The AI Daily Brief: Artificial Intelligence News and Analysis - Privacy, Censorship and AI: A Conversation with Venice.ai

Episode Date: July 5, 2024

On this holiday weekend bonus episode, NLW is joined by Erik Voorhees and Teana Baker-Taylor of Venice.ai, a new LLM focused on data privacy and anti-censorship. Concerned about being spied on? Tired of censored responses? AI Daily Brief listeners receive a 20% discount on Venice Pro. Visit ⁠⁠https://venice.ai/nlw⁠⁠ and enter the discount code NLWDAILYBRIEF. Learn how to use AI with the world's biggest library of fun and useful tutorials: https://besuper.ai/ Use code 'summerfun' to join the summer challenge and get 50% off your two first months The AI Daily Brief helps you understand the most important news and discussions in AI. Subscribe to the podcast version of The AI Daily Brief wherever you listen: https://pod.link/1680633614 Subscribe to the newsletter: https://aidailybrief.beehiiv.com/ Join our Discord: https://bit.ly/aibreakdown

Today on the AI Daily Brief, I'm joined by the leaders of the new OpenAI project, Venice. The AI Daily Brief is a daily podcast and video about the most important news and discussions in AI. To join the conversation, follow the Discord link in our show notes. When I heard about Venice AI a couple months ago, I was very excited. For those of you outside the crypto world, the team behind this company are some of the most fiercely philosophically respected in the space. These are folks who have long been banners of the principles that underlie that industry, principles of openness, decentralization, permissionless systems and individual sovereignty.

Given the capacity for AI to be a force for centralization, I was incredibly interested to see what they would do. Well, what they're doing is called venous.a.i, and they introduced it with a piece called The Separation of Mind and State. The piece reads, It is clear that central powers shall always desire to capture human institutions. Money, religion, education, business, even language and mathematics itself.

If monopoly control over God or language or money should be granted to no one, then at the dawn of powerful machine intelligence we should ask ourselves, what of monopoly control over mind? To whom do we grant license over intelligence itself? The piece continues. All good people care about safety. The important question is safety best achieved through coercive centralization or through open decentralization.

Some well-organized voices are certain it's the former. Observe the enthusiastic alliance between large tech firms, which naturally wish to curtail competition from upstarts, and the state which has never seen a thing over which it didn't desire jurisdiction. There is another way. Transparency and decentralization are better safety mechanism than appeals to experts in state licensure. The former tends towards iterative improvement, while the latter tends towards complacency and stagnation. So what they came up with is called Venice, a private, permissionless, LLM.

Venice, they write, utilizes leading open source AI models to deliver text code and image generation to your web browser or mobile app. The second point, they say, is about censorship. Every person who has used the leading AI apps has observed the weird, creepy, paternalistic censorship, and it's getting worse. Are you interacting with AI or a multi-billion-dollar bias simulator? We don't believe they continue. The thoughts you develop in your mind are our business to regulate and censor. It follows that we don't believe the thoughts you develop with the help of a machine mind are our business to regulate and censor either.

The solution is not to force tech companies to act in certain ways. The solution is to build alternatives and humbly offer them. Venice is joining as the newest sponsor of the AI Daily Brief. This bonus episode is a conversation with Eric Voorhees and Tiana Baker-Taylor of Venice about where the project came from and how they they see the current shape of the AI landscape. Despite the fact that these folks come from the world of crypto, I don't believe you have to be the least bit interested in cryptocurrency to be interested in what they're building with Venice. So let's dive into the conversation and hear about what a

different approach to LLMs could look like. All right, guys, welcome to the AI Daily Brief. Eric Tiana, how are you doing? Doing great. Hey, Nathan. Yeah, great. Thanks so much for having us. Yeah, no, I'm super excited about this. So, you know, as all my listeners know, You guys are a new sponsor of the show. But I think that what, you know, I was mentioning before this in the introduction is that, you know, you guys are both people that I've known for a really long time. The project is one that's super exciting. It's the type of thing that, you know, when I was doing marketing consulting full time,

I would have been beating down your door to actually try to work with you guys. Because I think it's an important and a really interesting project. So, you know, what I wanted to do with this conversation is give a lot of folks who I think, you know, don't know you guys yet. the chance to learn more about you and where this company comes from, because its roots go back a lot farther than chat GPT launching in November 2022, I think. But so let's get started maybe with just some personal introductions, you know, who you guys are. And then we'll talk about how Venice came to be. Yeah, T. You want to go first? Sure. So I am a reformed banker,

spent the majority of my career in financial services. And about, eight years ago, I noticed that a lot of the projects that I was working on that were very focused on financial inclusion weren't going anywhere. And it was quite frustrating. And so one of the alternatives that was really coming into its own was cryptocurrency and how crypto could be used for people that don't have access to bank accounts that have to walk miles after getting paid in cash home and our targets for nefarious actors and how crypto could solve some of those problems. And so that's how I originally got interested in cryptocurrency and started my career full time in that. So I've spent a lot of time working with policymakers and a lot of time with

companies building actual interfaces for people to be able to purchase crypto and trade it and invest it, et cetera. So still kind of in that financial services space. And recently, I had been speaking to Eric for a couple of years. He was definitely someone in the industry that I looked up to and admired and said to him, if, you know, you decided to do a new project after he had ended his last project, that I would love to work with him in the future. And so simultaneously, I had been really kind of doing deep dives into some of the generative AI options that people were using for different types of efficiencies and was a little concerned around the level of censorship and the way that my data seemed to be kind of triangulated with other types of services

that I was using, like search, for example. And simultaneously, Eric called me and said, hey, would you like to join me? I'm going to build a open source generative AI app. And I just thought it was serendipity. Amazing. Yeah, so I come from the crypto world. It's been my hobby and passion in life for 12 years or so, 12, 13 years, and fell in love with it as a way to solve what I felt as the most pressing issue in the world, which is the debasement of currency.

And really, through that learned about permissionless systems and trustless systems and open source software. And it really led me down a path of just a new way of thinking about good and bad software. And so that's been my whole world for a while. I built a couple of companies in the crypto world. Satoshi Dice was the first one. It was like a Bitcoin casino back in the day. It was half of all the Bitcoin transactions in the world up through 2013.

and built a company called ShapeShift, which was an exchange for digital assets that didn't hold customer money. So I've always cared about protecting people through the way that software is designed. And so, you know, after ShapeShift, these last couple of years, I've gotten into the AI world just as a hobby because, you know, who hasn't? It's so cool. And started realizing that like it's actually heading into kind of a dystopian future. if certain things aren't changed. And primarily, I wanted to make an open source app that allowed people access to very powerful AI technologies without centralization and censorship.

So that's where the idea for Venice came from. And we can dive into that whenever, but that's my background. Amazing. So I think actually, Eric, it's useful perhaps for folks who, you know, don't know the history of ShapeShift, part of what made it interesting as an observer from the outside is it was sort of constantly moving towards greater decentralization throughout the course of the project, you know, sort of finally ending up in this state where you guys kind of maxed out how decentralized the system had been. And I feel like, you know, to the extent that that was the, you know,

the immediate predecessor to Venice, it might be useful to sort of get an understanding of how you're thinking about software design and system design had been evolving, sort of at the end of that journey moving into when you started thinking about AI. Yeah, I think maybe a good analogy is like things like mathematics or language are decentralized technologies, right? No one controls math. No one controls language. These are tools that all people in the world can use openly. They can use them differently from each other, they can change them with time, improve on them. And because these technologies are open and accessible to everyone, you know, without borders, humanity is better for it. And it doesn't really matter, like, what any politician says about language or mathematics,

like anyone can engage in these things. And I think that's very important for humanity. Something like money, I feel like belongs in the same category. And so that's why I cared about decentralization in the context of cryptocurrency. And when it comes to AI, we're talking about seriously powerful intelligent systems. And I think all sorts of good and bad consequences will come from this. But one thing that I feel very strongly about is that this technology is so powerful, it really needs to be democratized.

Like we don't want to live in a world where one or several large central companies are providing, you know, the AI, services for 90% of the planet. So that's really like the genesis of Venice. Let's talk about Venice and, you know, let's try to give the listeners a sense of exactly how it's set up and what makes it different or how you guys try to design it differently, sort of from the ground up. Yeah, well, so the elevator pitch is it's like a chat GPT app and it just doesn't spy on you

and it doesn't censor the information. That's pretty simple pitch, right? And this is basically something I wanted for myself. You know, like I'm a big fan at ChatGBTGPT, one of the most incredible tech products ever built. And yet, everything that you talk about with ChatGBT, GBT, or any of the other leading ones, it's all being recorded in one central location

where anyone of that company can read everything that you say to the machines and everything that's said back to you. AI systems in the future will be able to read, everything that you wrote and know you on a level that is perhaps more intimate than you even know yourself. And so I just, I wanted to engage with these AI systems, but I didn't want that degree of privacy taken away from me. But I didn't really know what to do until I learned about some of these open source models. You know, I kind of assumed that the leading models from Anthropic or Open AI were so far beyond anything in the

open source realm that it would be silly to try. And a few years ago that was absolutely true, but the open source models have become highly competitive. And for most use cases, they are roughly as good, not necessarily if measured by like certain scientific studies, but if you just ask someone to compare two systems that may interact with a casually, you know, they both feel in the same week. So when I realized that, I was like, wow, okay, let's put an app together that lets people have the experience of interacting with AI, you know, text image code, but not at all the Orwellian stuff. When it comes to how you think about Venice as a product, or maybe just the category of product is a better way to think about it. What is your bet on how consumers are going to make decisions

about which of these applications to use? I mean, inherently, you're sort of making a bet that for a lot of use cases, open source is going to provide close enough to parity that it will be other factors that matter to people. But when you're designing Venice, obviously there's sort of this core of not spying on you, this core of non-censorship. Are there other product decisions that you guys have made to try to make it more like the experience that you would have wanted out of an LLM, out of a chatbot? Yeah. Well, from the privacy angle, it's a tricky thing because everyone says they care about it, but very few people will actually like take action to use something differently for the sake of privacy. So, you know, I kind of knew that like just saying, oh, we're a private version of chat GPT, like that'll get some people, but it's not really going to be, it's not going to be emotionally compelling in the sense that to change people's behaviors.

But what we're finding is that the censorship side is actually something that people connect with really quickly. Like anyone who's used chat GPT has felt the paternalism of the answers that come back to you or don't come back to you or come back in a way where you can tell like that's not the machine replying to you. That's some human or some committee that doesn't want that to be discussed. Everyone's had that experience and I think most people just tolerate it. So when they try Venice, they have some of these interactions and that's not present and they immediately see it. And we get people commenting all the time and they're like just so like just grateful that they can have these kind of interactions without that paternalism. So that on the lack of censorship, I think, is what people will feel immediately. And then it's just about, you know, making sure that we are

roughly as good as the the other models, right? In terms of images, in terms of text. So we we think we're in that league and we also have built it in such a way that the speed of response is very quick So everyone that uses it just like sees how fast and easy they can have an open source LLM and sees how powerful it is immediately. I think the other thing that I would add on the design aspect is it really serves multiple audiences in a very simple and sleek design. So it provides access to open source LLMs that anyone who is familiar with AI and

familiar with open source software can go on to HigginFace and really drill into how of the models were curated and fine-tuned and trained in the first place, right? And so all that information is there completely transparently for somebody that knows what they're doing or someone who is curious and learning. Equally, the app then delivers an interaction with these open source models that you could potentially run on your own machine if you had, you know, the GPU power to do it. But it delivers it in a way for a mass market audience. So it's very simple to use. You don't have to toggle between an image generator and a chat generator for text. It's all sleekly embedded in one line so you can very easily move between those two types of interactions that

you might have. Equally within the image generation, there's a number of incredibly cool. And every day it seems like something, you know, cooler than what came out yesterday comes out today that is allowing people to really play with imagery and art and video. And some of the things that you can create are extraordinary, but you kind of have to know what you're doing, right? You need to understand Loras and you need to understand how to prompt the LLM in a way that's going to produce the image that you're looking for. So what's interesting within Venice is there are kind of pre-programmed different styles that you can generate images from. And I think for the new user, it's very accessible. So there's a balance between it appeals to a sophisticated user and you can really kind of dig into it and use it in a way that is more advanced and it equally caters to somebody who is brand new to AI.

And I think the idea around, you know, how are we going to change behavior? I think we're in a very different situation today than we might have been with money, for example. We all have learned behavior that has been, you know, ingrained within us in a sense. you know, childhood, generational knowledge around how we save, how we spend, you know, is distilled to us from our parents, where AI is brand new. So I think that if people understand the differences, then they are more apt to make an informed choice. And I think that's where some of the privacy things come into play. Maybe that's not the first thing that they're attracted to, but once they learn the benefits, I think it becomes an even more attractive value proposition.

It sounds almost like part of the product thesis is that the productization of LLMs in terms of making it a better user experience right now or up to Venice has only been available with the with this sort of at the cost of censorship and privacy, right? So the companies that have offered an experience that is, you know, kind of user-friendly and consumer. friendly have done so in the context of, you know, a particular set of restrictions around what people can and can't do and how they can and can interact with it, as well as these sort of privacy concerns. It sounds, though, that you guys are bringing a product perspective to this, where you're saying, look, you know, sure, you could use, you know, if you are comfortable running an open source model on your computer, great, you know, but the vast majority of people are not going to be able to do that. And so there needs to be a sort of something that has the same level or even greater user, you know,

usability, user friendliness, but without the costs of sort of, you know, data, data loss or, you know, just censorship more broadly. Yeah. People are always going to choose the easy product. And we can make judgments about that for better or worse, but that's clearly what people prefer, just empirically through their own behaviors. So we knew with Venice, like we have to make something that's as easy or easier to use than a chat GPT.

And if we can accomplish that and then give people. privacy by default and a lack of censorship, like we'll be on to something. So, okay, so let's zoom out a little bit because I'm interested in sort of broadening the conversation. So if you look right now at the sort of leading contenders when it comes to, you know, this category of LLMs and chatbots, there are a couple different theses for what will ultimately win the market. On the one end of the spectrum are the folks who are clearly focused on.

being the state of the art, right? And so this is the chat GPTs of the world. I think open AIs, almost their entire premise for how they're going to win this space is being ahead, right? And it's that sort of race for capabilities. On the other end of the spectrum, big tech is clearly making a bet that is saying it's actually about distribution and, you know, existing installs and how you plug models into that. And so they're aggressively leveraging, you know, their existing user base with effectively kind of good enough approaches or being willing to plug in other people. You know, Microsoft sort of sits somewhere in the middle of this being as close as they are to Open AI, whereas Apple with Apple intelligence is just extremely focused clearly on the distribution

in the installs. It feels like Venice is trying to carve a third path a little bit, which is, you know, has a similar philosophy of for a lot of different types of use cases, open source and sort of, you know, the state of the art, the pure state of the art is not the required condition. It's being, you know, sort of good enough, far enough along, but that there is a market and opportunity for the context in which that software sits in terms of what people can and can't do. I mean, is that how you guys see it as this sort of, you know, a, a third path alternative that you're trying to carve out? Yeah.

So I will give you an example of this in principle. So the image models on Venice are not quite as good as the image models that you'd use on mid-journey. And the LLMs that you're using on Venice are not quite as good as like Claude Opus. However, if you go to any of those services and try to create an image as innocuous as Trump and Biden having T, like you try to generate an image of that. you can't do it. These services simply will not.

They refuse to generate an image as innocuous, as two politicians having tea together. So we don't need to be like necessarily the cutting edge. We just need to like allow people to actually use the system for things that they want to do. So that's that's our niche. And just providing like open access to machine intelligence. And these things are moving so quickly that like, you know,

the state of the art is only maybe a couple months away from any open source model. So, you know, if you can deal with being a couple months behind the curve, but you can actually access everything you want to access and use it freely and openly without being spied on, I think there's a large market for that. And I think, too, again, if you look at how people are using this technology today, it's not so much a third lane, I think, of users, but if you are, graphic designer or, you know, you're a documentary filmmaker. Yes, this product isn't probably going to be fit for purpose for some of that more advanced, you know, programmatic stuff.

But I would argue that the majority of kind of everyday people use chat LLMs almost like in place of search, right? So you're able to ask a question and get an answer without having to kind of sort through a whole bunch of possible answers, right? And so that is incredibly more efficient. If you're just trying to make, you know, a funny picture of a dog or capture a moment or recreate a moment, then, you know, this is very sufficient for doing that. So I think that they're like with any type of technology, it depends on what you're using it for. And over time, obviously, we will be enhancing the product with new features and capabilities as they become. available and certainly as we have time to build them. But I don't think that the majority of people

are writing, you know, PhD dissertations and, you know, creating documentary films with AIA. It's kind of a niche group. And I think that there will always be companies that will cater to those niche groups of people and deliver the top of the, you know, state of the art technology for those particular purposes. Yeah. I mean, listen, I think that to some extent from where I'm sitting, it's as simple as, you know, if AI were to stop advancing right here, I still think it would disrupt basically every industry in terms of how people did things, right? And that is a very strong argument that huge swaths of use cases are, you know, do not require the pure farthest sort of state of the art to be extraordinarily disruptive, which creates an opportunity for people to make

different types of decisions within the market of options around which of these things that can deliver comparable results are they most interested in using, right? I don't think that most people are looking at avals when they're deciding which of these tools they like, you know, better to, you know, to the extent that they're even making that decision, they're just seeing which one feels more correct, right? You know, which one feels closer to the tone or, you know, whatever they're going for. So I do, I do think it's- Or which one will even answer you in the first place. Right. And I think that that, you know, so let's actually talk about how you guys, what your perception of where the discourse around this is. You know, obviously there's going to be some set of

people who are extremely strong and loud about these types of issues. Obviously, Elon Musk is trying to raise a flag, you know, for some of this. But I think a lot of people are, you know, one, he's a Rorschach test that mostly anything that comes out of his mouth, you know, says more about whether you like Elon or not than it does about whatever he's saying. However, he is, you know, I think when he's talking about these things, part of the reason that there's a lot. you know, that not everyone is listening is, is there's a perception that is sort of being self-serving with Grock and that he's just sort of got an axe to grind with Open AI. But, you know, have you guys, I guess, witnessed an evolution in how people are discussing this? Are you seeing it get louder

in terms of these questions of censorship? And, you know, when you think about who the market of people who are receptive to this message right now are, how do you think about it? Is it a group that sort of defined it any knowable way? Or is it just, you know, just, you know, just, you know, sort of an ever-expanding group that, you know, gets, gets kind of bigger and bigger than more that these issues come up. Yeah, I think that people are noticing it across the board. There are obviously privacy evangelists that notice these things first, right? And they're very open about it. Edward Stodd is one of those people that, you know, very often will send out a tweet when something happens in the news and he's like, this is crazy. Are people paying attention to what's

happening. And it doesn't necessarily matter what the specific, you know, instance was. But Edward Snowden is kind of one end of the spectrum. But I think, you know, we hear from our, you know, mainstream users that they find it refreshing that not only will Venice answer your question, but equally, it won't tell you that you shouldn't have asked the question in the first place. And I think that that is where people start to notice that kind of per se. And, you know, parochial patronizing tone that sometimes some of the, you know, big tech apps their models can take, right? So it's not just, we won't answer your question, but it's, you know, you really shouldn't be thinking about this. And so when technology is telling us not only, you know,

the supposed truth, but also curating what we should even be exploring, you know, intellectually, I think that's very problematic. And people do notice when they're being minded, you know, by a parent. And this parent happens to be, you know, a piece of technology. So I think that's the one thing that has stood out kind of across the mix from, you know, people that really care about privacy and that really care about, you know, information being censored or free speech to just your average everyday person that is, that is trying to potentially challenge their own views or to learn about a topic that, you know, some people consider. taboo. And I think that becomes the discussion. Like, who is the arbiter of discretion? Who decides what is taboo? Does that vary by culture? Of course it does. Does that vary by socioeconomic class,

potentially? And so when we start limiting people's critical thinking and the ability to try to extend their knowledge base, I think that's very problematic and it's really obvious. Yeah, I'll add that if you look forward, you know, just a few years, it's not hard to imagine various governments in your country or in other countries, which puts pressure on these centralized AI companies such that the censorship and the bias in the models isn't just coming from that company anymore, but is now coming from politicians behind the scenes. I think everyone can understand it. like if these systems had been around during COVID, what the AI could tell you about that virus and outbreak and the response to it would have been highly curated by various government authorities.

And so if you trust all the government authorities, like, you know, maybe you don't care about that. If you're skeptical and if you think that many different voices need to emerge in order for truth to be discovered, then that kind of censorship is really, really dangerous. And when you combine it with like the world's leading artificial intelligence machine learning systems, it can get pretty dystopian. And so all we want to do is build an alternative.

So that if that starts happening, you know, people have a different way of interacting with these systems. For what it's worth, there's also the extremely banal reality, which is I have to create thumbnails every day. And a lot of times I talk about Trump or Biden as relates to crypto or as relates to, you know, AI or as relates to whatever the topic. And when I go to try to create an image that has one of those guys in it, I'm not trying to start some deep fake war, you know, I want Trump shaking hands with a friggin robot so I can put it on, you know, the YouTube thumbnail. And there are there are huge numbers of use cases that are like completely legitimate, non-risky that, you know, these big broad brushes of what you can and can't do just, you know, overwhelm. And I think that when you run into those sort of contrasts, it removes ideology, at least initially from this. It is just completely practical barriers to actually using these tools for what you need them for.

Imagine if we were back at the start of the Internet, right? And the web browser had just come out. And you would try to do a search or something. And then once a while it would tell you that that search was invalid, that you couldn't look for that thing. That would be a very different experience than what we actually had in the 90s. And I think people appreciated the power and magic of that open ethos where you could type anything into the Google search and you'll get a range of answers. That quest for open knowledge, I think, served humanity very well. And it is tragic now that we have this new kind of information browser, these AI systems, and yet all sorts of the questions that you might ask get constrained or restricted.

I think this is a regression for human civilization, and we want to push back on that. Yeah, I think the one thing that I would add to that, too, is if we take a step back, I mean, the beginning of the Internet is certainly an excellent example, but let's go back even further. You know, the New Yorker and New Yorker cartoons have been around for a very, very long time. And parody, especially in politics, political parity is part of culture, right? And it can be protest, it can be comedic, it can be ironic. And so, you know, if someone is trying to create Donald Trump enjoying an ice cream cone on one of the centralized models and it just refuses to do it, I use that as an example because somebody sent me a note on Twitter the other day asking if I could create a picture of Donald Trump having an ice cream cone.

And Venice had no issue. doing that. Now, I appreciate that, you know, deep fakes are a concern, but I think that sometimes, and certainly in this case, I feel like the safety measures or, you know, the prevention, the risk mitigation that is being put in place is solving for a problem that hasn't yet kind of materialized in the way that, you know, some of the safety experts have predicted. And if we kind of lose our balance of, you know, just kind of good humor, the New Yorker is a great example of a cartoon that probably offends some people sometimes. And, you know, no one is trying to censor the artists of the New Yorker.

So this is a great segue into a conversation that I wanted to ask you about. You know, obviously a big part of this is the safety debate and what it looks like to have have guardrails or what types of guardrails should be around these systems. And I think that the level of discourse, well, I find the level of discourse around this, at least in policy circles, extremely frustrating. I think that there is this sort of, any politician who talks about this is going to start with some can statement around, you know, there's a lot of good that can come from this, but also a lot of bad and we need to buy.

And then it's sort of, you know, just insert something that looks like chat GPT could have said it to them rather than actually having a critical analysis of actually ranking the risks with these different systems. And so my presumption would be that part of the way that you guys think about it is just you've made a different assessment around where the biggest risks lie with these systems and the risk of centralization of control of these extremely powerful systems, the risk that centralized control can lead to shaping, you know, the broad public perception of what is or isn't real. Those risks for you guys, I would imagine, outweigh or rank higher than other types of risks that these companies are prioritizing. But how do you guys think about the state of the AI safety debate, you know, in general and then specifically perhaps as it relates to open source?

So this is where, like the background in crypto is very, very relevant. You know, like generally the world operates today with a money system that has, central parties that control it, right? So each central bank in a given jurisdiction is controlling the money, and the government makes rules on how money can be used and how much will be printed, what the price of money will be in the interest rate, et cetera. And a lot of people don't have a problem with that. They think that central authority like that is important, is effective.

And some of us simply believe differently that when something is important and consequential, decentralization, of power is actually like the safest path. So when it comes to AI, like I don't know whether it will be net good or net harmful. It'll probably be a mix of both. But I certainly don't think that any human in the world is smart enough to be in charge of that decision, nor any single committee, nor any single government, nor any single company. I think it's a complex problem. People will have different preferences, different cultures will have different preferences.

and the way that you establish good order and safety is through decentralization. And that's a hard sell for many people because they want to know someone's in charge. This is a very human instinct to want to know that there's a singular entity that's in charge of something. But in complex systems, that's a really dangerous impulse. And so, you know, this is why I think regardless of where you are on the safety debate, you should advocate for open source AI because if it's not dangerous, then it doesn't matter. If it is dangerous, open source is really the best way to make sure the entire world can see how things are getting built and developed.

So that's where we come down on it. And yeah, I'll leave it there. I think the one thing that I would add is when you talk to the average person, if we stick with Eric's analogy, around, you know, do you think that the central bank is doing a good job? Do you think that, you know, monetary policy that's being set is effective? And most people, you know, their hobby is not assessing monetary policy, right? So I think their view of whether or not the economy is doing well is kind of based on, you know, does everybody I know have a job? And, you know, can I afford my groceries, right?

Is inflation out of control? When you talk to people about which, how would you feel about a central bank digital current? which is programmable and traceable and is supposed to be digital cash, right? It's going to be cash that's issued digitally by the government. How do you feel about that? And oh, by the way, everything that you spend, unlike cash, will be able to monitor on all of the data around that transaction. The government will have access to.

And, and, and, and, and. Then you start to see people go, well, wait a minute, no, I don't want that. I want to be able to spend my money, how I want to spend my money. and I don't think that the government should have access to all that information. So going back to what I said earlier, I think that if people have access to clear information, the education around this need not be overly complicated, but once you really understand how the information about how you use these tools could be shared and with whom, the privacy element, it's not even that you have to care about,

privacy. It's more, you know, the individual is my individual sovereignty being put at jeopardy even more than I might have felt that it has been over whatever the last year, my lifetime, etc. Do you think that AI, the nature of AI specifically creates more centralization risks than even we've seen with other technologies? Yeah. The, the, the, the, the, the, the, the, the, the The strong impulse with AI is toward centralization, if for no other reason, than just the training of models, is a highly compute-intensive task that at least today has to be done in large data centers with highly specialized equipment and $100 million budgets. To the degree that that's true, there's a strong centralizing force. and I think meta deserves tremendous credit for being the largest company building the best frontier model

that is willing to open source it. I don't want to live in a world where they're the only ones doing that. And I think the better path is if people can figure out how to do decentralized training, there are some very cool projects working on that. And I think if that net gets cracked, then humanity is in great shape. but if that can happen, if training of frontier models must always be done with huge budgets on

centralized hardware, then it's going to be an uphill battle. But it's probably still a battle worth fighting. What if you, if you guys could write the script on the evolution of the AI space for the next, I don't know, whatever the period is, the next 12 months, the next 18 months, the next two years, what would be your your wish list in terms of consumer perception, in terms of, you know, you know, regulation in terms of, you know, any of these sort of big things that will shape how the industry evolves and how people interact with it. I mean, my hope would, my hope would be that the powers that like to centralize control

will abstain from trying to do that so quickly with AI. I think we live in a sort of like a honeymoon period right now where we have this brand new technology that's changing how the world works, I think, in largely very positive ways. And there is a tendency of people who don't build things, politicians, to see the flourishing of society and to try to grab hold of it and put guardrails on it and tell people how that flourishing may be used or may not be used, always, always under the name of safety. and I just I hope that that impulse is is resisted. It won't be resisted by the politicians,

but I hope it will be resisted by the public of whom we are humble members. Yeah, I think the one thing that I would like to see, and I think that if enough people believe it to be important, it will be a forcing function for everyone to simply be more transparent. So right now, you know, we refer to some of these models as black boxes. We don't know what their system prompt is saying. We don't know how the model is trained. And, you know, we don't necessarily always know how our inputs and the responses that we're getting are being used by that company either to build out their products or to, you know, fine or tune their models, et cetera.

There's just a lot we don't know. And for me, I think that, you know, sunlight is the best disinfectant, right? The more transparent and the more open, something is, then, you know, again, going back to trustless systems, I don't have to trust you because I can verify for myself exactly what is going on behind the scenes. And that is one of the things that open source models provide. And then I can make a decision. And so, you know, I still use chat GPT for certain things.

And for other things, I would choose not to, but I'm able to make an informed decision. And so I kind of think it kind of goes back a little bit to, you know, consent, right? I'm giving away this information and I know how it's going to be used and I'm okay with that versus I really have no idea and I'm just trusting you. So I think that more transparency in this space is going to enable users to feel more confident adopting this technology. and I think it's really important that people do. It's one of the things that I'm a little scared about is that people will be scared and just not use these tools

and will get leaped-frogged and not be able to be competitive in the workforce, for example. But I think that transparency is going to be the thing that helps that user adoption grow. There are a ton of really interesting places we could take this conversation. So one of the things that I'm excited

that we're going to do with you guys is have sort of, you know, some of these themes on a more recurring basis that we come back to. You know, things that we could get into are U.S. policy vis-a-vis China is a really interesting dimension of the open source conversation. One of the things that's fascinating about, for example, the Schumer guard or sort of guidelines, you know, document that just came out is it's very clearly, or it's much more slanted in the, in the direction of innovation to stay competitive with China than it is AI safety in the sort of way

that Europe was, which is very clearly. fascinating. That's a whole great conversation. I think another really interesting conversation that sort of touches on some of these themes is, you know, popular perception of AI as it relates to data, training, scraping, you know, it's an extraordinarily contentious space. And I think that there's, you know, part of that has to do with the fact that it emanates from these big tech companies which have lost trust. So, you know, we're going to come back to a lot of these different conversations over time, which is going to be super fun. But I really appreciate you guys. spending some time kind of laying the foundations and giving the groundwork here.

You know, like I said at the top, I think it's an extremely important project and something I'm really excited to have, you know, here on the Daily Brief. Thanks. It's been a good chat. Yeah. Thanks so much, Nathaniel. We look forward to check in with you periodically. Awesome.