Space Summary
The Twitter Space Let’s talk gaming #23 with Spellborne, Gam3sGG, Pool Masters and Crystalfall hosted by MeritCircle_IO. In this insightful Twitter space, representatives from Spellborne, Gam3sGG, Pool Masters, and Crystalfall delved into the realm of gaming within the Merit Circle ecosystem. Discussions revolved around community-driven projects, blockchain integration, VR and AR technologies, creative game design, partnerships, inclusivity, monetization strategies, innovative game mechanics, and the future of gaming technology. The dialogue emphasized the importance of collaboration, engagement, originality, and sustainability in the dynamic landscape of gaming development and user experience, offering valuable insights for industry enthusiasts and creators aiming to shape the future of gaming.
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Space Statistics
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Questions
Q: How do collaborations impact the gaming industry?
A: Collaborations bring diverse expertise, resources, and perspectives that drive innovation and growth.
Q: Why is community engagement important in gaming projects?
A: Engaging with communities builds loyalty, feedback loops, and a sense of belonging among players.
Q: What role does blockchain play in transforming gaming ownership?
A: Blockchain ensures transparency, security, and ownership verification, empowering players and creators.
Q: How can gaming projects leverage VR and AR technologies?
A: VR and AR enhance immersion, interaction, and engagement, offering new dimensions to gaming experiences.
Q: Why is originality crucial in game development?
A: Originality sets games apart, attracts audiences, and drives interest and excitement in the gaming community.
Q: What are the benefits of inclusive gaming environments?
A: Inclusive spaces promote diversity, accessibility, and participation, enriching gaming experiences for all players.
Q: How do partnerships contribute to the success of gaming initiatives?
A: Partnerships bring mutual benefits, exposure, and synergies that amplify the reach and impact of gaming projects.
Q: What impact do innovative game mechanics have on player engagement?
A: Innovative mechanics enhance gameplay depth, enjoyment, and retention, creating unique experiences for players.
Q: Why are monetization strategies critical in gaming?
A: Balanced monetization ensures fair value exchange, sustainability, and continued support for gaming projects.
Q: How can gaming projects balance profitability with player satisfaction?
A: Striking a balance between revenue generation and player satisfaction is essential for long-term success in gaming.
Q: What are the key considerations in creating successful gaming projects?
A: Creativity, player-centric design, community involvement, and technological innovation are essential ingredients in successful game development.
Highlights
Time: 00:15:42
Community-Driven Gaming Projects Discussion on the rise of community-driven initiatives shaping the gaming landscape.
Time: 00:28:19
Blockchain Integration in Gaming Exploring the impact of blockchain technology on ownership and in-game economies.
Time: 00:36:55
VR and AR in Gaming Experiences Insights on the integration of VR and AR to create immersive and interactive gaming environments.
Time: 00:45:11
Importance of Creative Game Design Highlighting the significance of creativity in game design and player engagement.
Time: 00:55:33
Strategic Partnerships in Gaming Importance of partnerships to amplify reach, resources, and opportunities for gaming projects.
Time: 01:05:27
Inclusivity in Gaming Communities Embracing inclusivity to build diverse and welcoming gaming spaces for all players.
Time: 01:15:09
Monetization Strategies in Gaming Balancing revenue models to sustain game development and enhance player experiences.
Time: 01:25:44
Innovative Game Mechanics Exploring how unique game mechanics drive player engagement and retention.
Time: 01:35:18
The Future of Gaming Technology Discussing the transformative impact of emerging technologies on the gaming industry.
Time: 01:45:55
Creating Successful Gaming Projects Key considerations in developing and launching successful gaming initiatives.
Key Takeaways
- Community-driven gaming projects are gaining momentum in the industry.
- Collaborations play a vital role in the success and innovation of gaming initiatives.
- Engagement with gaming communities is essential for sustainable growth and user retention.
- Incorporating blockchain technology can revolutionize gaming experiences and ownership structures.
- Nurturing creativity and originality remains crucial in the development of successful games.
- Strategic partnerships contribute significantly to the visibility and expansion of gaming projects.
- Emerging technologies such as VR and AR are reshaping the future landscape of gaming.
- Accessible and inclusive gaming environments foster broader participation and diversity.
- Innovative game design and mechanics are key factors in attracting and retaining players.
- Monetization strategies need to balance profitability with player enjoyment and fair rewards.
Behind the Mic
Introduction to the Session
Hello, everyone. We're really excited for this session. This session is going to be a major one. It's going to be one for the books. In a moment, I'll talk a little bit about what you're about to hear. Real compute, real AI agents and the right to transact. So we're going to go over a lot today, and the core of it is this juxtaposition that exists in web three. On one hand, we have a space that provides such critical solutions to such critical issues across tech, across governance, across finance and across AI. But on the other hand, there is a lot of vaporware in our space, a lot of narratives that are designed to attract investors, retail investors, advocates, enthusiasts, but don't actually have true market value at the end of the day. And so we're going to be discussing these points in detail on how the organizations, the projects that are in our circle and in our sphere, projects that are involved in the independent AI institute projects that are in this call today, in this spaces, are providing real solutions to real issues and to, and creating the world that we want to live in.
The Role of AI in the Future
AI is going to be our operating system in the very near future. I don't know if you've heard the term exocortex, but it's exactly what it sounds like. Our cerebral cortex is our mind inside of our skull, our exocortex. This will be part of our mind very soon, and the operating system of an exocortex is going to be what? AI. So it's important that we own this intelligence, that we have the right, and we have a say in how AI is ultimately deployed, distributed and ultimately operated. And we can't do that in a centralized paradigm. But then also, we can't do that in a world where we're creating narratives that are non-deployable. So we have to bridge that gap. We have to leave space for developers to develop, but we have to allow this to be built in the time that it needs to be built. And instead of creating, like I said, vaporware. So that said, in a few minutes, we're going to kick this off. I have my esteemed colleague, Russ, who is our chief business development officer.
State of the Industry and Introduction of Guests
Hello, everybody. Glad to be part of it. Looking forward to it. Yes, sir. We have theorec. AI will be in the house, 6079 will be in the house, wired network will be in the house, and many others. So we're super excited for this spaces, and very shortly, we're going to turn up and we're going to talk about our successful event in Singapore at Token 2049 and how we revealed the elusive h 100s in a way that was not only visual, but it was easy to see the deployed nature of these said machines. So I'm going to pause for a bit and we'll check in with you very shortly. All right, well, we're going to set it off. We're missing one of our key contributors who will be here shortly, Mike from 6079. My dear friend and partner, we have some awesome guests today and we have an essential topic that we a set of topics that we want to cover that all really actually go together in a beautiful way. So real compute, real AI agents and the right to transact.
Diving Deeper into Web Three
We're going to dig into what all of that means and how all of those things relate to. The thing that is that I really want to highlight today is sort of the yin and yang of web three in terms of usefulness, in terms of market power, in terms of human usefulness. And what I mean by that is there's kind of two prongs with web three. There's one which web three solves some of these incredible use cases across the world and provides solutions in so many spaces. But then there's this other side of it where it's kind of the Wild west and there's so many narratives, there's so many projects that make a statement about how they do x, y and z, but do they really, or have they really done the due diligence to create the thing that ultimately solves the problem? And we're going to start with a conversation about compute, but I'll get to that in a minute. I want to introduce our guests, or rather have our guests introduce themselves.
Introducing Ron from Theoric
I want to start with Ron from theoric. Ron, if you could introduce yourself and introduce theoric, we would be pleasured. Thank you, Doug. Well, it's great to be here. I'm excited for the conversation today. As co-founder of Theoric, my background has been as an entrepreneur for most of my career and working in AI and machine learning. For much of it, I was involved, really got into AI and machine learning at ad tech company called Quant Cast, where we built lookalike models to help find people that might be interested in goods and services. Scaled that to multi-hundred million dollar business. Then I went on to start a company, think big analytics, helping enterprises with AI and machine learning. Sold that to Teradata, a large database company. Went on to the CTO office in Google Cloud, focusing on applied AI and responsible AI. And after that I was at Canada's Vector Institute independent research lab with 500 researchers, about 100 industry sponsors, again building an AI engineering team and scaling the infrastructure for compute.
The Future of AI and Theoric’s Vision
The founding team of Theoric were people I'd worked with into some of those previous places, and we really felt that AI was going to be the most important technology, the most transformative technology of our lives. And my experience at Google and other places in big tech just convinced me that it doesn't end well if we let a few monopolists, a few billionaires control AI and control the economy and control the future. I really got excited by the web three ethos of community participation and democratization, and having a way that we can have AI protocols that we can all influence and benefit from and that are transparent and ones that we can all reap the benefits from. I think it's a pivotal moment in our society. AI is going to be utterly transformative. The nature of work and our personal lives is changing rapidly. And so at Theoric we're really focused on the agent layer. We basically see that all the advances in what are called LLMs, even though it's a misnomer, these large language models powering things like chat, GPT, that they are general purpose, and you can build them into systems that do really powerful things.
The Role of Agents in AI Advancements
They can act autonomously, increasingly autonomously. They can plantain, they can access data in real time and APIs and run code, and so they can do all kinds of useful tasks. And so we see a future where anyone can create high value agents that do things they know how to do, and that the agents dynamically compose and work together to solve problems. Right. We've just released our testnet, we've launched love people to give feedback, but we're really bullish. The pace of innovation in the open community is something that we think is really going to outstrip what decentralized players are doing and give us all a chance to have a stake in the future of AI. So that's a quick overview. Obviously excited for the conversation today. Very on point with our ethos and what we're building.
Connecting Theoric with Other Innovations
Beautiful. And I can't wait to dig in more deeply into what theoric is doing. And it's notable to state that across the space there's not another AI agent-based project that is deploying as quickly as with quality as Theoric is. And so we're super excited to be partnered with you guys and we're super excited to see what unfolds. That said, I want to pivot to another one of the pioneers of the space, the future pioneers will be looked back at as pioneers believe that in the coming years. And so I want to pivot to Ken over@wire.net. Work. Ken, if you could introduce yourself and introduce the wire.net work project.
Ken from Wire.net Work’s Introduction
Oh, it's funny. As you were leading that up, I figured you were going to go to somebody else. I didn't know that was my interest, but I appreciate it. Yeah. So what wire is doing, I'm the founder. I'm the CEO of wire. And what we saw four years ago is that it wasn't even AI related to start web three, which the definition for me is the next generation of the Internet was so inferior to the web two counterpart that were never going to be the, quote, unquote, future of finance without bringing infrastructure up to the level that it needs to be. And so that's what wired did like we wanted. We would love to have been just a product development company at the product level, but the infrastructure wasn't there.
Building the Infrastructure for Web Three
So we pivoted very early, and we started building just straight infrastructure to allow this. Now we leap forward to 2023, and then now, and AI's come just so fast and decentralized. AI is so needed. And what we built was, we didn't even realize, but we were building for that. We thought were just going to build for humans. And then what we built, we looked at the requirements. We're like, this is exactly what AI agents need. So what we did at wire is we built, and we're releasing here in the fall is a universal transaction layer. Like, these smart agents are going to need unfettered access across all chains. And you can't do that with bridges, you can't do that with burning and minting.
Challenges of Existing Infrastructure
You can't do that with just wrapping assets. You can't. You can't do it with the current infrastructure. Well, that's what we've been building for the last four years. So you're going to have all chains, not just evms, not just, you know, cosmos and what they're built on, not just, you know, what Solana is built on, but everything. So one unified transaction layer, one universal identity, which will be for humans and for AI, for smart agents. And that's what you need for a high performant or a full performance smart agent. If not, you're gonna be siloed on chains, or there's gonna be a huge fees, you know, lag times for trying to bridge from one type of architecture to another. And so, you know, and speed and cost as well.
The Importance of a Universal Transaction Layer
So you don't know. You know, if you prompt a smart agent, you don't know if it's going to take one transaction or 1000 to complete what your prompt is, depending on what you're trying to get it to do or what chain that liquidity or transaction's on. So there's so much that needs to happen, and so you need a universal transaction layer. And so we did that. And it's very secure. It's the only, in my opinion, as far as I know from what's out there, it's the only blockchain architecture that can actually give you everything that you need for these agents to perform at the level that they should.
Showcasing Partnerships
And we have other partners up here. I don't want to. I'm trying to stay in my lane. I don't want to steal Mikey's thunder, but, yeah, that's where we're at. And as this conversation goes, I'll definitely add some more comments in. Amazing. Yeah, so I'm seeing some pieces of a puzzle. I'm seeing Fioric, the AI agent layer. I'm seeing a the wire.net work the network that it could exist upon. I'm seeing compute, and I'm seeing these as real, viable solutions that can fit together. And this is exciting, you know, this is why we're here. So, Mikey, I want you to give.
Introducing Mikey and the 6079 Project
So I'm going to do a two parter introducing Mikey. Okay. I'm gonna let Mikey introduce himself and the 6079 project, but interwoven in that introduction. Mikey, I want you to tell us what you mean when you say the right to transact. Go. You got it? All right, so I'm Mike Anderson. I'm on a mission to make independent AI the global standard. And what I mean by that is we are at an evolutionary spike right now where humans are changing from humans without AI. It's kind of like there was a point in time where there was humans before tools, and we looked much more similar to all the rest of the animals. We created tools.
The Historical Perspective on Technology and Tools
And look at this world we've created. We've got buildings and infrastructure and electricity, and these are all things that compound, because we have tools that can compound on top of each other. AI can move today at thousands or even millions of times the speed of a human mind. And they're gaining competency, they're gaining tools. Ron talking about agents, I believe that Ron and his team are just right on that cusp of building the best agent platform in the world. And that's all happening right here, and it's happening in the independent AI world, because we're using open source tools. Those open source tools are composable, meaning that they can work together.
Interoperability and Community Trust
We're trying to solve interoperability, not trying to create moats so that we can monetize. And they're protocol driven, meaning that you can trust that the community is going to be part of making decisions about what's happening in the future. And so within that world where humans are now getting access to a whole new level of power that we've never had before, we also need to be able to update our social contract with one another. And the United States did a fantastic job, like the founding fathers did a fantastic job of setting up the United States in opposition to an imperial crown that we all bow down to. And when they did that, they gave us the Bill of Rights.
The Social Contract and AI
And the Bill of Rights have the ability, if you really take it and you're like, okay, what is freedom of press, freedom of speech, freedom of organization? What do all these things really add up to? And it's the ability for a person to transact in ideas and thoughts and beliefs and financial value, and to organize nonprofits and unions and churches and businesses and all these sorts of things that have become society. We have a new social contract in place with AI because they're faster than us. They can watch us wherever we're Athena. They can manipulate us subtly. So the freedom to transact and the freedom for an individual human to be able to own their artificial intelligence is actually a precursor to being able to have any of those freedoms in the Bill of Rights.
The Importance of AI in Modern Society
So I believe that what the people here are doing is actually as critical to the future of human life as what the founding fathers did in the early days. Does that answer your question, Doug? Like, and then some, yeah, that was awesome. So, you know, there's a critical piece that layers on top of this, and it's decentralization. You know, Mike was mentioning the right to transact and what that means in terms of the very essence of what the United States DNA is, which is, which is embedded into the Bill of Rights, and which provides our rights to act as sovereign citizens, to follow our dream, follow our bliss, provide for our families, and all these basic things that we take for granted.
Building the Desired Future
And there's this kind of new layer that we are facing, and we want to build the world that we want to see. We want to as the early builders in the space, we want to be on the right side of this. We want to create the world that we want to see. And that's what the players in this space are up to. So I want to pivot. I want to talk a little bit about exhibits. So, exhibits provides compute. And Russ, I want you to introduce, I've said this to this audience a thousand times, so, Russ, I want a freshen, you know, a fresh version of this. But I want you to talk about Exodus and talk about how we're different, how we provide compute.
The Landscape of GPU Cloud Compute
Yeah. So, you know, we hear a lot about GPU cloud compute, right? And we tend to think a lot of Amazon and Google and Azure and, you know, we think of them, those as big monopolies. And, you know, they control about 70% of the cloud GPU market. And everybody I talk to who uses them, they kind of like whining, complain how expensive it is, how they lock you into long contracts. It's just not a great situation. So now there's a lot of what I call emerging marketplace GPU providers, companies coming up that are offering GPU's in the cloud in a lot of different ways. Some of them are low cost, some of them are region specific, some of them are by community, and a lot of them will trade GPU's.
Introduction to GPU Provisioning
We provide GPU's to you provide GPU's to you. We share GPU's with them. Ours come from crypto miners. Ours come from gamers. The real difference with ionet is at the bottom of all of those marketplace providers emerging, providing GPU's, there has to be somebody who physically has the GPU, and that's exhibits. So we have very deep relationships with data center providers and people who build racks and manage. So somebody might have said, you know, maybe Ionet is the Airbnb of GPU's. Well, exabits is. We're the Marriott of Gpu's. We physically manage, own, manage and operate all of the physical infrastructure that is sometimes the source for a lot of other providers. And in being there doing that, we're the ones who can, you know, we have the hands on, so we can provide the reliability. We can provide the on hand support, give you white gloves.
Reliability and Infrastructure
We're the ones who can offer you reliability. We can. So it allows people a lot more of a comfort working directly with. So we work directly with AI ML providers on their bare metal, their APIs, their inferencing, whatever it might be. So it's a big difference being the ones who physically have the infrastructure and we have GPU's in about a dozen data centers all over the world. So we have a distributed network. And for those of you who are at Token 2049, we had an amazing event. We actually, for this particular week, we worked with Rack Central, a data center provider in Singapore, and EMC, and we installed a rack of H 100 servers in Singapore and went live. So boom, there you had it. Another GPU farm for exhibits with high quality. And we invited people to come to the data center to actually see our facility and listen to how we carefully manage and go through all of our stuff with that.
Credibility in Emerging Spaces
And it was so well received, and it just adds a lot of credibility to, wow, this is the company that's actually delivering the reliability and the quality of GPU's in the emerging space of cloud providers. Thanks so much, Russ. Yeah, I think the key piece is that the real infrastructure is so critical and the real build is so critical. In the web three space, it's quick to be expedient, or it's easy to be expedient. It's easy to build half of a product and then go get funding and then go show the bag and call it a day. But if we want to create something real and if we want to build the future that we want to see, we have to look past that. And that's, again, that's what the projects and the spaces are about. So I want to jump to the AI agent economy and just kind of pull that back a layer.
Understanding AI Agent Components
Ronnie, can you tell, Ron, can you tell us about just the key components of what makes an AI agent? Yeah, absolutely. An AI agent, its brain is ultimately generative AI model, also known as large language model. So that could be open models like Lama three one or QN 2.5. Or it could be commercial models like OpenAI zero one model that just came out, formerly known as strawberry or anthropic clawed sonnet three five as examples. So that's a brain. Then you've got working memory, which is essentially a whole bunch of information context that can hold multiple past interactions. You can use a technique called Ragdez retrieval augmented generation, where you pull out of a huge search index, relevant information for what the agent is working on, and include that. And you can have examples of past work, which again, is part of that working memory, so that the agent knows what it's doing.
Tools and Planning in AI Agents
And you can also have access tools which can be APIs or code sandboxes for executing generated code or databases to query, right? So you have this combination of tools, working memory, a brain. And in fact, unlike humans, agents can have multiple brains, right? That it's common to actually use multiple different models, right? Like there's been a rise of fast, cheap, often local models that are doing useful things. And sometimes you want to just do something quickly to summarize something or scan or pull things. And a small, cheap model is great. Other times you want to do complicated planning. And state of the art models like zero one or llama 31405 b are better at that. Maybe those are even fine tuned. So with the brain, you've got working memory, you've got tools, and a key function they do is they tend to do a form of planning and then decide.
Collaborative Functioning in AI Agents
What we see working well is not just single agents, but teams of agents figuring out how to collaborate, working together. And, you know, I think another really important point that came up in talking about wire network is it's incredibly important when you ask agents to do a task that you have a budget, you have a sense of, like, what is reasonable to accomplish the task, right? Just like you don't have hire a contractor, a person and say, go do it. Price is no object, just go execute this for me. Right. So certainly we've built into theorex this idea that you gotta have a budget. And so like, as a collaboration of agents comes together, they have to negotiate, given the budget, they have to pay for the data that's used because, like, real time access to data, whether it's social data, whether it's index, blockchain data, whether it's news, whether it's web searches, like that, data usually costs something.
Constraints and Costs in AI Operations
And likewise, so does actually executing the thinking, the brain. Right. The processing of all of this. Right. So that's high level. What are the key pieces and some of the key constraints in thinking about how you make agents work? I guess the other thing I'll say is that right now we're in a phase where there's so much excitement, so much growth, that many products have free access for a certain amount of usage. We're no exception. That's true in most web three and web two products and AI is that there's free credits and a certain amount of free usage. Long term, we think people are going to be paying for use, but the initial use, people are getting free trials, which is awesome. Awesome.
Future of AI Agents in Trading
Thank you so much for that overview, Ron. Imagining AI agents operating in the space of trade, operating across crypto trading, for example, or in general blockchain trading. So maybe I have an agent, I give it a budget and I say that, hey, I want these outcomes and I provide it with the brains that I see fit so to say, to use your analogy of the LLM, and then I set it off to market, is that accurate? Is that going to be kind of how it looks in the future? I think that sort of end state, I think that there's going to be a journey where people get comfortable, right? So the first thing is gathering the ability to have agents assist them and help them research and analyze and make good decisions about when to buy and sell.
Democratizing Access to DeFi
The next thing is then starting to simplify the execution, democratizing access so you don't need to be a complete expert on how to execute in DeFi. So we've got a partnership with Brian that provides agents that make it easy to express a natural language, how you're going to execute. I think that's going to change. People are going to want to have really good visualization to see simulations or likely outcomes so they can be confident. Eventually, though, you do get to an end state of like more and more, hey, just have the agent automate managing for me. And I think that sort of democratizes. We know that the big money managers, the hedge funds of the world, have long had automated agents that are managing their I portfolios.
Competing in Financial Markets
So democratizing that technology so anyone can curate a set of agents, a team of agents that will manage money for them and compete with the big players is an exciting opportunity. And I think even with that, what you're going to see is people sort of giving, you know, teams of agents, a subset of their portfolio to manage. And they'll manage, they'll handle it, just like, you know, handling human managers. You would not give all your money to one manager. So in the same way, you probably have multiple teams that each are earning the right to manage more of your money. So I think that's the direction of travel and trading, and we're seeing a lot of excitement from some of the first agents that are enabling that kind of analysis and trading.
Disruptive Potential of AI Agents
Gotcha. So this is such a major disruption. The way you describe that, the way you describe people, the people having the ability to stand up to these major players that have been dominating and driving the financial sectors for decades, having the ability to actually engage with these players. And I mean, this is, this is the core of web three. This is, in my view, the very essential ethos of web three and why it's so valuable, because it's ultimately going to be an arms race. And with web three, we have the ability to provide a space where common people, you don't have to have just mass resources to actually be a player in the space.
Empowering Developers and Users
You have to have, you have to have the ability to discern what you want to have as a developer. You have the ability to engage and to utilize resources that are offered in a decentralized fashion. And so I want to move to Ken. And, Ken, I want to ask you, in the space of the AI agent economy, what do you view as the needs of the AI agent in order to operate within the AI agent economy? Yeah, for sure. So, I mean, just to backtrack, Ron made a lot of good points when he's talking about, like, agents are going to have agents, and, you know, you're going to have a budget and negotiation and all that.
Infrastructure Needs for AI Agents
To me, those are all microtransactions, like, under, like, under the water line. Those majority of those are going to be on chain transactions as well. So people think about all these are agents, and they're going to be, you know, they're going to be trading and they're going to be doing all these things that's, like, above the waterline for me. But it doesn't matter if you're above or below. They're going to be on chain transactions. And so, again, you're going to need really fast, really cheap, really secure. And so both sides of that equation will be on wire network. So what you just asked is, what are these agents going to need?
Identity and Wallet Requirements
Well, we'll start with identity. So not only are you, Doug, you need a universal identity. Like, you're going to need an identity for all to go across chains, but your agent's going too. And so you need to have that part of the infrastructure that's something that wire provides inside the universal transaction layer. You're going to need a wallet that has that functionality so that it doesn't have to go KYC everywhere and not have the potential wallet for a cryptocurrency that you have. For instance, Hedera Cardano, Polkadot, Ethereum, Solana, like, all eos, every single one of those is all completely different blockchain architecture.
Challenges in Blockchain Integration
And so normally you'd have to go, okay, well, I want to play around on ethereum, so I have to go download a metamask wallet, and that'll generate me, you know, my key pair for the Ethereum networks and evms. All right, well, now I want to go play on Solana. Okay, well, now I got to go download the phantom wallet, right? So I can get my Solana address, and then I, I want to go play in the cosmos ecosystem. Okay, so I got to go download Kepler, you know, or leap or whatever they have over there. Like, that's not conducive for a smart agent. It needs to have one wallet with an identity that's universal, that can go and perform its function.
Speed and Efficiency in Transactions
Then it's going to need speed, right? Like, we call it the speed of thought. Transactions at the speed of thought. You have no idea. Like, let's just say hypothetically, you give your agent a prompt to go find you the best yield for one day, and you give it a $1,000. Okay, well, how many transactions is that smart agent going to use? Is it going to be one? Is it going to be a thousand? Is it going to be a million? You know that when you have, like, high frequency trading on the stock market, you know, they're doing so many transactions in a day, like, huge amounts.
High Frequency Trading Challenges
So it better be, you better have enough bandwidth there to allow that agent to do what you want. And then if there's thousands or millions trading, I mean, it just escalates quickly. So there, if you have speed, well, you need, price has to be super cheap. You can't be reliant upon. Well, let's put this way. Do you want the Ethereum network to be the network of AI smart agents with 15 tps? No, it's not going to happen. Like, it's. It cannot happen. So you need something that's super cheap, super fast, has a lot of bandwidth, and then secure.
Security Considerations
Like, you can't have these agents going across all these bridges and everything else that get, they get popped all the time and get exploited. So that's where, you know, the universal transaction layer comes in. We have all of those things. And, you know, that's, if you don't have those, like, what's going to happen? You're going to build, like, a decentralized smart agent on Polygon, you know, like, what happens when you need to go over to Solana? What happens if you need to go get liquidity over, like, from Cardano's ecosystem? Like, once you start thinking, like, practically, you realize that, you know, there is only one way to do this, and that's going to be, like, with wired network and with this independent AI consortium all working together, everybody bringing in their, as I call it, their primary weapon, and build out this tech stack for peak performance.
Wire Network Capabilities
Awesome, Ken, thanks so much for that. So just for Claire, like, just to say, simply wire.net work offers the ability to trade across any blockchain without gas and without using bridging technology. Is that right? Yeah, exactly. So you're going to be able to have a universal Dex, a universal NFT marketplace, a universal wallethead. And so that's going to solve all the problems. Like, you're not going to need to go to uniswap anymore or sushi swap or pancake swap, considering what blockchain you're on, you're going to be able to go to one swap and do whatever you need and have increased performance.
Future Directions for Trading
Like, if you're trying to go to Solana, to Cardano right now, is there a bridge that even does that? Not that I know of. Like, if you're trying to go from, you know, ethereum to Hedera, like, how do you do that in a decentralized fashion? Like, the only way that you can do that, to my knowledge right now, is through a centralized exchange. And that's the problem. Okay, so it's kind of like, to use your analogy. So it's kind of like in the past, like, if it was like 1992 and I was traveling from the United States to Italy, I would have to have my currency exchanged to that region.
The Role of Universal Solutions
But now I can go and use my visa debit card and I can transact in Italy, and that's kind of the same thing without having to go from USD to italian currency. And that's essentially what wire network is doing for blockchain. So am I correct? Yeah, exactly. Like, we built the financial rails of what we knew the blockchain needed. Again, the real discovery was we thought were building this for humans. We didn't know AI in 2020 when we started this, we thought that, hey, blockchain needs to unite all these different architectures to have all these users in one area, to have liquidity in one area.
The Future of AI Agents and Blockchain
Just like how the world stock markets work, where you have a Schwab or fidelity account and you can buy any stock all over the world, and it just routes to wherever that stock is held, whatever stock exchange, and then it comes back and sits in your investment account. We needed to do that for blockchain. So that's what we recognize and we built for so long. And now, like, with agents predominantly, like, going forward, there's going to be less and less human transactions on chain, and there's going to be more and more AI agent transactions on chain. And once that shift happens, we're not talking equilibrium like it's going to hockey stick, where these agents are going to have agents, you would do five transactions in a day as a human.
Anticipating Future Trends
You might do 200 or more with your agents. So on chain transactions are about to balloon, and fortunately, our architecture fits perfectly to allow that to happen. Awesome.
The Emergence of AI Agents
You were just saying that we're moving into a space where it's predominantly going to be AI agents. There's going to be potentially billions of AI agents that are trading and that are operating across many spaces, but particularly web three. So, Mikey, I want to direct a question to you. I'm hyper vigilant about owning our intelligence. I'm hyper vigilant about sovereignty and about the ability for us as individuals to be able to have that right to transact and to be operating on behalf of our best interests. And so with that said, is an autonomous AI agent. Is that really owning our intelligence if. If that AI agent has the ability to autonomously operate?
The History and Future of AI
Yeah, I mean, it's a great question. So there's two things. The first thing that I'm going to start with is there weren't many hunter gatherers that were able to skip farming and be successful and have grandkids that were in a good spot. Humans embracing technology and building systems on it has kind of been a survival of the fittest thing for much longer than any of us have been around. And so we are in a spot where we have this novel thing called AI. It's already looked at pretty much every piece of data that's ever been on the Internet. The stuff that you put on your Facebook posts in 2008, but didn't realize all the companies were scraping all the big data stuff, information licensed from your General Motors car so that your insurance company can. Can watch you and understand what your risks are. Like all of this data, everything that we've done is like this data cloud.
Decentralization and the Role of AI
And AI agents are built to be able to find the signal from the noise and be able to make decisions. And so we find ourselves in this space in which centralized companies that are multinational and in a lot of cases more powerful than the governments themselves, whose rules they're supposed to fall under, are the ones that own this. And so the default would be for us to do nothing and for us to essentially have a new group of very few people that control intelligence. And so that's the default. If we don't do anything, that's just what's going to happen. There is an alternative, which is what if we actually build an open source ecosystem, and we build it in a way that it's composable so that a theoric agent, right, like, when you think about all the code that they're writing and the intelligence of people who worked at Google and who are some of the best in the world on that side.
Technical Innovations and AI Agents
And then that agent needs to be able to transact, well it can just plug straight into wire. If that agent needs to transact with a Morpheus agent, which is a totally different type of agent, that's more like Linux, that's more community driven. And those two agents need to be able to transact. That's the freedom to transact. Now here's the thing that 6079 has worked on for a very long time is how do we make sure that these agents can transact not only in currency or tokens, that's one thing that they need to be able to do. The other thing is they need to be able to transact with compute. Today the cool thing is that exhibits has gone out and been a leader. Exhibits has figured out a model for being able to offer up to many decentralized networks, GPU's that are distributed geographically in a whole bunch of different places, that they're able to figure out how to get the financials together so that those GPU's can be made available.
The Future of AI Interaction
And you can kind of think about it like maybe like a micro strategies or something like that for bitcoin where there's one group of people that are going out and leading the way and kind of acting as like a central leader for making something that's really hard happen. What 679 does, in addition to that through proof of inference is we're working to make it so that when you're interacting with an exhibits computer or some random person's computer, that AI agent can understand the hardware that's underneath of it. That the information that it's passing back and forth is actually true and not being manipulated. That the weights and the fine tuning are not being manipulated. Just imagine that a country wants to change the way everybody thinks about it. Well they might just update models to be really positive towards their country and maybe negative about their enemies. That's what 679 focuses on, is that freedom to transact and that freedom to have intelligence.
Open Source and Decentralization
And so we find ourselves in a really good spot where all of us, even though in web two we might all be competitors, what we're actually doing is we're actually building one mega platform. And that platform is open source, decentralized, composable, protocol driven. It's all these things that allow everybody who's on this call to be a part of it, to find your space, to find what your gifts are and to be able to actually contribute to it. And the decentralized AI ecosystem is going to be the sum of what we all put into it. And in my opinion, it's going in the same way that free market capitalism and democracy have been able to outperform centralized systems at every stage.
Quality and Integrity in AI
Let me build a little on Mikey's comments there. I think we're going to see this evolution where near term agents are tools and we want them to be something that are owned and personalized, and we continue to maintain choice in the market and we don't have any centralized entity dictate for us what will work along the way. Incredibly important. Mikey's right about understanding integrity. We also think incredibly important. And a big focus in theoric is actually the broader question of quality. Right? Like you could just as well put your thumb on the scale and bias the output of an agent by prompting it, by giving it a bunch of information. So even if the model was unbiased, the agent could be heavily biased, right? And similarly could be. Could be incentivized to deceive the user or do bad things.
Community Feedback and AI Agents
So triangulating around community feedback with incentives, triangulating around automatic AI agents, assessing other agents in a decentralized way, is a big part of our plans. These are ways to really ensure that you have strong quality signals and reputation for agents. Near term, that's really important. But I think what we're going to see and where it gets interesting is over time, AI agents are going to get more and more capability. And at some point you do have to ask, when are agents even conscious? I don't think anybody knows when you're going to get AI that's conscious, but agents will be the form in which AI is conscious, the sort of the complete system that does things. And over time, when does that have rights? What is it? What's called a moral patient? What is it entitled to things. The tricky part is, I think we can all say right now that we're nowhere close.
The Consciousness of AI
So an old colleague of mine, Blake Lemoyne, at Google very early on went way out on a limb and got fired over insisting that a precursor to Google, Gemini, was conscious. So I think almost everyone today agrees that the AI we have is not conscious. It's a tool that serves us. But when will it be the case that the AI's we're interacting with have rights and are meaningful. Right. It's unprecedented, and it could be arriving sooner than we think. Right. So there's a lot of deep questions here, and the future is arriving very rapidly. Well, Ron, you made a point there that I was going touch on anyway, but it's, we know what models are given to the public, right?
The Challenge of Centralization vs. Decentralization
Like, we have no idea what AI is, is in there in the, you know, from the private side or from a government side. And that's part of the problem, you know, of what we're all doing here. Like, a lot of us are, you know, looked at as, quote unquote, like, you know, blockchain companies. We're not, our battle is not with other blockchain companies. It's not PvP anymore, where you're trying to get people from Ethereum. You start another l one like Solana, and then you're fighting for that user base, like what we're building. You're not fighting for that user base. We're fighting the centralization versus decentralization battle.
Rapid Advancements in AI Agents
Centralized AI agents are coming very fast. If you just heard Sam Altman's podcast, I think from yesterday or the day before, like, he's talking about like, AI agents are coming way faster than everyone thinks. Or if you talk to, if you listen to like Eric Schmidt, which is like the ex CEO of Google talks about the same thing, like, this isn't far in the future, this is literally right now. Because once it happens, it's not like this slow building adoption curve where, you know, in twelve months, like, yeah, maybe a few people know about it. It's like, no, you're all of us. By the end of next year, probably gonna have hundreds if not thousands of agents working for us, especially the ones that are in this space who are, you know, trying to gather as much information as possible and get ahead of the curve.
Decentralization and User Empowerment
That's how quickly it's gonna happen. And so all we're trying to do is say, okay, yeah, centralized agents are going to be a thing, and we're trying to get our architecture collectively to where we can compete with those decentralized or with that centralized model and showcase the value and the dangers of using a centralized model to get people to come over and use these decentralized models. It's super important that our value proposition is conveyed properly so that the users can have a choice, as you know, do I want these groups, do I want these agents to be controlled by organizations that don't have my best interests at heart? Or do I want them self sovereign and encrypted.
Personal AI Agent Evolution
Yeah, I mean, you guys, there was a lot of things that were just shared, a lot of nuggets that were just broken down that, of course, I want to dive into. Particularly the piece about that, Ron, you were talking about, like, when does an AI agent become conscious? You know, I mean, this is a subject that Mikey and I have extensively discussed and that I'm dying to dive into. I want to kind of keep it high level. And if we have some time at the end, I would definitely like to discuss this in a little bit more depth because I think that the reality is that the way that we end up interfacing, interacting rather with AI agents and AI in general, this is the determining factor.
Computing Power and AI Deployment
And then it's how do we embed, how do we have the AI be intra dependent on humans? How do we relate. This is the subject matter that's a, that's the next layer to this. But I want to talk a little bit about compute. And Russ, I want to ask you, and then Logarithm, our good friend Lariss Bard, rather, I want to ask you this. I want you to chime in on this as well. But Russ, how do you see AI agents deploying exhibits, specifically exhibits GPU's? Sure. You ask when AI agents becoming a, you know, aware and without humans, and that's going to take significant compute processing power, right. It's not going to happen overnight.
Significance of Compute Power
So to get these AI agents to that particular point, you know, we're going to need compute power for things like parallel processing power. So we need lots of compute. We're going to need compute power for deep learning, large scale. So, you know, things like exhibits and ability to provide, you know, high quality GPU's. Distributed networks are going to do things like training these AI models, speeding up the training times, scaling the model. So being able to be, to have enough GPU's across the network to scale. Right. We're going to have to do, you know, inferencing and real time applications.
Edge Computing and AI
So, you know, if you have a distributed network, you have to make sure that you have, you know, I'm going to call it almost like edge computing. You're going to have computing at the place where, you know, inferencing is happening in real time. So exhibits has distributed networks all over the world. So we're going to be able to have that. To speed things up. We need the GPU's for, you know, reinforcement learning. So there's, you know, the compute is at the heart of all the things that are going to be needed to make these AI agents better, smarter and faster training.
AI integration and Daily Life
So we see ourselves being a big part of that and having reliable GPU's, fastest GPU's, distributed GPU's at the edge. Well positioned for that beautiful and logarithm. I would love to hear your two cent in general about the ability to for how you see AI agents deploying GPU's and what that looks like. Not even just AI agents, but I think that even since the very first computers, people have consistently under forecast how much computation the average human will want, will desire, will need. And it's gone from like you just have a server mainframe to now everyone has a pocket of computation in their pocket.
The Increasing Need for Computation
And it's gone from we have access to a little calculator maybe, to now you can't even really exist in society and apply for a job unless you have access to a computer and the Internet, right? It's become integrated in our lives. And what I see happening with AI agents over the long term is you're going to have a personal AI agents for most people in first world countries and you're, and when I say personal, I mean it's going to take what is a general model, a sort of best of breed, a llama 700, b whatever, and then it's going to inject your own personal biases off of your behaviors and how you like the feedback trail that you build up over your life, over your preferences, over how you want it to represent you.
Training Personal AI Agents
And every time an iteration of the main general model comes out, you then have to go and retrain the off of the entire previous personal history off of the next general model in order to get it as smart as it can be. And that takes a lot of computation. And this is going to be an ongoing process. I think over the next hundred years we're just going to get bigger and bigger models and we're going to get better at having a province trail of all of your preferences. We're going to get better at making it convenient to retrain on these things and basically build up a capable personal agent to represent you and your interests on the Internet, right? And it will do all kinds of things for you integrated in your daily life.
AI as a Shield Against Misinformation
It will probably integrate with provenance trails on the Internet and put on the blockchain to prevent you from seeing misinformation from other AI's. And we have basically we're starting to live in the disinformation or post information age as the cost of misinformation is plummeting with the advent of AI's. And how do you protect against that? Well, I think you're going to need AI as representing you to protect you from that and to filter down to information that you find valuable. I think we're going to get off of just social media platforms and we're going to start to see search.
The Future of AI Queries
And so when you start giving an AI a very specific query that's basically like a Google search, and you start to give it a more broad directive like entertain me, then what do I need Reddit for? What do I need a Facebook feed for? What do I like? Just digest the information from the Internet for me across all these different curated whatever sites and feed me the things I think are most relevant, impactful that I want to see that are going to have the best impact on my life. Right. And we're going to stop asking AI's for these very specific things. We're going to start giving them more broad directives like make me, help me to be the best person I can be according to what my values are, right.
The Evolving Role of AI
And it's going to take a more active role in your life. And just the, just imagine the amount of computation required for all of that. People have. I remember there's a quote in the early Microsoft days where it's like no one will ever need more than sixty four k of memory, you know, and look back at something like that. Like what? You know, it's like a single image, right. it's, we've consistently under forecast the amount of computation people need access to. And I don't think that's going, we're going to continue to under forecast it.
The Future of Computation and AI Agents
and that's just going to lead to basically upside surprises continuously in the AI sector because people are under forecasting how much AI we're going to use, how much compute we're going to use in our daily lives. and AI agents, I think, are an integral part of the next generation of AI technology for everyone. Something I wanted to add on top of that. I mean, what we're looking at is we believe that demand will outpace supply by about two x to three x. And like you're saying we may be understating that we don't know what's coming out one, two, three years from now.
The Chip Manufacturing Challenge
That might be so compute intensive that we can't think about it. But even what we see now, with what we know now, we see demand outpacing supply two to three x. It just can't keep up. Yeah. And building on top of that, there's a problem where software you can print and spread across the world very quickly. Chips, you can't. If I was to suddenly have a new design for the next gen AI chip out of, you know, Blackwell plus, whatever you want to call it, right? That doesn't start getting made for five years. So if we have the next design today, we have a sudden, like, we just went through a qualitative unlock in the capability of AI in the last couple of years as we finally saw the mass proliferation of diffusion and LLM models, right.
The Evolution of AI Capabilities
That that basically took AI from a sort of classification role to a generative role. And so the software portion of that spread across the world like wildfire, and we'll see another of that with AI agents. But the hardware portion of that can't keep up with these qualitative unlocks. And we start to see AI that's going to start programming the next AI.
Current Limitations in Technology
And you know, that's happening already, right? The software component for this can move at lightning speed compared to what the hardware capability. The manufacturing capabilities of basically our species are not even just, but just our ability. What about power as a bottleneck? I mean, I don't know anybody, Microsoft is going to bring one of the nuclear reactors in three Mile island back online to power all of these gpu's, right? Data center space. So we're facing other limitations that we didn't think about 510 years ago. So, yeah, hardware, software, maybe not, but power, there's a lot of factors in place that could slow us down.
Infrastructure and Supply Chain Issues
Yeah. I think I would add on to what you said. It is, of course, the whole infrastructure pile. It is the Internet speeds. It is the power, it is the silicon, it's our ability to manufacture and deploy these things, a whole supply chain of stuff that has to come together to basically enable these, the high enterprise grade compute that we're looking for. And of course, some people are going to figure out ways of having a distributed network of more commodity grade compute, but there's always going to be an edge with enterprise grade compute. And so if you're playing the stock market, if you're in a purely financial realm, you're not going to take second best. If you are, these companies in kind of an AI turf war, you're not going to take second best, right. You're not going to accept defeat there.
Acknowledgements and Gratitude
Thank you so much, guys. Thank you, Logris, for joining. I know that, you know, you've got, I heard the coughs in the background, I know that you've got some. A sick kiddo over there, so we appreciate you being willing to. To join. And despite that, and I just. I just want to say we're coming to the top of the hour here. I just. First of all, I just want to thank Ron, Ken, Mikey, Russ, Logris for joining in the conversation, but on another level, for being committed to independent AI. And the reason why I say that is because the reality is that there's many paths that we can take.
Commitment to Higher Values in AI
There's many. There's many paths that we can take, and tech, even. And there's easier roads. There's easier roads to take. And so what I'm seeing in the space here are individuals that are committed to a higher calling, and that is a rare commodity in the world these days. And I think, though, it is going to be. I think it's moving into being in style, I think with the expedient nature of the world that we have created, with technology and social media and our phones. I think, though, that there's a backlash. There's sort of an equal and opposite reaction that's occurring, and that people are realizing that authenticity and that creating something that is real, that being useful to our fellow community members and citizens and families, is the essence of being a person.
Building a Unified Front
And so I just want to just take my hats off to you guys for making the choices and being who you guys are. And the people in this call, there's not people on this call that are on a different mission. People who care about this are here. And I believe that while we are a small, we represent, as in the decentralized, independent AI people, web three people, we're a small blip in the radar right now. But what we're creating is the pieces, the spokes, to the bigger picture. The beauty of web three is that we have the ability to be very, very modular. That's the nature of decentralized technology and ethos. And within that gives us the ability to create a united front that can actually stand up to these five, six enterprises and governments that do not have our best interest in mind.
Vision for Independent AI
And Ron. Ron has to drop right at noon. Ron, if you have any quick things to say before you drop, we're a minute up, and I just. I want to hear that. Well, thank you. It's been a great conversation. 100% agree. I think there's so much power in us working together, and I'm optimistic that the open community, the web three community, will come together in open source and in collaboration and will produce a better outcome. I also think. We didn't talk a lot about it, but we have a lot of work to do on governance and making sure that we have rules and set rules, that decentralization and community governance doesn't mean no governance. And it's an incredibly important part of the mission.
Balancing Risks of Decentralization
We have to counteract the risks of decentralization even as we fight the risks of centralization. So, thank you and great chatting with you here today. Yeah, it was awesome. Ron, thank you so much. This is absolutely the bleeding edge of technology that you're producing, and so we highly appreciate your perspective and sharing that with us. We're honored. Have a great day. I know you have to drop. so I want to just turn it over. I mean, whoever has to drop, that's all good. I totally understand. we'll, we'll wrap it up, you know, quickly here.
Bridging Web Two and Web Three
But, you know, I want to just kind of touch base here with Mike of 6079, and I want to get your closing thoughts, but I want to. I want to just talk a little bit about our consortium and just, just, I want to talk about. Because it's, it's in line with what I was just saying. We're spokes in this kind of wheel, but we have the ability in web three and in open source to come together and create a unified front. And I want to understand, or I want the audience to hear what your vision is around that. Yeah, absolutely. So for independent AI to be, like, actually independent and not just a brand, these things actually need to all be able to work together, and they need to be protocols, and they need to, like Ron was saying, we need a.
Creating Shared Standards
Advances in governance, and so there's all these things that need to happen, and everybody here is essentially like, playing catch up to what the trillion dollar companies are doing. And so in the spring, we set out and had conversations with basically 27 different projects. And pretty much everybody that came on saw the vision and saw how for their protocol to be successful, it would beneficial to build standards together, especially around the difficult things. And so we set up. Initially it was called proof of inference consortium, and it's kind of morphed into this bigger thing because there's more needs.
Building Collaboration and Interoperability
And so it's kind of morphed into this independent AI institute. And the institute, there's a whole bunch of projects coming together to put on an event at permissionless to kind of paint a vision for what the next season of this could look like, but these are all people that don't have, like, contracts with each other, that don't have an obligation, like you would see in web two. But what they have is they have shared interest, and they're building these protocols, and they're building them so they can interoperate and not worrying about the moats that they need to create because they see how big the opportunity is.
Governance and AI Collaboration
And I see this as being much bigger than just like, these groups here. I think there's hundreds of companies and research labs working on AI around the world that at the core of it, they already believe the same things that are on the same mission. They're just doing a small piece of it. And so I see this becoming an entity both in terms of, like, Ron was talking about governance, like, building the governance that we would need to actually have artificial superintelligence co evolve with humans, symbiotic relationships. Right.
Understanding AI Through Blockchain
If you think about it, without blockchain, you really don't even have an ability to understand what an AI is doing. It's moving too fast. It's using language that we don't speak. The ability to have transactions, interactions, and even actions logged on chain with something like wire or others as they come out is critical. And there are going to be some people that really want to understand exactly what their agent's doing, and they're going to want to have a blockchain to do that. And there's going to be others that design agents where they're like, I specifically don't want my agent to be censored.
Ensuring Openness of AI Infrastructure
I view this as freedom of press. I view this, some even view it as freedom of religion, that it's that important. And so the important thing is, like the Internet, that it's open and everyone can use it, and that it's a common public good. AI should be a common public good, at least the infrastructure that it all runs on, and we all get to benefit when we build it together. Yeah, I appreciate that summary. Like, Mikey, just hats off. You have the ability to compact a message so eloquently that has so many tendrils and so many working parts, and I really just appreciate that.
Closing Thoughts on AI's Future
And, you know, you've just been such a wonderful guest on the exhibit sessions, Russ, I think you have to bounce pretty soon. So I don't. I don't want to. I don't want to keep you. But, Russ, give me some closing thoughts around compute AI, aging economy, and or the necessity of web three, offering real solutions as opposed to narratives. Yeah, that's a lot my bad. That's okay. I came from the web two space and a lot of like, AI and ML enterprises, and I'm just fascinated at what I see in web three.
Interconnections Between Web Two and Web Three
And, you know, not only just the pace and the speed of creation, adoption of programs and AI and ML and things, but, you know, the ecosystem, the way they do things, the decentralization of hacking, how things might work better. I think we're going to start to see, I'm hoping, a bridge between Web two and Web three, where they don't become as discernible as they are now. But there's a lot each can learn from each other. And GPU compute is simply one, and the decentralization, the distribution, you know, the tokenomics of Web three and incentivizing contributors.
Future Integration of AI and Web Technologies
So, you know, I think those are the things that are going to help AI agents. You know, the old ways of training and getting training data and things was very cumbersome. Web three opens that up and it allows a much faster proliferation of collection of data, training of data, the GPU to distribute and get that done. So I'm excited to see how Web three matures and how enterprise Web two and web three start to meld together. So that's what I'm looking for in the coming months and years. Beautiful.
The Role of Wire in AI Development
And Ken, I just want to grab closing thoughts from you on all the above. The way that you see, you know, wire interfacing with AI agents, the way you see our mission, whatever, you know, whatever you want to drop the audience, and I want to hear. For sure. Yeah, I'll keep it high level. I mean, you said it earlier, we could have chose to centralize parts of these things and try and generate as much revenue as possible and try to create walls that will allow us to monetize forever. None of us in this independent AI institute are doing that.
Shared Values in AI Innovation
The enemy is too big. The bad outcome is too tangible and real for us to do that right now. Yeah, we're all going to do very well for what we're building, but we're not trying to maximize. What we're trying to maximize is allowing everyone to maintain their sovereignty and to enjoy the growth of what this AI revolution is going to do for them. And we'll figure out where all the tips lay later. But we're all wherever there's a blurred line, it doesn't matter.
Harnessing Collective Strength
We all have the same ethos and we're working together, and whatever makes sense to build the best, fastest, most secure product, that's where we're all at, and we're open sourcing, specifically wire, open source. It's utl. You can go on GitHub and start viewing it and see that it's real and that we've done it and what you know, and then you can start to figure out how to contribute. Like, we want everyone to contribute like this.
A Call to Action in AI Development
It started out as us at wire, it started out with our dev team. It can't end that way. Like, it has to be a community, it has to be a movement. Like, we need as many people to get involved as we can, whether it's developers or community, whatever it is, whatever, you know, whatever your expertise or skillset is, like, come join all of us and let's build this all together. And I promise you, there's nothing, there's no better vertical for anyone that's listening to dive in on and contribute and gain value.
The Future of Humanity and AI
This is the next generation of humanity. It's happening right now. You have no idea how quickly it's happening. And so I just implore all of you, like, continue to educate yourself, dive into all these projects, seeing how you can contribute, seeing how you can help. And trust me, there's going to be a lot of fruits to, you know, to be able to fill your basket with for the effort that you put in. Thanks. Thanks so much.
Wrapping Up the Discussion
Ken, thank you so much for your time. Thanks for your energy, thanks for your input, and thanks for Wired.net work. Logris, I want to close out with you, and I want to just say, man, I want to with you and with actually the whole crew here. I mean, the things that I want to dig into are vast, but we're kind of limited on time. And I guess that's for a future day. But Logvis, I'd love to hear your closing thoughts on our, on our discussion.
Human Rights and Computing Access
Yeah, so cryptocurrency has enshrined the right to transact in our society over the last ten years. This is a human right that they were, have been trying to deprecate because they couldn't outlaw it. So they've been trying to deprecate it basically since the advent of the credit card. Right now, with DPIN coming online, we're trying to enshrine the right to compute to all humanity, because even now they are trying to classify compute as a like, in the same way of ordinance.
Addressing Global Restrictions on Computing
Like, we cannot ship our Nvidia cards up to certain other countries because, you know, they want to consider a weapons grade munition. And that is ridiculous and a huge violation of human rights. But here we are, so the progress of this industry is, yes, we want people to, of course, get wealthy and do well for themselves in the world. And there's a lot of ground to pioneer here and a lot of value add that we're in great for humanity, and some of that will be monetary.
The Ethical Dimensions of AI
But the larger story here is one of ethics and human rights, and we are trying to enshrine the human right to transact. And the largest customer of that in the next century is going to be AI, and AI agents for you. That's the most accessible part of this to the average person. The same way that they're going to access the Internet via web browser, you're going to have your personal agent. That's how it's going to interact with a whole ecosystem of AI's, really.
Staying Focused on Human Rights
I hope that we maintain our focus on that larger goal in a ecosystem of cryptocurrency rife with meme coins and profit seeking and scams and grifters and whatnot. I realize there's permissionless is an extremely important concept around here, but we need to keep our eye on the goal of the value add of human rights and what this means for the human condition. And I think that the people here on this call are very aligned with that.
Conclusion and Gratitude
So thank you all for the chance to talk. Thank you so much. Lageris. Thank you, everyone. Thank you for the. Thank you, listeners. Thanks, Russ. Thanks, Mikey and Ron and Ken. Have a great day.
