so like I think I get a lot of this right the bit that I struggle with is the Once the model is tricked like the the expensive bit is training the model once the model is trained the the querying of the model and the ongoing iterative learnings is is a lot cheaper and it feels a little bit like the pharmaceutical industry where you as a pharmaceutical company what I do is I spend all of my time looking for a molecule that allows me to solve a particular illness that's the expense a bit the research and development once I've found the molecule you then they then patent rush to patent them to create a monopoly that enables them to retrieve back the money that they spent in developing in the first place and it's that that little bit there that I I'm I struggle to connect how you go from like an open learn open development but then still let the people who invested in that happening in the first place make sure that they monetize the output of the of the final model so that there is a return on investment even if like someone has to pay for the computation that might be the people who are paying speculatively on the expected outcome of that but then how do they make sure they recoup that investment from what is created in the model if the model is open and the outcome is open yeah I mean this is an excellent question and I don't I mean there's a lot of controversy right now like as we speak VC Twitter is tweeting a lot about how you know people are making a mistake investing in generative AI because you know there's really like no clear monetization for this type of thing and you know and so so you bring up good points but I think well there's a few things to say I mean one one obvious way to monetize this stuff is just productization so like right like right now if you actually want to use these models it's very very rudimentary it's you go in you put in a prompt you get an output but the reality is that these models are capable of so much more like you can take by the way there's a product I think it's s-t-r-m-r.com there's a product where you can like upload like 20 photos of yourself and fine tune the the staple diffusion model it's called it's a Google paper and it's called G booth and basically then you have this concept of Jake or Pierce that you could use in a prompt and you can say like peers on a bicycle wearing a leather jacket you know going to the store or whatever it is and it will like generate like a likeness of you there's all these operations that you could affect with these models you can upscale images you could take one image and and and what's called in paint it which means you replace a subset of it you can out paint it you can expand the boundaries of a photograph like infinitely outward right and the kind of the point I'm trying to make is that there's so much functionality here but there's no like good interface to actually like the best interfaces that give you this functionality they kind of look like like airplane cockpits and they kind of need like an engineer at the wheel you know and you know the analogy that I think of is Photoshop right Photoshop right right it's a little piece of software that anyone can write in theory and they've certainly gone to Great Lengths to make sure that people don't fired it but but at the end of the day like they are the premier kind of interface to you know photo editing or if you think about like figma as a premier interface to collaborative creation of like web Graphics or whatever right and so there's definitely like some indication that these tools can be powerful and what's different here is that the power of the AI kind of goes like 10x beyond what we were able to do before and and so the person who creates the Photoshop of AI you know is potentially going to make a bunch of money yeah I mean the the like back of the head opening moment that someone said to me for AI one day was like in the future like the desktop of the future will be nothing but a text command prompt and everything will be built for the sketch that you need like you go I you know I want to I want to write a letter and you'll get like the perfect little right letter writing piece of software that is just there for you to use that and then and then you go like whatever like you don't actually have the concept of programs that are mass distributed anymore you just like you just the thing I need I describe the thing I need and then I use the thing I need and whatever the best tool for the job is and I think that like the ability to the through natural language the ability to create a close-up communication between what it is that someone desires and what the computer is able to facilitate in matching that desire is incredible and for me the thing about that I'm really interested and like I'm starting to see potential path forwards here is like how the generative AI and creative Ai and these algorithms result in assets that actually have value at the end of it and like nfts are a great component of that and I know that you look a lot like nft financialization so like what does what does that mean to you how do you think of nfts as an asset class and how do you think those are going to expand and continue to be more financialized great question so I mean historically right digital assets really like all assets but let's focus on the digital assets they're kind of divided into these two subcategories fungible assets and non-fungible assets budgetable assets are things like tokens currencies equities you know things that have units that are inter operable with each other substitutable for each other and non-fungible assets are the things that are like singularly unique and are not substitutable for for others such assets so that's kind of like your house you don't necessarily want to switch your house with your neighbor house because they're not the same house they're different one could be bigger and so forth and if you kind of like look at the if you look at the kind of the set of Assets in the world what you what you start to realize is that like actually most assets are non-fungible like there's only like 5 000 different kinds of stocks and the stock market and there's only a handful of currencies right but the number of like goods and jewelry and housing and cars and other like assets that very much outnumber fungibles and so right historically of digital assets fungibles were the things that were liquid and non-fungible things that are illiquid and fungibles are liquid because they have this familiar mechanism of you know the exchange microstructure order books right that enable them you know together with coinbase and binance and and the rep and and kind of decentralized exchanges as well you can fairly easily create mechanisms for fungible liquidity and a lot of people in the space have looked at non-fungibles and they said look this is always going to be a kind of a less liquid asset class because in order to create liquidity for non-fungible what you got to do is you got to like put up a you know a for sale sign and you have to find a counterparty that's willing to transact with you give you money and you give them you know the asset and that's how you create liquidity now I mean that's yeah I mean like like let's look at the history of finance a little bit and like just like I mean clearly not right right like the that position because you there's there's a few interesting things that we see in finance right from the point of view of like coffee or rice we've taken things that actually were kind of non-fungible and we created like fungible categories within them to make them tradable as like the middle ground where you can go this class of thing is approximately this grade so we'll just trade those as that great diamonds is another example of that but then non-fungible turning non-fungibles into fungible Financial assets like look at securitization look at like packaging up credit card loans packaging up mortgages all this kind of stuff that that happens a lot it's sorry like I just when people talk about this idea that non-fungible assets are going to be less liquid I get a very exercise because I'm like no it's definitely not right right well well I so I'm with you and like the reason that I arrived at that conclusion like within digital assets is because we saw how you know crypto economic mechanisms could create a bunch of liquidity and so we saw that in fungibles like a couple of years ago if you had a token and you actually you actually might might know this since you had a token a couple years ago it was very difficult to get that token listed on an exchange it might take a year it might take an opinion from lawyers it might take paying binance you know some large sum of money and then what happened in 2020 was that Dex is really came to Market and they came to Market because of this thing called the liquidity mining program and what that means is that people would allocate tokens and token supplies that compensated liquidity providers and suddenly we went from a world where it took a year for a token to become liquid to a world where a token could become liquid with a couple of million bucks of daily volume like literally overnight right and it's just it's just a different level of efficiency now having seen that then you look over at nfts and you say wait a minute if we can do that then what's the mechanism that makes nfts really liquid and the conclusion that I came to and I wrote a blog post about this and must have been January of 2021 it's called appraisal games and the nft liquidity problem the conclusion that I came to is that you just need one basic primitive and that is the ability to appraise you know this like kind of non-fungible good and that seems like a hard problem like how do you do that well it turns out that machine learning is like really amazing at that it's almost like built for foreign machine learning models they'll take a bunch of factors about nfts how big is the series who's the creator what kind of sales that they have in a series what kind of sales the Creator had before how many you know YouTube followers and Twitter followers and social media followers that they have you know have like did they did they sell something for a large amount of money before like are people it just like there's all these like quantitative factors that machine learning models are amazing at crunching and turning into an output which is kind of a plausible price for an nft and this is exactly what is the subject of our portfolio company upshot.xyz upshot is a you know essentially a pricing mechanism using machine learning they price almost 12 000 nft Series today they price it with like one giant machine learning model and once you have that pricing primitive well it's still not quite real but what happens is it gives market makers this Anchor Point they're like here's a plausible price not just the floor price of a series but for every individual item in the series and what we see with floor prices is because these have been the only kind of pricings so far is that there's a lot of market makers that transact at the floor pranks but when these data feeds of reference pricing in general come out that market makers will be able to create kind of more General strategies for Market making every single nft that's out there and thus they will turn the nft space liquid that's what's happening like right now as we speak so so you don't you don't think that there's going to be the next level of abstraction that you don't think that we're going to go to securitization and and baskets of assets because from the point of view of I suppose you like in in Market in traditional markets you have the concept of like Market risk in idiosyncratic risk like the risk of an individual asset versus the risk of the the the overall Market and when you're dealing with like individual fungi non-fungible items you are dealing with like more idiosyncratic risk in many ways unless you're able to diversify that because you know it could be that let's take board Apes for example right yeah board Apes there there is there there is currently a bunch of things are out about board Apes that indicate that there may be a load of like racist tropes being used in board Apes now that may make some of the board Apes that have those racist tropes in them like much less valuable but the market decides that they're just going to cut that bit out and ignore it and then just concentrate on the ones that don't have those bits in it or whatever like there's an idiosyncratic risk of individual assets that may fall outside of so so then what from a market Maker's point of view that's fine because I'm not taking one bet I'm taking many bets because I'm just buying and selling like a basket of these assets but for the individual retailer investor or the individual person who's trying to get exposure do we not think that maybe we're going to go to more of these basketed approaches via like the correct form of or of as you say like being able to rate these properly is really important as what made securitization possible that's where standards and poles make their money right but like using AI to do that in the more complicated more open transparent way is an amazing idea but is that going to lead to this basket approach where that those will be liquid more than the underlying yeah I don't I don't want you to think that I am excluding like the idea of putting these Assets in baskets or creating you know what I would call like indices of nfts right but I'm just kind of making the point that the pricing the ability to price these things it like without necessarily having actual sales on the market that's the Primitive that enables all of those things right so like like my kind of there's a little bit of Secret Sauce here but like my my kind of way of of thinking about it is you know I can think of a smart contract that using an or a priced feed can actually like make all nfts liquid and so whenever I whenever I like find a startup that's working on a nft like liquidity problem type of a problem that I compare them to that contract and say how efficient are you like relative to that and that contract is very simply a vault or a basket if you will that in order for an asset to go into that well it has to be priced by the Oracle and then a commensurate number of tokens has to be issued in accordance with its price and then if you want to like withdraw you know an asset from from the basket then you got to reprice it again at the time you got to burn those tokens and then you got to withdraw it right and so when you when you create that smart contract where you're creating is a cryptocurrency that is backed by the appraised prices of these assets it's asked it becomes asset backed and so I think like if you create such a contract and this contract is adopted at scale by all the market participants and all the market makers and and everything then you just simply solve all nft liquidity like period but the powerful ones no history right yeah well I mean there's the it's it's the it's the middle bit as well right because a new in you still need the Venture Capital you still need the the people who take that that really early risk on a collection before it's even been issued on a new artist before it's even been issued on being the one that like goes yeah cool I bought I bought the original set and like became part of the Community First and like the community being like key to this like idea before that the asset even exists but yes I absolutely once the asset has taken its first tentative steps into existence and trading the the this this just makes it so much more liquid but that's the same problem that we have with tokens right it's like getting the initial token by a market is should be the hardest bit once it's once you've done that then having it listed on decentralized exchanges and generating liquidity around it has now massively been commoditized and I think that's if that's going to happen with nfts that's that's gonna completely blow the blow I think it'll blow fungible stuff out the water as you say but like do you think when you talk about nft financialization we've started with art yeah like what what is what is the list of the next three things in the order that you see them coming yeah so so so like when you look at the market today and this has been the case now I guess for a little bit over a year or maybe almost two years right like the the predominant and preeminent use cases of nfts is digital art which is how kind of the original nft boom started but then like more presciently like most of the volume is now in Collectibles like you mentioned apes and maybe bunks as well and and so forth and then there's a there's another vertical which is like in-game assets that a lot of people are positing will be the next leg of nft adoption that I'm a little bit more skeptical about but right but it is a significant portion of volume of the gmv today so those three things explain the current nft gmv and at the height of that market call that I don't know like December of 21. that was run rating more than all Global art sales gmv previous years so just on those three categories and just with a couple of tens of thousands of enthusiasts we managed to out gmv the art world now what's next well what's next could be like really like boring things like that you would expect so tokenizing music tokenizing movies tokenizing real estate tokenizing the the deed to your car or something like your title to your car sorry right and then and then there could be like like really new things that we've never done before so that would be like tokenizing blog posts that mirror.xyz maybe it's like a good example of that and I know that people already trade like when you when you create a post on mirror today you have the option of like adding a bunch of nfts of people who just claim or buy to compensate you for for the writing but then those nfts kind of they trade on their own like secondary markets and acquire like a life of their own so I mean that's a fascinating approach right here is a market where first of all we've never turned blogs into assets before but yeah think about how many like billions of blogs there are and the blogs that we have monetized in the past like how many what percentage of blogs are monitors maybe like single digit percentages because there's one and only one working modernization model for that which is advertising and you essentially have to be like a top blogger it's very hard to do that now where you have to work for like a publisher who has that type of Revenue and we're going from that world to a world where you know a writer can actually make money from their work by by using this alternative modernization scheme using tokens or nfts or something like that and to me that is super exciting because it opens up this new kind of Market that has never been traded on the secondary before and you can think of it as like this giant Global public IPO of blog posts and just like whoa and then you know and then and then like if you ask me and if you read our thesis on our blog.coinfun.io there's a post I made in 2020 which is called All Digital content is going on chain the lowest hanging fruit for nfts is as it says all digital content so you know think about icons think about fonts think about clip art think about stock photos although AI is put is supposed to put a dent in that now right right but like like all of these markets that traditionally investors don't really think of as sexy could become quite a bit bigger if you remove the middleman from let's say the stock photo markets and replace it with like a decentralized marketplace where photographers can sell stock photos directly to licensees but because the technology is so efficient it could do that now you know that could potentially be 10 times bigger than it is today right yeah so I think I think a lot of people talked about I think a lot of people talked about this idea of continually talk about this idea of like real world assets going on Ledger like real estate or like car deeds and stuff like that I do think that's going to take longer like it's been real estate tokenized real estate man like I remember that from 2015. absolutely but there's been like an interesting shift right so from like 2015 to maybe like a couple years ago the view was well what's blocking this tokenization as the regulatory Frameworks and we really need like security tokens to come around and then we can we're going to begin to like tokenize real estate and the trend now is actually like screw waiting for security tokens we can just tokenize in a different way through like LLCs and nfts and nfts are actually the predominant way of tokenizing real estate right now right which which makes complete sense I think that I think you're right though that like we haven't really bottomed out the full range of digital first assets that are actually quite easy to continue to tokenize like like stock photography like domain names like you know all of these assets that we think of as as digital first I mean as you say music royalties all this kind of stuff the the last topic I wanted to talk about was scalability of blockchains so obviously you've been around for for a decent period of in the crypto market and you've got you you have seen a number of like scalability Solutions coming to Market and you could we continue to see the congestion on networks and problems with that how do you guys think about the next phase of scalability for public ledgers it's a really good question and I think like in some ways we're in this Quantum superposition where it could go a bunch of different ways and no one has quite collapsed the wave function yet but but basically you know you know and people have opinions on that I'll I'll tell you kind of like what the field is so it's only like a few years ago it must have been 2017 or 2018 or something like neural rubini went up in front of the U.S Congress and was like guys like blockchains don't scale period right so I'm really happy to report that that is not the case anymore we have thoroughly solved the blockchain scalability technology problems with many many different Technologies some technologies that I can name are proof of stake so we just went through the ethereum merge right where we're moving through POS we've seen Layer Two which means kind of secondary networks that settle to ethereum or another base layer and those generally come in two flavors optimistic Roll-Ups which are already in the market and zero knowledge Roll-Ups that are like rapidly come into market for many many different companies we've seen alternative blockchains like I always kind of thought of of your guys thing as you know different form form of consensus and just kind of different way of doing it and you guys obviously are not the only ones proposing alternative schemes you know we've seen Cosmos we've seen polka dot we've seen Solana all these networks make kind of slightly different trade-offs between decentralization bottlenecks and speed throughput efficiency type things Solana gets criticized a lot for being a little bit more centralized in other things but then on the other hand they have you know you you have to give them the credit of having created a community of people who can actually build products that mainstream users can use on top of this network as long as the network doesn't go down yeah yeah as long as the network doesn't go down absolutely and so you know so there's all these solutions that are out there and if you talk to the Solana people they're like you know it's the Practical Way Forward if you talk to the zero knowledge role of people they will say listen we get all the trade-offs but we're making the best one not only is this thing super decentralized and private it's also like really fast and practical to use you're getting all the benefits that you get from something like a Solana but you're also getting the benefits of you know decentralization and and self-sovereignty and permissionlessness and so on you know if you talk to optimistic roll-up people they'll say well we're already in the market with kind of a similar thing but then zero knowledge people will say yeah but you know your network isn't a secure or something like using zero knowledge proofs even though we're a little bit slower sometimes and a little bit more expensive sometimes and so you know and then and then there's every like all the Alternatives and kind of their economics and and Avalanche and something like this so where do I stand well first of all I always have been someone who believes in like a multi-chain like outcome I just think that there's going to be many different types of architectures and trade-offs that blockchains make that are going to be you know relevant for different kinds of applications and so right I see many blockchains sticking around and I don't mean like five blockchains I mean like hundreds or thousands or even more and the reason that I think that is because I do think that like large businesses will will want to run on their own app dedicated blockchains and they'll want to create custom optimizations for how their blockchain works in the same way that their technology teams today create very bespoke and custom you know architectures for whatever they're building like I used to work at Amazon Amazon's back-end architecture that handles you know some insane amount of orders per second is not to be found in any other technology company it's just like completely unique right and completely optimized to whatever Amazon is doing and that's what I that's why I think that there's going to be a lot of blockchains because there's going to be a lot of businesses that will want to bespoke optimize their app dedicated chains and and so like in that world I mean I see a lot of these Technologies kind of like coexisting and interoperating and by the way there's been huge progress this year in blockchain interoperability so right right like blockchain interoperability for a long time has looked like bridges that you sent tokens but what we see now is a market of blockchains that are not just blockchains they're also smart contract during complete computers and what this has allowed is things like layer zero hyper lien right which are kind of more General messaging buses that allow kind of a broader interoperability not just tokens but nfts you know reading State between blockchains reading or calling methods between blockchains and what that amounts to on a practical user level is Omni chain assets like nfts that don't live quote unquote in a particular chain but live on all the chains and whatever chain you needed to live on right and right and and and I think that's a that's an exciting feature yeah I think there's as you say we're in a superposition and like all of these things or none of these things could be true there's the the the the power of networks often come down to their ability to create network effects and it's unclear at the moment whether or not the network effects can be garnered by interoperability effect like fully effectively via interoperability or whether or not like actually transitioning everything to a particular Ledger that's right for that that set of Industry applications is the right and end State and I you know I could debate about this for forever I think it's a fascinating area but it's it's really interesting to see that you guys are keeping such an open mind and all of the potential outcomes I have seen some investors talk about you know if it's not evm or if it's not evm compatible then it's not going to work because you know the the games already like in the later stages because solidity is a standard or the evm is the standard and I think that forgets how early all of this is and how much of an experiment it still is which I think is a is the right way of looking at it yeah I mean I certainly I've heard that view and I understand why people take that view but I think that view really under indexes on things that are not visible in the market that are coming you know like one project that I've been following and investing in for a long time is orbit right and urban has a very very different approach to consensus in general and actually like fills in a bunch of like private consensus mechanisms where you know we're mostly used to public consensus mechanisms in public blockchains and I think web three people like kind of under under appreciate how much you really need that type of mechanism you know in order to actually Implement and and and get web 3 adopted and and for example like on that Network today there is a kind of Layer Two project called Akbar that is settling to ethereum but the the programming language of those smart contracts is not evm compatible it is er it's Urban native and what that means is that if orbit which has a really big vision and an accelerating set of adopters right now like if they become really big they'll just naturally adopt this type of non-evm solution just because it's compatible with their Network so again it you know I think there's a lot of latent factors that could throw a wrench into like the the evm Theory so it's been it's been such a pleasure talking with you and if people want to find out more about you or or coin fund where's the best places for them to go next well they can look up our websites coinfun.io they can look up my website which is brukhman.com and they can follow me on Twitter at jbrukhg Brooke so brukhman.com just for people with b-r-u-k-h-m-a-n.com slightly strange spelling Jake it's been such a pleasure having you on thank you so much for your time and yeah I look forward to chatting you with you again soon yeah thank you so much for having me