How AI & Crypto Combine for Innovation - Niraj Pant | ATC #505

In this episode of Around The Coin, host Stephen Sargeant interviews Niraj Pant, co-founder of Ritual. Niraj began as an investor at Polychain at the age of 19 and has invested in the likes of Offchain Labs, Eigen Layer, and Arbitrum. With an intention to build on the forefront of web3 and AI, Niraj set out to co-found Ritual this year, raising $25M from Archetype, Robot Ventures, and Accomplice.

Host: Stephen Sargeant

Guest: Niraj Pant

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Episode Transcript

Stephen: This is your host, Stephen Sargeant. In this episode of Around The Coin, we have Niraj Pant. He is the co-founder of Ritual. They're taking AI, they're taking cryptocurrency and blockchain, and they're creating an efficient system and infrastructure. We talked a lot about his six years at Polychain Capital, where he was on the other side of the table as a VC and a partner working with some of the biggest entrepreneurial projects like Celestia Labs.

And even Anchorage Digital. We talk about privacy, censorship resistance, and how they balance that as a developer, along with compliance and regulatory requirements. We get into explaining what Ritual is, as if he was a five year old, and we talk a lot about AI and its inefficiencies, but how they're using blockchain to get over these challenges and excel the next million users.

In cryptocurrency, blockchain, and potentially ai. This is a must. Listen, if you're in the AI or blockchain space, Niraj is answering amazing questions, especially how to get that funding during a bear or a bull market. Listen up. This is a great episode.

Stephen: This is your host, Stephen Sargeant, the Around The Coin podcast. We have Niraj Pant. Co-founder and of Ritual, former investor, VC partner, Niraj, tell me a little bit about yourself and tell me a lot about Ritual and what you're doing over there at the intersection of AI and blockchain.

Niraj: Thanks for having me. My background, you know, in crypto started with my interest in cryptography. And the types of things that cryptography could, you know, bring to the world. We've had, you know, this, this great evolution of how information is, is kind of been democratized around the world. And cryptography, I think, really provides these great tools for self sovereignty.

And so, when I was in college, I started studying cryptography and, and, you know, worked with a professor around privacy, especially as it relates to cryptocurrency. And while I was there, I saw the power of what cryptocurrencies could bring. Combining hard cryptography and distributed systems and incentives to power these new forms of money and compute was a very, very powerful thing for me. In 2017, I dropped out of school and joined Polychain as one of the first employees. and stayed on there for six years as you know, leading the kind of private investments at the firm. I got the chance to work with a bunch of amazing entrepreneurs across a bunch of different categories, everything from NFTs to DeFi to deep infrastructure.

And through that time period, I got a really good sense of. Seeing the different evolution or changes, I guess, in, you know, funding and how the space, you know, broadly has changed as it relates to technology and things of that nature. In 2023, in May, I left Polychain to co-found Ritual, which is. What we're going to talk about today, which is a infrastructure network that's designed to bring decentralized AI into the world.

Broadly, we focus on, you know, a couple of main salient properties that our infrastructure provides. One is censorship resistance, which is, you know, can anyone in the world access these models and use them in their applications without fear of it being, you know, fear of the, the dev platform being rug pulled.

The second is privacy. So, making sure that the user's input and output into the model stay private and away from the eyes of, you know, a big company that may have, you know, deferring incentives from you. And then the final one is computational integrity. So, is this model that someone is claiming to run, is that the one that's actually being run?

And being able to provide a proof of computational integrity for that.

Stephen: Can you take me back to your early days? Because you were talking about in school, you had a lot of software engineering jobs. What was the conversation around cryptocurrency at that time? Were people thinking about, you know, the problem solvings of the payment, you know, the arcade payment rails?

Was it like, oh, internet money, or was it like, oh, we can, you know, buy, you know, these hacker handbooks on the dark web for a few Bitcoin? What were the conversations like?

Niraj: It was very much, I think, still how it is, which is very Wild West feeling. I'm feeling like you can, you know, build so many cool things and there's such interesting people from, you know, from different walks of life, different parts of the world.

And it's really like choose your own adventure in some way. So for me, what excited me the most was all of my friends were really excited about it. And so we were constantly reading white papers and talking about it and trading coins and, you know, all, kind of all of the above. And you know, for me, it felt like this, you know, generational technology opportunity to, you know, get into and be a part of.

And so that was what ultimately drove me into it.

Stephen: You skimmed over your time at Polychain Capital, which is huge because there's a huge amount of portfolio companies I think many of the listeners would know. You're talking about modular blockchains when it comes to Celestia Labs, you know, you have the regulated custodian like Anchorage, who was recently on actually a Chainalysis podcast, talking about their federal charter.

What was it like? Because we have a lot of founders listening to this show, so they always like to zone in on What was it like being that, you know, that VC partner? Was there any companies in there that you saw that stood out to you? That you knew that was going to be a game changer, whether it was in crypto or just tech overall?

Niraj: Yeah, the the experience was, was a really interesting one in that I got to see crypto as a change through multiple cycles and, and, and multiple years. You know, the narrative shifted, the technology improved the applications changed. I think even just the discussion around the technology has changed quite dramatically.

You know, 2017 we were thinking, you know, is this even a real industry? And, you know, now we're thinking about, you know, when's the, you know, when's the next regulated ETF coming? So it's changed quite significantly in terms of the discourse. From an investment standpoint, my, you know, the area for me that was You know, most intellectually interesting to me was what are the developers of, of tomorrow going to be building their applications with?

That was always a question that, that was very, very important to us. And so to me, finding interesting innovation is what are people, you know, what are kind of inklings of ideas that people have or the new research papers, what are tho what are those innovations gonna provide to the market? So one example of a, you know, application that, you know, to me felt game changing, you know, a company we invested in was Offchain Labs in early 2021.

We led the Series A into that company and it was very clear from, you know, meeting the team that they were laser focused, strong academic pedigree and background, but also had the ability to execute on this really, really, really big vision. Which is, we have Ethereum, it's really valuable, a lot of people are being priced out from using it.

And Arbitrum came in and provided that, you know, today it's, it's, you know, one of the largest projects in the space. And that I think was the type of thing that we were able to see from research paper, you know, whenever it was released in 2017 or so, to live working product, you know, only four or five years later.

And, you know, at the scale that it is.

Stephen: Tell me a little bit about, you've been in the industry and you've been around crypto for six years, so even as a you know, you're looking to invest in companies, you've been in bull markets and you've definitely been in bear markets. What advice would you give to a founder listening to this episode today that's probably not getting the fundraising terms that they want to or struggling to raise money or just struggling, period, because of the cycles that crypto goes through?

Is there any advice that you can tell for maybe the last bear market we had?

Niraj: In some ways, I think having that adversity right now is really good. Because investors are looking at things with a much, much more, you know, fine toothed comb than they were, you know, say in 2021. So if it makes sense now, I think it makes even more sense in, you know, in a more bullish market.

And I would urge founders to go talk to other founders that have raised from investors and figure out, you know, what did, what did they say to investors or value did they provide in their company that made investors so interested in what they were building? And I think the, the other thing is there's kind of, in some ways, a disconnect between you might have a really interesting, useful innovation.

But perhaps you're missing, you know, how do we take that and build a business out of it, or how do we take it and, you know, tell the story, which is really important. So sometimes there's, you know, the company and then, you know, everything else that you need to kind of. And so I've found that having, you know, friendly VCs or other operators that can give you that feedback before you go to a broader set of investors is incredibly valuable.

Stephen: I haven't heard anyone say that. And I think, yeah, using that existing network, if someone just raised, there was something that definitely cost the VCs or the investors attention. Speaking of ritual, you know, I know on the website says the AI coprocessor.

For blockchains, explain to me like I'm a VC that you're pitching who's like, what are you talking about?

Niraj. I don't know what that means. Explain like I'm a VC or a 5-year-old. I'm assuming the explanations would be very similar.

Niraj: Yeah. To us we think there's a really big opportunity today with where AI is. AI is being used by, you know, hundreds of millions of people around the world especially LLMs, you know, fairly recent technology has, you know, pushed AI into, into a lot of usage really, really, really quickly.

And that was an important signal for us in, in looking at product building and, you know, what are people Using their both, you know, free time on, but also their work time. And one of the challenges, or I guess potential opportunities for us that we've seen is AI models are, you know, the big AI models are really only built by three big companies in the world.

And they're run on, you know, three or four big cloud providers. And for a crypto person seeing this, you know, alarm bells start to go off where, you know, it's centralized control, you know, do you really want, you know, 10 people in a boardroom deciding how an LLM is steered or, you know, who can use an application or what you're allowed to say to it.

And these things are already in pretty You know, pretty important usage. You know, the 2024 U.S. election media is already using LLMs and generative AI in pretty big fashion. So, the opportunity for Ritual is this kind of bilateral benefit, you know, AI helping crypto and crypto helping AI. AI, you know, is helped by crypto because AI is this highly centralizing technology.

Crypto provides you self, you know, tools for self sovereignty And now you can get hard guarantees with the cryptography that is brought in. And then what does AI help crypto with? Well, AI is one of the most used new technologies today. And it helps improve how you use applications, how you do your day to day work.

And We see a lot of really interesting opportunities, again, for developers and end users, in places that AI can permeate crypto applications. And so, with building Ritual, So, Ritual really acts as a conduit between AI and crypto, and making it incredibly easy for the average smart contract developer to integrate a few lines of code into their dApp, and use that to consume the output of an AI model.

And we've seen tons of different use cases and, and, and, you know, kind of developers that are excited about this technology. So Ritual really was built to to service this you know, this growing part of the, the crypto economy.

Stephen: What's the biggest use case when developers are coming to you and saying, Oh, this is perfect.

I want to plug this into A, B, or C. What's some of the biggest use cases from maybe a developer perspective, and then maybe from an investor perspective, where do you think the use case that they're going to make the majority of their money back by investing in Ritual?

Niraj: To me, the benefit of AI in crypto, Is is bringing in a level of automation that you previously couldn't have with these human driven systems.

So an example we've seen that's, that's, you know, pretty common is in DeFi. DeFi, you know, every single decentralized DeFi protocol has human governance that is driving how they spend the treasury, how they change the parameters of the protocol, how they compensate people, and it's quite inefficient.

There's not enough people to run all of these DAOs, and they quite, you know, they run quite slow. And often for the for the governance piece of it, they're not able to respond to changes in market you know, market, you know, prices and, and, and things of that nature in real time. So an example of where Ritual can be valuable is the future, you know, DAO governance person could you know, instead of manually voting, you know, proposing a vote on how an interest rate parameter should change and then getting Everyone to vote on it, you can instead put an autonomous risk controller that is run on Ritual that is constantly pulling in data from, you know, not only your dApp, but a bunch of other DeFi dApps across the space.

Pulling in live market data and autonomously adjusting the risk parameter. And you can get it to, you know, optimize for, you know, let's minimize the amount of liquidations that happen because that increases the overall system risk. So it's examples like this that can be applied in many different use cases.

You know, everything from DeFi to, you know, building autonomous agents. You know, ultimately to even optimizing, you know, blockchain level stats and fees and things of that nature. So, that's you know, that's I think one of the biggest use cases for AI and crypto today.

Stephen: I think anyone listening that runs or is in the DAO is shaking their head vigorously, yes, right?

And I think that's one of the issues with DAOs. Being so centralized because of those shortcomings, they have to rely on centralized or Web 2. 0 infrastructure in order to facilitate it because there's not that ineffi because of the inefficiencies that they're running into in a decentralized world. So I think that makes actually perfect sense.

You know, some of the core problems you talked about on your website is around current AI stacks, right?

Whether it's lack of strong SLAs, permission and centralized APIs, high compute costs, limited access. I think you had explained earlier, can you discuss some of these core problems and how you believe that these problems are being addressed, especially with cryptocurrency?

Niraj: So the couple that I'll mention that I think, I think the most valuable for where crypto and, you know, cryptography can really help is in providing those strong guarantees that I mentioned earlier. One of the biggest ones being computational integrity. So in the use case I talked about, which is having a blockchain now actively using say an ML agent or a controller of some sort.

To autonomously change, you know, different parameters of the protocol. That is a case where, you know, you definitely want proofs that the computation was done correctly. And that people can't cheat or try to game the system. So they can benefit from you know, their you know, their kind of exploit, I guess you could call it.

And we have kind of developed a series of, of proofs around various ML models and their, their differing sizes. So for smaller models, we, we kind of use a certain technology for bigger models. We use other technologies and the computational integrity piece, I think is, again, it's one that's quite valuable in crypto.

And then it's, it's valuable in many different contexts in AI, whether it's, you know, government wants to show transparency about the, you know, the inferences that they're running for, you know, certain application that they're that they're serving. So that's one. Another is privacy. We've seen a lot of issues with protocols or I should say with, with, I mean, Web 2 companies and taking their users data and reusing it without paying them or you know, without, you know, any sort of look to copyright or anything like that.

And we're seeing this with the, you know, the New York Times case against OpenAI right now. And I think a lot of this can be solved with privacy. You know, if the operator that's actually providing you the output of the model is You know, now not getting the information or not getting the input that you're sending them.

That's great for both the user. It's better, I think, to not give them information unnecessarily. And it's, you know, I think it's ultimately good for the development of AI to have this kind of alternative. You know, we have private messengers, we have private email. And I think we need something like that you know, for AI. Not everyone needs it, but it's important that we have this one alternative.

Stephen: Like, and I know you're coming from a privacy first. Can you describe, like, an important for Developers especially why this is important when they're building, especially users on the blockchain. Like, why is this so important?

And do you think we're shifting from more of this open, you know, give up our information? You know, you know, everyone has, you know, given up a lot more information than they should. To get 10 percent off at Bed, Bath Beyond, are we now shifting a lot more to being very privacy centric? I think there was a huge hack today in like, you know, some of the top 10 social media platforms, I think LinkedIn, Twitter.

I didn't research how true it is, maybe you know better than me, but do you think there's a real big shift to privacy and, you know, these big companies or big tech companies not having all of the data, especially when they don't need the majority of it?

Niraj: Yeah, I certainly think the crypto base of users, which is growing pretty, you know, pretty significantly, and I think we will reach, you know, a billion crypto users this decade.

They are for sure very privacy conscious as a group. And they tend to you know, vote with their dollars and pick the privacy focused products and protocols in many different ways. I also think the, you know, the broader masses you know, while, you know, while privacy may not be as important to them is increasing in importance for many people.

Seeing, you know, corporations take advantage of, of users data in a way that they shouldn't, whether for corporate gain or for information gain. And also seeing a lot of big governments start to push towards more privacy as well. We've seen with the EU starting to push you know, cookies and kind of the, the selection of what data you, you send to advertisers, Apple banning, you know, the way that Facebook does their cookie collection.

We're starting to see, I think, a shift towards privacy. And again, it's, you're, you bring up the important point that oftentimes when you, you have something that's not private, you know, you might be getting that product for free. Crypto does have the nice ability potentially to, you know, change the way that developers can program incentives into their applications and offer things that, you know, maybe they're not free or maybe they're closer to, you know, Closer to free, but not exactly free, but you get all of these great other properties, which you know, which balance it out.

Stephen: You were talking about one of those core elements being the high cost. Of, you know, cloud space or maybe you can explain exactly where the costs come in. Does crypto help that? Because crypto has the ability to do micropayments and, you know, as you said, a lot more automation and use of oracles and other decentralized facilities.

Do you think this is a better use case for cryptocurrency with AI when it comes to things like the high cost of access?

Niraj: I think what blockchains are really great at is building these open programmable marketplaces. That anyone can interact with and build applications on top of and and, you know, consume without permission.

The challenge that we're seeing with a lot of the traditional cloud providers is that, you know, a lot of them are cutting these backroom deals with certain providers or certain users. And these costs in some ways are kind of fake, like, you know, some, some providers will cut the costs, you know, 40 percent for, for certain people.

And to me, that should just be run on a blockchain where it's transparent, open, and it's, and it's a marketplace. Most of these places you know, basically are, you know, kind of run their GPU businesses like a casino. That's maybe a little bit of an aggressive analogy, but they're really taking the side of every other trade.

And really what we should do is open up both the demand side and the supply side and let anyone build and, and use a marketplace. So no geographical restrictions I think is a big one. And allowing new supply to come from, you know, different regions to power different users. And then broadly opening up distribution.

What I think a lot of the You know, foundation model companies outside of OpenAI are struggling with is distribution. OpenAI has amazing distribution between their Microsoft partnership and all the corporate partnerships they've made. And many of the other companies are falling behind you know, due to that, you know, they're, they're kind of the juggernaut in the space.

And what crypto can provide to developers is a you know, almost unbundled distribution and you know, sort of model usage part of the stacks. You can now, you know, as a model creator, bring your model to Ritual and pick what Applications use it, and kind of conversely, the application developers now have access to any model, not just one model.

And I think that openness will create a lot of interesting applications that weren't possible in just a closed ecosystem.

Stephen: Now, does this play, like, parallel to Ethereum? Plugged into Ethereum? Because you mentioned, you know, some of the high costs with Ethereum, and everyone's using it at the same time, which could drive up gas fees.

And a lot of people are building their own blockchains. We just had Alex Pruden from Alio, and that, I believe, it's one of the portfolio companies of Polychain Capital, where they had to create their own L1 infrastructure for that exact reason, where Ethereum was trying to serve too many people, where they were just really focused on privacy first.

How does Ritual play into this whole ecosystem when people use the words like Ethereum and layer one privacy chains?

Niraj: Our goal is to broadly bring AI to you know, to blockchains en masse. The first products that we've released, or I should say the first developer products that we've released one is called well, one is our Infernet node.

So, Infernet is our you know, our, our compute system, our AI compute system that allows you to, from a smart contract, you know, write which model you want, the features you want, and then the input from the user, and then call it off chain get the result, and then bring it back on chain if you so choose.

So, we have an Infernet SDK that's written in Solidity. That allows you as a, you know, developer on Ethereum and soon other, you know, other networks to use any today open source model that you would like. Inside of your application, or you could build your own custom model if you wanted. And then the off chain component, which is how we achieve the scalability because doing a lot of these computations on chain would, you know, as you know, be infeasible.

The off chain component, the Infernet node, which anyone can sign up and start using to start you know, completing requests is a way to coordinate these messages and these requests from, you know, from Ethereum. Do the work and then bring the result back, you know, optionally with with a certain type of proof depending on, you know, your requirements and and your level of security that, that you'd like.

So, we're certainly very much of the, I think the new wave of the, you know, do the work off chain, prove it on chain. And I think that brings a lot of great scalability.

Stephen: Some of these core problems that you mentioned, the beauty of AI, I think, is like how quickly it almost solves its own shortcomings, right?

How quickly it solves its own problems by, you know, the more information it has, the more decision making it can make through the LLMs. Are you worried of building something that where AI can say, Hey, like we, if we get enough information, we might be able to execute so that these inefficiencies are erased, or is by adding in cryptocurrency kind of going outside of, you know, the parameters that AI could do on its own?

Niraj: This is a, this is a great question that, that I think about a lot. And to me, the. The most important thing of what we're building is, is creating access to AI. We've recently seen a trend towards open source in the AI community the last, you know, 18 months or so. But before that, you know, it was mostly just.

A bunch of researchers at Google and Facebook and a couple other companies that were doing the research and keeping a lot of the results in house that they were working on. And I think that issue that comes up later is if you do create these, you know, agentic LLM systems that, that really truly can think on their own or can do a lot more on their own, it's better for society, in my opinion.

To have that system transparent and open source, such that anyone can, you know, test the limitations of it, test the security of it and, and ultimately test the, you know, the efficacy of some of these claims, rather than keeping it inside of a boardroom where people are deciding, you know, should we release this or not?

How much should we neuter it? How much should we kind of keep the results to ourselves? So, I, I don't think we're there yet maybe it'll take a, you know, another innovation after the transformer to get to that level or, you know, every, every company is trying to, trying to solve this problem right now, you know, every foundation model company.

But what I think that we are providing is In some ways, the, the access piece that will allow people to set up guardrails in the future and and really be able to, you know, push in the direction if that, if slash when that, that world comes about.

Stephen: It feels like you have like, both feet in each pool, or one foot in one pool, and one foot in the AI pool, and one foot in the blockchain pool.

When it comes to resources How you deploy capital, you know who you're hiring, are you looking to hire more AI experts and then kind of plug in, you know, it'll be AI first plug in the blockchain, or be blockchain first and kind of plug in the AI from that aspect of it?

Niraj: Mm-Hmm. . We, we are a very inter interdisciplinary team where we have AI experts, we have crypto people and, and, you know, most of the folks at the company you know, have some combination of, of the two as well, just depending on their role and, and what they're doing.

We ultimately, you know, have this shared vision across AI and crypto, where it has this kind of, I think, bilateral benefit to both spaces. The difference that, that we are taking to our go to market and distribution is we are very, very focused on new, you know, net new Web3 use cases. Many of the crypto AI startups are going for more of a Web2 go to market.

And that's not to knock what they're doing, it's just a, it's a different approach. The Web2 market is bigger today. And if you can bring some of these properties in to those, those users, you know, lower costs and better transparency and ease of access. That's great and that's you know, really beneficial for AI.

Our difference is We're going after crypto native developers and showing them where AI can be really beneficial and help improve usage, retention, the safety and security of many of their crypto systems. And we think that new distribution mechanism will be a, you know, kind of a boon to what we're building into the crypto AI space more broadly.

Stephen: How difficult is it as a founder to hire somebody that's in charge of go to market strategy, a CMO, because that's still part of it, right? You still have to get your product out there. Someone that's in charge of partnerships, which is an immense part of the decentralized ecosystem, is partnering with whether blockchains, applications.

When it's so difficult, many marketers are traditional. There's not too many go to market strategists that even know crypto, much less that know crypto and AI. How do you, is it more technical led, you know, founder led sales? How do you approach that?

Niraj: I feel really lucky that we have a really talented team that For a good majority of the folks on the team, we've worked with for some of them three years, some of them five years.

And some of these people are, you know, 22, 23 years old. So he's in some ways for, you know, for most of their careers. And our approach to, you know, specifically to go to market and distribution and growth is because we have a few folks on the team that come from, you know, crypto venture backgrounds. In some ways, we were, you know, customers of some of these protocols, but in a little bit of a different way, you know, we're considering similar questions.

Will developers use this? What users will use this?

And now we're in a little bit of a different part of the table, but still focus on very similar questions. Ultimately how do we grow this space? How do we enshrine what we're building into the ecosystem more broadly? And you know, how do we help developers, you know, build the next generation of crypto protocols that are powered by AI?

Stephen: Niraj, I think this is great. I don't think many people could answer such a question, right? Yeah, leveraging that background that you already have when you're on the opposite side of the table to use that to kind of drive growth, answering those same questions and using it to power your own business.

You did mention censorship resistance.

You did mention privacy first or privacy centric. My compliance ears perk up and probably does so does regulators in the United States. How do you balance privacy and satisfying either regulatory requirements or other things when you're actually building?

Niraj: So we have taken the approach of, it's very much, I mean, when you're a node on our network you have the ability to kind of pick the types of requests that you would like to service.

It's a, it's a very, very heterogeneous network in the sense that Small devices can join, you know, we're hoping that in the future, maybe phones or laptops all the way to, you know, consumer grade gaming GPUs, all the way to, you know, the massive servers that you might see in a, you know, data center in Dallas, Texas or something like that.

And one thing that we are allowing nodes to do is to basically pick what type of content that they are willing to serve. You know, obviously with, there's certain caveats technically with, with how you do it with privacy. But there are both tools we can use at the ML level as well as at the crypto level to allow for a network that's both you know, open, but also censorship resistant.

The other thing that we can do, which is I think pretty powerful. Because we have this, this network of models some that are that are open source users can ultimately take these models, you know, if the licensing is correct, take these models and run them locally. The big trend in, you know, the, the traditional AI space.

For what you would think of as decentralized AI is, you know, people use their MacBooks and download, you know, Llama2 onto their, their MacBook and, you know, use the, the native M3 on their you know, on their Mac or, you know, some sort of on device GPU to actually do the inference. And, I mean, that's fully private to them.

And so that's something that, you know, we, you know, through our, our kind of model, you know, our model explorer will allow users to do. And so. Ultimately, if that's a really important use case for you, that's, that's something you can do. So the way we're setting it up is to be highly modular, to work with a variety of use cases and a variety of user preferences.

Stephen: You talked about one of those use cases being DeFi. You know, you've been in software engineering for, you know, the majority, I believe, of your career. What is the conversations happening with developers? You've probably seen them from a VC standpoint, and now that ritual they're probably building using your infrastructure.

We saw in the United States they went after the developer of Tornado Cash, which was a decentralized mixer, and they arrested him and they sanctioned Tornado Cash. Are these concerns echoed throughout the developer community, or is it mostly, especially those touching DeFi, or is it they feel that this is a one off occurrence and they're pretty safe if they're not trying to facilitate, you know, proceeds from North Korean hacks?

Niraj: These aren't questions that have been brought up to us yet the view that we have broadly is we're, we're just very focused on transparency, openness, you know, we're not trying to shirk anyone in particular, you know, broadly it's just to improve access. And I think really our, our biggest competitors are.

It's just closed innovation. It's people keeping the innovations to themselves and not allowing, you know, the broader economy and, and investors and users to be able to actually use and develop on these products. And that's the, you know, one of the most important things for what we're building is is pushing on those core values and building the technology around it.

Stephen: You just raised a round at the, you know, the time I believe you came out to sell 25 million. Backed by or led by Archetype. What do you think made this a no brainer for investors? I guess it's maybe easier for you because you used to be in the same position, but maybe share what like made this like a snap decision to raise such a healthy round during 2023, which, you know, before the ETFs were approved and the market started to look a little bit brighter.

What do you think made this a no brainer during a bear market?

Niraj: Ritual, ultimately, is a company that I would have liked to back when I was still investing. And I felt that there was going to be a very, very big outcome here. And a lot of developers would get excited about it and started seeing all of these signs again around control and centralization, as well as these new application opportunities.

And it was kind of the right culmination of You know, AI is starting to get really exciting and you know, the right set of team that we were able to work with that you know, I feel you know, I learned from every single day and are really kind of pushing the boundary on so many different areas, whether it's engineering, research, product.

You know, business development, et cetera. And that's really the tack that we've taken. There's the, I think the Justin Kahn, you know, always talks about, you know, first time founders care about product and second time founders care about distribution. And, you know, while this is my, you know, my first, you know, big attempt at a company we are incredibly focused on distribution.

I think that we kind of feel that if the usage is there and the users are there, you know, everything else will take care of itself. Maybe that's a little hand wavy, but that's the approach that you know, I, I like to take at least from a from kind of a guideline standpoint as it comes to to the company.

So those are, I'd say, the reasons that you know, the investors, I think, liked what we were what we were building.

Stephen: How do you get developer buying? Because there's so many blockchains, there's so many projects, so much infrastructure. Competing for developers, competing for usage. How do you find that either?

Product market fit? How do you get people rallying behind your cause? Is it, you know, jumping into discords and talking to developers directly? Is it just putting out a great product and knowing maybe after you saw maybe a hundred different companies come to you and projects you're like, Oh, they're all running into the same challenge.

So if we can solve that challenge for them. We know we have at least 25 companies that would probably want to be a part of our ecosystem.

Niraj: Yeah, exactly. There, we saw a bunch of use cases, or I'd say, I'd say specific examples of companies in the crypto space that were jerry rigging together AI into their product, whether you're using OpenAI's API or, you know, kind of a simpler model and doing that on chain.

And eventually, once these products need to decentralize, they're going to need that piece of the, of the product to be decentralized as well. And it's a simple thing of, you know, if you're a DAO and you have AI in your, in your application, it doesn't really make sense to give someone Off chain, a credit card to go pay for the service of a centralized API, you know, the DAO should just be able to pay directly for the services to another DAO that's offering that AI infrastructure for them.

And so that's kind of the way that we've thought about the product development and how we are connecting, I'd say, those, you know, those developers to what we're building. And I'd say the other thing worth mentioning is In thinking about what new, you know, I should, what new use cases that, that developers are going to use, it's really about thinking about the new contours of what an infrastructure provides you.

Whether it's, you know, we're seeing a lot of interesting work with parallelizing the EVM with a bunch of different projects, or new ways of doing interoperability, or off chain computation. And it's thinking about, you know, maybe more philosophically, what are the emergent properties you get when you have this, this, or this?

Niraj: And so what we think about is what are the emergent properties you get of having on chain AI? And a couple of examples I'll give you is what AI provides users, you know, taking crypto aside for a second. is it creates these emerging behaviors you get, you know, you feed some data into a machine and you get back a model and then you keep feeding it new data and it should be able to, you know, reliably predict, you know, if you give it an X, you know, what the Y should be based on all of the previous data you gave it.

And if we can now combine that with, you know, you know, crypto, which is these verifiable computers. What can you do? Well, you can take massive swaths of data, generate insights out of them, and now allow users to, you know, more predictably, you know, provide their inputs into programs or, or, you know, maybe talk with human language into a program, and then use that as a way to generate intents rather than rather than clicking a bunch of buttons on a program.

Helping in a more B2B standpoint, helping DAOs. Even even in games, you know, being able to autonomously generate character scans or dialogue or using an LLM inside of a game to kind of program your character in human language. There's so many, I think, exciting opportunities and, and Once you understand AI at a, at least a basic level and, and crypto, the connections start to make themselves more and more evident with that framing.

Stephen: You know, the funny thing about DAOs is everyone jokes that they're, you know, DAOs are neither decentralized Autonomous or actual organizations. Do you feel that this solves a lot of that, where, you know, a lot of people are cracking on the decentralized and autonomous part, and they're saying, well, it's really just four people running something that they don't want the government to intervene with, so they call it a DAO.

Do you see a lot of that, or do you see the DAOs that are truly trying to solve these governance issues and keep the decentralization, but they're still having to plug into Web 2. 0 infrastructure?

Niraj: Yeah, these are, these are really big problems that we have to solve. We've come very far, you know, given DAOs are only a few years old.

You know, corporations, you know, joint stock corporations are, you know, hundreds of years old. And it took a lot of, you know, management theory and practice to see How to effectively govern them. And there's a lot of really great companies building new ways to try to change how we do governance and make it more efficient.

And we're starting to see the creation of, you know, committee based planning and you know, kind of subcommittees and creating multiple development teams that that all compete together or cooperate together, I should say, in the, you know, in the vein of a DAO. And what I think that AI can solve and bring to these DAOs is replacing a lot of the work that humans may not want to do.

You know, the rote, let's calculate some stuff and change how this DAO works or Let's figure out how these payments are done or, you know, that's replacement. You can also talk about augmenting the usage of governance in DAOs. You know, imagine if with a proposal, you know, you're a big fund and you have to vote on what you need to do for that proposal.

You know, an LLM could you know, reliably gather a bunch of information for you and then summarize it. And then now you have a great tool to figure out how to effectively vote with your, with your money. It would be, you know, as I think what we're seeing today is, you know, imagine trying to run you know, GE, for example, with you know, the one, one coin, one vote system, you know, it'd be incredibly inefficient.

And I, I think we're trying to bridge that gap. You know, we've created something, I think, very democratic or at least very very transparent. But how do we. You know, maybe improve the efficiency such that the systems can start to really compete with their you know, the Web2 counterparts.

And focus on the project at hand, right? A lot of these are, you know, the votes are always the most painstaking part of the DAO. And it's kind of like the core ethos of the DAO is to kind of be able to hear everyone has an equal voice. But it's also the part I think a lot of people in the DAO hate the worst. Hate the most actually.

Niraj: One interesting angel investor was Balaji. I think most people know him. He has like, he's like kind of this innovator of like the network state is kind of his ethos about, you know, people connecting in the cloud versus, you know, you know, Republican or Democrat and you're in the U S. Was there any insights or advice if he pulled you aside before investing and say, Hey, you know, this is, this is what I think, or this is how we should run it, or is he just a silent investor and you never really had those one on ones with him?

Bology's work has been influential to a lot of us at the company for many, many years. Even, even before thinking about this company I think even eschewing a lot of the great values of privacy and self sovereignty and the great economic power that being a crypto developer provides you and the kind of Incentives that you get from crypto and the you know, the verifiability that you get from blockchains.

So largely I think that has helped us quite a lot and thinking through this being an interesting opportunity to to pursue. And, and recently he's been, you know, really beating the drum for decentralized AI and been one of the, you know, the most influential people in that space. You know, between having people start to run models locally.

Trying to decentralize away from just, you know, one or two hardware providers. And then ultimately, you know, how these things intersect with crypto and how we can, you know, bring about this, this shared collective vision of the future that, you know, I've, I've been mentioning you know, in, in, in the past on, on the podcast so far.

Stephen: I think what Balaji does, and even Andres Antonopoulos, they don't talk so much about the actual existence of cryptocurrency, blockchain, AI. They just tell you what history is about, and you know, and that usually lays out a pretty good picture of why you need some of this future technology. Do you agree there?

They don't like beat the drum so much about decentralization. They say, well, this is what happened 60 years ago. And if we don't want this to happen in the future, these are some changes that we might have to make.

Niraj: Yeah, I totally agree with that. I think that's the right approach. Yeah. I've found with investing the most interesting innovations not only challenge you from a business standpoint, but they really start to change the way you think about the world, you know, philosophically, socially, politically.

And Ethereum is one of those things. Ethereum just is not just a new application development platform, you know, it's not Heroku 2. 0. It changes the way you think about who controls the things that we run. And what kind of things are you giving to corporations or governments or other people? And I, I really do think that's the opportunity here with crypto AI as well as as I started, you know, really diving into the space.

It felt like there was an opportunity to to really affect society on, on, on many different levels with this technology. And that really, you know, kind of drew me to it. I think especially with you know, with LLMs, seeing how, you know, language is being used as a, as a way for computers to, you know, talk back to humans is you know, an amazing innovation.

And really reminded me of the first time I read the Bitcoin white paper. It felt like this almost you know, kind of God like creation. That's really going to change how we, how we live live in society.

Stephen: And it's funny to see how it's like progressed in many different ways. And, you know, you talked early about the early on days, people were talking about NFTs. What are your thoughts on the NFT markets, the metaverse, you touched on crypto gaming a little bit. What are your overall thoughts about crypto and maybe other elements that interest you, aside from what you're doing at Ritual? Or maybe even like, hey, I think Ritual might be plugging into this and could really expedite something like, you know, spatial experiences with the metaverse.

Niraj: NFTs are, to me, one of the best ways for regular people to get into crypto. The challenge with a lot of the existing crypto protocols is that they may not solve regular people's challenges. You know, DeFi, for example, you know, if you're a regular American that saves in a bank account you don't really invest, DeFi may not be really super valuable to you.

You know, for being pragmatic about it. What I think NFTs are great for. is they really widen the aperture of what you can do with tokenization. You can, you know, NFT can be anything from, you know, I played 10 minutes of this game, and so I get an NFT, all the way to, you know, this is a 10 million dollar, you know, piece of art, it, you know, should be, you know, at the MoMA.

And I own the digital, you know, rights to that, that piece and thinking about NFTs as a way to program different types of value is is a really, really exciting opportunity for people to tackle and I think you remember in 2021, 2021. So many of the ways that the celebrities and the, you know, the big famous people got into the space was through buying PFPs, through, you know, work, you know, building these NFT games and, and using them and being patrons of them.

So there's this great loyalty connection that NFTs drive. And I'm really excited to, to kind of watch the innovation closely. And from the perspective of Ritual, we're already working with a couple of NFT teams today that we'll be, you know, hopefully announcing over the next couple of months that shows the power of how we're able to drive these new interesting experiences with AI and blockchain.

I think, you know, once we, once we release it, you'll see how wacky some of these things can get and, you know, frankly, how cool they can get. And I think it'll really drive, you know, the next, you know, generation of, of users, you know, the next hundreds of millions of users to crypto is you know, being through NFTs.

Stephen: It's funny that you used the word wacky. I'm sure listeners to any of the podcasts will be like, wacky, I'm not interested. Walk you to the crypto industry is like, yeah. Tell me more. We're gonna take my crypto, take my Ethereum. We recently had over the last weekend actually, Ray Chan nine gag, CEO who built nine gag basically off a meme culture in 2008.

I peeped the ritual Twitter account or X account. And it seems like you have a little bit of that meme humor yourself. Do you feel like this is a great way. To, you know, maybe advertise or promote or just have fun in, you know, whether it's crypto Twitter or whether it's in decentralization to draw in developer interest.

Because it looks like some of the memes, like if you were a developer, like those ones hit. Maybe not so much for me, but as a developer I can see some of those hitting pretty hard.

Niraj: Yeah, we, we love memes. They're, they're just fun and they bring a human touch to everything that we do. And, you know, internally, we, we like to shitpost all the time, I think it's just fun and, and you know, lightens up the, the mood of, you know, I've been talking about these very serious platitudes of, of centralization and the risks of it.

So it, it really provides this, this kind of nice touch to to what we're building. And we really like interacting with protocols in that way as well. That is, you know, a lot of what we learned at Polychain is that's just a fun, interesting way to engage your community. And you know, as you know, community is a, you know, incredibly important thing for, you know, some of these decentralized crypto networks.

You're trying to build a tribe of people that are aligned around your core values and core mission of your, your project, your token your product, et cetera, et cetera, et cetera. So, yeah, definitely definitely we'll continue to do that over the, the coming you know, weeks and months.

Stephen: And memes are like interoperable, right? Like better than most blockchains out there. They can go across any country, any language. And everyone just kind of gets it. You know, with the BTF, or BTF, with the Bitcoin ETF, I hope they don't start calling them BTFs. With the Bitcoin ETF approvals, you know, the crypto winter seems like it's dying out.

You mentioned potential NFT partnerships or marketplaces being built on Ritual.

Is there any other features, concepts, or even like, hey, customers are begging us for this, but we haven't got there yet, but we're going to get there. Is there anything else that you want to mention before we finish the episode?

Niraj: The The goal for us over the coming months is to just increase the capabilities of the ritual system. So more models, more users, more integrations. And I think it's kind of a, you know, positive flywheel with all of those things. What I would, you know, implore people to do is, you know, go check out our node and go try running one.

It's pretty simple to run, and now you can take part in this, you know, new economy of servicing AI models, and really any device can do it. I mean, to some degree, and eventually we'll increase, you know, who can participate, you know, through, through our building. I think that's an exciting way to get your feet wet with you know, with our systems and, and with AI crypto.

And then I'd also say to, to check out our SDK. And as we start announcing some of the integrations that are building on top of us, people will be able to see how how capable some of these things are. So, we have a lot more coming over the next couple of weeks. So, you know, Twitter is a great way to see what we're up to and we'll be, you know, posting more memes and, and fun stuff as well.

In addition to, you know, the serious updates on the You know, the Node software and the research and, you know, the other other more you know, hardened stuff.

Stephen: How long do you think before we stop calling Twitter, Twitter, and we finally give in to Elon and call it X?

Niraj: I don't know. I keep switching between the two.

Stephen: It depends who you talk to, right? I feel like we transitioned from Facebook to Meta kind of easily, but we're still saying Facebook. Nobody's like, oh, I was on Meta the other day or, you know, Meta's annoying me with their privacy things. I feel like it's been a tough switch for Twitter.

Niraj: It has been tough. It, it doesn't roll off the tongue as easily.

Stephen: Yeah, X just sounds weird because then people are like, what do you, like, exactly what you thought. Like, when do you talk at X? Like, like, is this, am I solving a, a formula of some sort?

Niraj, where can people find you? Where's the best place? Give us the website.

We'll put everything in the show notes. What people like when you spell it out from them over the episode, they feel like they're part of the process. So where can people find you and find out more about Ritual?

Niraj: Yeah. So our website has a ton of information on it, blog posts code more about the team. And if you're looking for a job and interested in AI crypto, we're hiring for, you know, a ton of folks. So the website is just So R I T U A L. net. Our Twitter is, or our X is So R I T U A Lnet. And then for me, I am So those are, those are some great places.

And we have a bunch of team members that are also posting stuff. So, so go follow them as well.

Stephen: That's awesome. I feel like you must have been early on Twitter to get that Twitter handle, I feel.

Niraj: I think 2009, so I...

Stephen: yeah, I was gonna say that's a many years to get nage just like that Seems like you gotta be pretty early on Twitter to be quite honest, because even if you just Google Niraj, there's a lot of Niraj that come up.

Yeah. , this has been an awesome conversation. I'm excited. Like I don't get really technical, I'm not gonna read the documentation. But looking through some of your flow, and now you explaining it, it really makes sense where people are like, Hey, we need to build and you're, you're right. You can't just plug, plug in or, you know, try to jerry rig some of these AI applications.

It's far too sophisticated. You need something that can do a complementary to the blockchain that you're running. And it makes sense why investors jumped at this opportunity. And we can't wait to hear more about this. Hopefully we can have you on a year from now to do a follow up. What's happened, some of the big projects.

Do you still dabble in, you know, VC angel investing on your own or you kind of left that world now?

Niraj: I, I try to support friends that, that invest and try to help them with you know, with their raises. So, I don't have as much time for it as I, you know, as I used to when I was a full time investor, but yeah, occasionally I do.

Stephen: Expect your friend requests to go up on Twitter all the time. Oh, friends, right? On Twitter. Expect those requests to go up.

Niraj, thank you so much for joining Around The Coin.

Niraj: Yeah, thanks for having me. It was awesome to talk and hear all your great questions.

Stephen: Thanks so much.