Anthony Vinci - Founder at Vico.io

Welcome to another Founder Wisdom Podcast. We have Anthony Vinci with us today, founder and advisor and author. His company is called, uh, Vaico, vaico.io. You can also learn more about him at anthonyvinci.com. Uh, interesting background you have. I believe you have a PhD, right? Uh, you're into all sorts of things. Uh, you have your book the book, I think it's called "Fourth Intelligence Revolution," right? So eager to just discuss all of that with your background, Anthony, tell us a bit more about yourself.

Awesome, thanks for having me on. Yeah, bit of a wandering background. I did do a PhD and then became an intelligence officer. So I served abroad for a long time and I left and I went down the entrepreneur route. Initially, and I had a startup called Finder and then another one called Leviathan Analytics in New York several years ago, and then kind of wandered my way back into intelligence and became the CTO of an intelligence agency. They were looking for somebody who kind of knew intelligence, but knew tech and knew startups. And so I went in and my job, my role there was really to bring AI and commercial data into this agency. Which was super exciting for somebody. I went from managing a small team at a startup to managing all the tech in this giant organization and trying to bring AI. And this was close to 10 years ago, so it wasn't LLMs, it was computer vision, machine learning, kind of different generation. And since then, I went into investing for a bit at Bridgewater Associates and then Cerberus Capital, but I left and you know, wanted to take one last shot. You know, it's addicting being an entrepreneur, and, uh, founded this company Vico about a year and a half ago. I—

sorry about that, was muted. Why the back and forth between, um, being a founder and working at, uh, government agencies? What are the parallels and the differences between both?

Yeah, you know, it's, it's been kind of like this same area. I guess I'm just sort of like a lot of founders, you become obsessed about certain issues, and I'm sort of like weirdly obsessed with information and decision-making. You know, I've just always looked at the world and I'm like, how do I answer questions? And so my tech, my old tech company was about that. We were kind of doing surveys and collecting information, um, for businesses. My new company, we do forecasts and help decision-makers and Intelligence is kind of the same thing. Investing is kind of the same thing. When you're an investor, you're, you're, you're out there trying to learn what's real. Like, what's real about this company? You know, the CEO tells me one thing, what's real? And then how do I make a great decision? You know, should I invest or not? So I've sort of always been in the same space but in different places. And I guess that's just, you know, a matter of, you know, you're an entrepreneur, you, you like risk, you like adventure. That's how I am. And, um, wanted to try it out in different spaces.

But when you were a kid, you wanted to protect people, right? Or something like that?

Yeah, absolutely. There, there is a, a, an element of patriotism and a feeling, a desire to, you know, protect people that has just been a through line in my life. And, um, you know, I was on the tech track post-9/11, and then when 9/11 happened, I was like That was the immediate thing that led me to intelligence. But, you know, I knew, I knew that intelligence world was the thing I was also interested in and, and wanted to be a part of.

And do you feel the US has done a good job protecting citizens since 9/11? Do you feel Americans are safe nowadays?

I mean, look, it's a hard thing. It's an ever-evolving challenge, right? To how do you keep, you know, hundreds of millions of people safe? How do you do it, you know, as ethically as you can? And Um, and I, I do think overall, you know, look, just if you just sort of measure it as, have there been any large, very large-scale terrorist attacks since 9/11? There haven't been. So at that, at that level, like, we have kind of succeeded. Um, it's not to say that America hasn't made mistakes along the way, but I think this comes down to vigilance by a lot of people who, you know, serve the nation every day, and also technologists more and more. I think that especially these days, a lot of the defense tech companies in America are really contributing to that mission, and that's helping kind of, you know, there used to be this reputation like technology was really old in intelligence and the military in America, and now that's shifting, and now you see cutting-edge stuff.

And you feel that DOD is playing its card right with Anthropic nowadays, aren't they? Um, you know, like having startup founders, uh, being like sort of distrustful towards the government? Should they not intervene? Aren't they like setting a dangerous precedent with what they're doing with Anthropic?

It's interesting. I was part of something called Project Maven years ago, which was a program— it's still around in the Department of War— to bring AI to remote sensing and some other uses. And there was a scandal then too. Google employees decided they didn't want to work on a, on a, on a project like that, kind of rebelled against it. Google, they didn't pull out so much as they just didn't rebid on the contract and they just let it fade. Now Google is back, right? And, and a lot of the other hyperscalers, Amazon and, and Oracle and so forth, are back, and, and the AI companies are back. The, the— so we have seen this before. I think with Anthropic and, and the Mythos model and so forth, it's complicated. And my— I'm looking at it from the outside. When I look at it, I see some aspects of miscommunication. I see some aspects of, um, you know, it— I'm just reading it from the outside. Again, it seems like there are just some people who just don't understand each other and what each other wants. I think that both sides, you know, this is the hard part, it seems that both sides think they're right, that they think that they're doing the moral ethical, justifiable thing. I imagine in the Department of War, they think they're trying to defend the nation. And I imagine in Anthropic, they think that they're trying to ensure that AI isn't used in an unethical way. That's a hard line to walk, and I really hope that they figure it out over time. And I think there's also this aspect of, look, AI is powerful. And we should figure this out. And there are going to be some growing pains as we figure it out. What do you do with a technology that is so powerful, um, that it could change the entire balance of power globally, um, that it could be used for cyber hacking or even creating, um, biological weapons, right? Like, what do you do with that? And so I'm sort of glad that these guys are hashing it out and figuring out where is the ethical line, where's the legal line? And let's look, let's let them argue it out. And we should all be part of that argument.

In fact, yeah, I think it's a clash of cultures as well because the counter— I mean, I'm mostly on Anthropic's side, but the, the facts and scenario was that when the strike on Iran happened, Dario was there arguing about clumsy and philosophical stuff when like the US needed him. To deploy and to protect, you know, even if I ran like, yeah, we might debate like if it was a good strike or not. That was the tension is like, hey, hey, bro, I need your help right now. But the guy is fucking arguing about spy in the sky stuff. And that's why they got undercut. And that's why Sam Altman jumped with OpenAI's support, right? The government needed their guy's support and the guy was in there. And I, I think that that was a misstep. And then after that, like you said, it's communication. It's just about bringing two human beings to talk in front of each other at one table and reaching an agreement. And I think, uh, yeah, Dario is a bit too much on his, uh, I don't know, libertarian horse. And which is fine by me, but it's also like, hey, like, your country in the end, right? Like, you wouldn't be there if America wouldn't be there as your, your base, right? Like, there's this base in America that is, uh, financial freedom and then laws and everything that makes America what it is. So, uh, anyway, tell me what, what you're up to nowadays. Uh, how does your, um, DOD background merge into VICO and what you're, you're doing?

Yeah, look, I, I, um, I sort of was looking at the world a couple of years ago and seeing how complicated it was getting in all these events, different wars, things like the, the Liberation Day tariffs, um, regulations are changing so much. It feels like the world was getting more chaotic, and that was like my world. I was an intelligence officer and an investor, and so I was really focused on these things. And I was like, it feels like AI has gotten to a place where it can help to, to make— how do you make better decisions in that world? And that was sort of the initial, you know, when you're a founder, you have this like initial idea that my co-founder, Lyndon, and I ran with. And what it became and what it evolved into was this capability to forecast what would happen. When you really get down to a decision, you're making a decision about what to do and it's what to do in the future, or it might be right now, but it's going to have future effects. So we built a system that could forecast events in the world better than people. That was the goal, right? And, um, uh, better than, um, even experts could do. Um, and as it turned out, um, and where we are now, better than prediction markets. You know, it was interesting was that, you know, at the time Polymarket and Kalshi and these prediction markets were coming out— PredictIt's another one— um, and showing people that you could successfully predict the world and do it in a numerical way, right? In a quantifiable way. Percentage-based way. And so, um, so we built a system to do that. And then from there, so we publish forecasts, we publish them on Bloomberg, we have a newsletter, you can come into our site and, and see these forecasts. But you also can make your own forecast for anything. And that's, that's a big difference with a prediction market. We don't need to set up a betting market or anything like that. You can come in, you can use our system and predict anything you want anywhere in the world. Okay. Within, you know, right now we're optimized for politics, economics, geopolitics. We're not doing sports and entertainment and some things. We'll expand the envelope later. But, you know, within, within those areas, you can predict anything. And now we're building into helping people make better decisions. Um, and that means, look, think about when you make a decision, it's, yeah, what might happen in the future, but it's also scenarios. What if this happens? What if that happens? Then what do I do? Right? And so we're building tools on top of it that you can use on our site or build into your tools via API to help you make these better decisions. We right now service people in finance and in national security. These are the worlds of, you know, this is where decision advantage really matters, right? Even being 2% better at a decision matters a lot could be a lot of money at stake, or it could be, you know, even people's lives. So that's where we work now. But over time, we want to help anybody make a better decision. And I think that removes a lot of risk in the world, and for businesses and people. And, um, it's just something— that's kind of what we want to contribute.

And is it a Palantir model, um, deployment model, in which you have like a software, the company hire you, hires you, and then you deploy a couple of engineers in there, or to customize the main piece of software?

No, no, it's like the opposite. My co-founder came out of Meta and Google, so we have this like kind of consumer app mindset, and it's literally like off the shelf, come on the site, just use the app and make your own forecast. Now we have kind of a more enterprise version if you want an API, if you want to incorporate your own data, you can do that. We can work with you to do that, but it's off the site, you know, it's off the shelf. It's like using a consumer app. That was like a design mentality we had, um, that, that I think also makes it more fun to use and more interesting and more responsive.

I love it. Um, yeah, you talk about Kaushee and all of that, Polymarket— these have taken off like crazy. Um, but you're not consumer at the end, you're very much B2B, right? So what do they pay normally to get you to deploy in their own companies? And what's the benefit of using you versus their own internal algorithms?

Yeah, look, we, we actually can work with anybody, including consumer, right now. So actually, if you're listening on the site and want to sign up, you can sign up right now, and I'll give you a beta account. And, you know, if you just mention you listen to this. And, um, and then we, we try to make it so that there is a, a, a lower cost version. Like, we Our lowest cost version we offer right now off the shelf is $100 a month, which we think is pretty reasonable for very powerful AI tech. And for people who kind of take seriously what's happening and seriously a decision, even if you're a small business or like an individual journalist or someone like this or researcher. And then we kind of scale up from there. It's a token model. And businesses are more in the, we're within the kind of think about it as $100,000 a year kind of range because they're doing more with it, right? They're using it more, they're integrating it in with some of their financial models and things like that. But we want to have that scale so we can help you even if you're an individual or if you're a big organization.

And the price of it, I'm trying it right now. I like it. I like the UX. What should I pay for eventually? Like when's going to be the paywall?

Yep. So when you use it as a beta, we give you— I think right now it's set at 7 forecasts you can make. Um, so that— and that's free and, you know, let you try it out. And you can access, by the way, when you're on at whatever level, all of the other forecasts that we post and our newsletter and things like this. And then from there, at the, at the $100 a month level, um, uh, I'll, I'll you know, you can check when you get on there to, to, to check on me on this, but I believe we have it set at, um, it's essentially a dollar a forecast, um, which, you know, we think is like a nice entry-level, uh, way to get into this world. And what, what's interesting is when you start to think about, like, you know, some people talk about, you know, AI as like, uh, metered intelligence, right, with tokens. What happens when you have metered forecasting, and you start to think really differently about the future, right? Like, you start to think like, well, before, if I wanted to get a forecast, I would have to go to like a professional consultant or advisor or, or something like this, and I would pay them by the hour, you know, maybe hundreds of dollars an hour, um, or even more, and they would write a report. And now it's like Wait, no, I could just pay like a dollar and I get something, you know, a little bit similar and overlapping. So then you start to use it more. And like, I'm at this point where I'm like, when I see something in the news now, I'm like, wait, is this really going to happen? Right? Like some politician and they come out and they say, hey, I'm going to do this, right? And I'm like, okay, what's really the probability of that happening? Very low.

If it's in the news and if it comes from a politician, probably single.

Exactly. And it helps you see through the noise, right? You see how much of it is noise, but it also helps you see sometimes it's real. So we actually forecasted the strikes on Iran, and we were— and if you looked at that time, you can see it when you come to our site or look up our newsletter on Substack, you'll, you'll see we were forecasting, um, 60, 70, um, close to 80% in the lead-up to the strikes. And Paul, Paul Sheen, Polly Market were like kind of— it's called, you know, fence sitting. They're around 50%. Like, nobody thought this was going to happen, and we're like, no, it's happening. Like, look, you know, before, um, we were at—

we—

the right before the strikes, we're in like 78%, um, a day or two out. And then 10 days out, we were at 60-plus percent, um, between 60 and 70%. So we were, we were calling it there. 3 weeks out, we were above 50%.

It's pretty amazing how quick things escalate with this guy. Um, it's, it's very intriguing. I'm just curious, as for the, the business model, right? $1,000 a month. Who needs to make 1,200 predictions a month? And then if the answer is like traders, wouldn't they have like an API integration in their Bloomberg terminal? Like, wouldn't they have already an AI in which they can just throw their predictions at. And I'm throwing a bunch of questions at you, but how would they organize their full spreadsheets of prediction?

Yeah, great, great, great question. We do— we offer our forecasts on Bloomberg, but it's a set number of forecasts. We have around 160 up there. We also have some indexes that we've launched on Bloomberg, but that's just— think of that as beta. Those are the forecasts we're publishing. When you come onto the site, you get alpha, right? You get— you make your own forecasts that nobody else has. And that's really where you get to see something special because it's what you're focused on. And then it's— remember, it's not just a forecast at a moment in time. You know, some— you can do forecasts hourly or daily. That's where you start to see trends, and that's really what moves the needle. Say if you're a trader, it's not just, hey, today is a 62% chance. It's that today's 62%, yesterday 55, the day before 50, the day before that 45. Now you're looking at a trend that allows you to now make a much better decision. Or what we do is allow you to make these what-if scenarios, right, where you say, okay, the probability of the Strait of Hormuz reopening right now in our model is like very low, um, at least at the time of recording this. Um, but you can play through what-if scenarios. What if this happens? What if that happens? What if Israel strikes Iran again? Or what if, um, there's a breakthrough diplomatic event in Pakistan, whatever it is, and see that. And so from our perspective as, as a model, again, it's not about this one forecast, it's about you running many forecasts, running them over time, running different scenarios, interacting with the future in a completely different way than we're used to. The closest example, just real quick, that I would say is when people did spreadsheets before Excel It was literally a sheet of paper that was spread out. You'd go to your accountant and they would fill it out by hand, and it would take all day, and it was very expensive because you're hiring people. And then what happened is with Excel, all of a sudden you could do your own spreadsheet and you could do it whenever you want. And so now you could do a financial model whenever you want, and you started to do more financial models and experiment more. We're sort of similar now. It— now the cost of entry, as it were, to looking at the future is so low, you can experiment with the future, run it constantly, think about running your business or your life in a completely different way.

Your sources, how similar or different is it from, let's say, a NotebookLM that I sent for research, or a ChatGPT Deep Research, or Claude Deep Research? Is it like the same exact API of research, or is it different?

We're pulling— ultimately, we're pulling from open source information. We pull from about 150,000 different sources. And we do that on purpose because a lot of our users are in finance and they need, you know, it has to be public information. But you can bring in your own proprietary information. If you have your own analysis, you have your own data set, you can bring that in. It becomes your siloed proprietary data set, and then that updates the forecast just for you. We don't even see it, right? We— you— that's just your forecast now. So we can go either way. Now, we have found actually that even just with this, um, non-proprietary open-source information, we're still forecasting better even than people who often have insider information. That's what's sort of really interesting about it, because these kinds of issues like a war in Iran aren't just about one single stream. They're about what's going on in the world, balancing it rightly. Ultimately, the analytics and having a great model that does that. That's what we focus on.

Isn't, isn't your alpha going through private sources? Like, wouldn't you have a model one day to have access to people with alphas, and that would be part of your API so that you could return even better predictions?

In theory, we could. This is where the proprietary data can come in, right? Is Maybe we're looking at, um, uh, DC politics, whether this regulation or this law is going to get passed, right? Yes, absolutely, we could bring in some alpha information. Maybe you're a lobbyist and you have some reporting, but even then you still need all the other information, right? Because we're measuring also— it's not just about whether some senator says he wants to vote for something, it's what's happening in the nation, where are polls, like all of those things that surround whether something happens. We're getting all that. So the 90% of that information, and then we can add that special secret, you know, 10% for you, you know, obviously as long as it's legal and you have rights to that proprietary information.

What's your predictions on the Iran-Ukraine or big geopolitical events out there as a guy that has its boot on— its boots on the ground?

Yeah, our model has been incredibly bearish on, um, Iran and, and the full normalization of the Strait. And, and, and what's interesting about our system, it's not just giving you a percentage probability, it's giving you the reasoning. You can see why it believes that this is the case. And, and essentially the model at this point believes that the U.S. and Iran are too far apart in the negotiation. And that— and so we have again and again, you can look back at our newsletters called the resumption of strikes, the straight closing again. And that's still looking out 30, 60 days, it's still pretty bearish. Um, same on— it's less bearish on peace in Ukraine, but it, it's still far below 50, um, over the course of the next year, unfortunately.

What about like, uh, takeoff of superintelligence, uh, 2027? Uh, in which we have a superintelligence that just takes off and, uh, goes by its own and does its own thing. Have you taught or predicted stuff about that?

We're doing, um, we're, we're actually doing— so this is a little, uh, the tech predictions are— is when I'm describing where is the envelope for our model and what it's optimized for. It's not optimized today publicly for that, but that is sort of the next area we're expanding into. We're starting to run experiments to see, you know, look, the model may make a prediction of something, but also I want to make sure it's back-tested and we can have confidence that it works, and forward-tested, right? So I know, I have, I know where we sit in terms of confidence for politics, economics, geopolitics. For tech, I, I don't quite know yet. That's the experiments and the work we're doing, and you'll see that later this summer where we, where we expand that envelope into those areas.

And Iran, you're saying like boots on the ground, like this will end up like Iraq and Afghanistan, or what?

No, actually, where the model is— we just did something in our newsletter last week on this— where the model is, is that the most likely scenario is kind of a no peace, no war, um, kind of scenario, more like what happened, you know, the war in North Korea is actually still technically a war. We just never did a peace deal. Um, and so we may— I think where the model is, is we may land in this kind of just low-scale, like, we just learn to live with it, and occasionally there are strikes here and there, but we both, you know, we all sort of just like move on.

Yeah, just more surveillance, I would say, right? Like just more supervision and more, uh, spying stuff, I guess, activity, just to monitor that they're not doing anything dumb, right?

Yeah, yeah. And, and pushback here and there, right, where you're, you're sort of seeing it settle into this again. I think the model saw this coming where, um, you know, we're trying to do a peace deal and then Israel strikes, um, uh, Hezbollah, so Iran, you know, closes the Strait of Hormuz. And then Israel stops striking Hezbollah, Iran talks about reopening it, and you're sort of seeing this, you know, settling into, um, this almost like dynamic equilibrium.

Humans are so weird, man. Uh, I was, I was like, um, yeah, super intelligence in the future, like, it will fundamentally operate different from humans because they'll know all the cards, right, from the opponent. So at this stage, it won't even be cooperation, it would just be like merging and copy-pasting and proving instead of trying to spy and destroy and hide, which is like so, so weird. That's, that's us humans. Um, talking about your next book, uh, or your actual book, right, that was released, tell me a bit more about it. Uh, The Fourth Intelligence Revolution was launched in 2025. How's the book doing and what was the thesis behind it?

Yeah, the thesis was this. Look, I was, you know, like I said, in my career I was bringing AI into this intelligence agency And this is, you know, years before LLMs, and I realized how important this was going to be. And also, um, what could go wrong, you know, ethically or, or legally and so forth. And so I wanted to kind of educate the public a bit on intelligence. It can seem so mysterious and classified and so forth. And so I wrote the book to kind of explain, this is where we are in intelligence and where it's going. And how it's going to affect you as a person. And there are essentially, I say, 3 ways. One is intelligence is expanding, and all of a sudden there's like economic intelligence and science and technology intelligence, and that affects even people at like tech companies now. Two is that AI is going to be used everywhere in intelligence. And, you know, we've seen these warning signs before, like how intelligence started collecting from cell phones and things like this, right? Well, AI is gonna be used, and we need to think about the ethical and legal boundaries of that, but also the opportunities to kind of make people safer by using AI. And then 3, and this is kind of the scariest thing to me, is that intelligence is now affecting everyone. And you see China and Russia and countries like this collecting intelligence on everybody. That's why when you see these hacks of insurance companies and banks and so forth, That's not to get at a senator or president. That's to get at sort of everybody and then potentially use it for things like information operations, like we saw with Russia in 2016, or we saw with TikTok, frankly. And, and then finally, what I recommend in that world is we don't necessarily want the government and like the CIA or something to try to protect that. We don't want them censoring, uh, disinformation and things. Actually, I think what we should do is sort of make the population, make all of us more resilient by starting to learn the lessons from and think like intelligence officers to protect yourselves and your family and, and, and your community.

Is there really a race between US and China right now? Like, as a guy that spent some time in China and that have been observing them, yeah, there's all kinds of arguments out there, like that they produce 230 ships for one ship in the US or something like that, and that their economy is, is growing faster, but it seems that America is unbeatable because it has a brain drain on the world and all the smartest people are there, we're greatly ahead of, uh, the AI, uh, and AGI race, and China is only good, in my opinion, from what I have observed, and I have hordes of data, right, at copy-pasting and improving. They're not good at coming up with new stuff, which is the, the name of the game. Are they really a threat, or is just that like a reason, like the arm race stuff, to just like try to beat them and innovate and move faster?

It's definitely a competition. I mean, both sides see it this way. It hasn't degenerated, thankfully, into a full and open war, or even like a truly a cold war, because we're so interdependent on each other economically. Um, but there, there, these are very serious areas of competition. Right, that— because, you know, remember, there, there is a difference in government, and the Chinese Communist Party, it is a dangerous government in my view for, for, for people in the West. They, um, feel very paranoid about controlling their society in a way that I think most of us in the West would be very, very uncomfortable with and just simply not want. And we want to minimize their expansion and into, into our world in that way. That doesn't mean we can't coexist. I do think we can coexist, but We, we do have to compete and, and hold them back. Now, it's not a symmetrical competition though, right? And we are competing in very different ways. You're absolutely right. I don't think that China can compete at the frontier of AI, for example. They're not where Anthropic or some of the other companies are, but they're just competing in a different way, right? Right now, I think they're competing on open source models. You know, you look at Deepseek or KIMI or some of the open source models which are effectively giving away for free, which then leads even Western companies to use those models as the low-cost models. They gain market share, they eventually may charge for it or have like a Red Hat style kind of services business. Who knows how they'll make money from it, but gain that market share. It looks kind of similar to what Huawei did, for example, where, or DJI, the drone company, or some of the electric vehicle or solar panel companies in China did, which is offer a lower, lower cost or even free version of something, gain market share, then make the other economy require your good. Now make them dependent on you, then make money from there. So that's where the competition is, is happening.

It's intriguing, right? Like, what makes you think that the government, the Chinese government, is scared? Because me, from my perspective, is like the big brother thing, right? Like, I remember being— by the way, I love China. Like, I've been there. It's a beautiful country, beautiful people. It's great. Um, but when I was in mainland China, I was living in Hong Kong for a while. Hong Kong is like not fully Chinese, right? But, uh, there was, um, yeah, the treaty that ended around, I believe, 2015 or something like that. But when I went through mainland China, I couldn't visit some website that was weird. And then I had to use like firewalls, and then I felt that somebody was watching, which is not really the case. Maybe there are— in the end, maybe I can be watched and monitored. Also, not being able to say things, it sucks real bad, especially for a libertarian like me. But that's not dangerous, right? Like, they cannot like come and kill me. So what I'm curious to double-click on, on your your, your view of their danger.

Yeah, yeah. And I would, I would predicate it in the same way, which is like, China as a culture, China as a people are great and would love to like—

pretty much everything, like everywhere you look at. Yeah.

So, so absolutely not about that. I'm really— when I say China, I'm really talking about the Chinese Communist Party, their, their national security, um, community within it, right? Like, that, that's what I'm worried about. And Um, look, I, I think that they, they have absolutely created what I would call like a panopticon of surveillance within their, within their own country that you're sort of describing. And I believe that they are trying to export that globally. Um, but it's not just about censoring, it's also about they want to change information. They want you to believe certain things. It's not just, hey, Tiananmen Square never happened. It's trying to, to make people literally forget that it happened over generations. That is dangerous, and, and in many ways as dangerous as physical threats. Um, it's also— look, there are real documented human rights abuses going on, gulags, and like the, like the Uyghurs, where millions of people have been kind of interned in literal concentration camps. And like I'm just not going to stand for that, right? Like, and, and I think we have learned in the West that, like, we can just— you, you cannot let that keep happening. Um, and so it's those two things. It's this sort of thought control and surveillance state and, and, and disregard for the, the rights for, for humanity in general that I, I just can't live with.

I think Russia is obvious, right? China is a bit less obvious, right? Because changing history books, like all governments from all over the world have been guilty of that, right? Like First Nations, what we did to these folks in Canada and US and Australia, um, we, we all change history books. Like, it's written by the victor, right? It's written by the person that had dominance over the, the next ones. I think we're all guilty of that. Uh, camps, one could say that ICE in the US, right, is I mean, it's not the same, obviously. It's not like imprisonments, people that came there illegally, but the ICE stuff in the US is pretty fucking dire. Um, and then there's obviously like the current administration, right? Like, we're seeing stuff that is like pretty outrageous nowadays. So what one could argue against that— I think that the obvious case is Russia though. Like, to me, like, Russia, like overstepping on territories that is not theirs and murdering people. That is super obvious to me, like, that Putin is a fucking psychopath that needs to be stopped. The Chinese people, you know, they're a bit nicer. Yes, there's some sneaky stuff going, Big Brother stuff, but just like my perspective as a guy that spent time in there, I think generally speaking— I don't speak too much Russians nowadays— Russian founders, Russian, Chinese, folks, right? Like, it's— I wish I would speak to more of them, but it seems that it's like also in their culture to, to not speak to outsiders a lot, which I think is bad. So obviously still very pro-US on my side, pro-Western. I wish, uh, current administration wouldn't turn back on their allies. I think that's one thing that has— one of the so many things that's been mis-administrated nowadays. But yeah, hey, what's next for you? Let's wrap this up. Like, what are your top priorities this year?

Yeah, this is an exciting year for us because we launched in January. The last several months have been about getting it out there, getting the tech in a really good place. We're launching new models over the summer that are like really exciting. Like where we're moving from a world where we're just trying to predict to one where we're trying to explain and allow people to engage. It's like this hybrid model. How do I bring people into this? So that just like intellectually is really interesting and like as a product and that's coming out this year. And then we're going, you know, like a startup, you know, we're 6 months in, we're going hard on sales and really trying to grow and offer it to more people. And so that's the rest of the year for us. We're growing our team, we're hiring engineers and ops folks and sales folks on the team. And it's a big year and anybody who's been in this part of the phase, right, where you're like late seed going into your Series A and you're just hustling every day to kind of run as fast as you can and get it out there. And that's my life right now. You're on mute again.