How Bots, Deepfakes and AI Agents Are Forcing a New Internet Identity Layer | Alex Blania on a16z

a16z's Ben Horowitz and Erik Torenberg speak with Alex Blania, cofounder and CEO of Tools for Humanity, World, and cofounder of Merge Labs. World is building the largest real human network, a proof-of-human layer for the AI era. They cover the technical challenge of proving human uniqueness at scale using iris biometrics, the privacy architecture behind World ID, and why platforms from social networks to dating apps to video conferencing will soon require proof of human verification. Timestamps: 0:00—Introduction 4:07—Three Big Ideas People Were Interested In 9:05—The Orb Verification Piece 15:21—Social Media Bots: PSYOPs and Propaganda 29:21—We Had Proof of Personhood for the Longest Time 36:44—Next Year Go-to-Market Is Focused on the US 40:09—Different Levels of Verification Read the full transcript here: https://www.a16z.news/s/podcast Resources: Follow Alex Blania on X: https://twitter.com/alexblania Follow Ben Horowitz on X: https://twitter.com/bhorowitz Follow Erik Torenberg on X: https://twitter.com/eriktorenberg Stay Updated: If you enjoyed this episode, be sure to like, subscribe, and share with your friends! Find a16z on X: https://twitter.com/a16z Find a16z on LinkedIn: https://www.linkedin.com/company/a16z Listen to the a16z Show on Spotify: https://open.spotify.com/show/5bC65RDvs3oxnLyqqvkUYX Listen to the a16z Show on Apple Podcasts: https://podcasts.apple.com/us/podcast/a16z-podcast/id842818711 Follow our host: https://x.com/eriktorenberg Please note that the content here is for informational purposes only; should NOT be taken as legal, business, tax, or investment advice or be used to evaluate any investment or security; and is not directed at any investors or potential investors in any a16z fund. a16z and its affiliates may maintain investments in the companies discussed. For more details please see http://a16z.com/disclosures.

Speaker names marked ? are inferred from speaking time and the show’s known hosts — they are not voice-verified.

• 0:01Ben Horowitz?

  How do you prove somebody is human?

• 0:03Speaker 01

  It is a surprisingly hard problem.

• 0:05Ben Horowitz?

  I think that people are gonna start getting accused of being bots.

• 0:09Speaker 01

  What we currently see is less than 1% of what it will look like in probably a year or two. The idea that AGI will lead to some very fundamental shift seems obvious.

• 0:19Ben Horowitz?

  AI is really good at programming humans, much better than humans are at programming AIs.

• 0:23Speaker 01

  Absolutely. An AI will be able to have a GitHub account and will be able to post and also attest to five other AIs that these are in fact humans, even though they're not. Honestly, if you don't take it serious now, then I think you should get a different job or something.

• 0:36Ben Horowitz?

  And those agents are very, very clever.

• 0:39Erik Torenberg?

  How do you prove you're real? In 1950, Alan Turing proposed a test. If a machine could fool a human into thinking it was also human, it had achieved intelligence. For decades, that remained theoretical. Today, AI agents run thousands of social media accounts at once, outperform humans in controlled persuasion tests, and generate hundreds of videos a day that audiences believe are real. The Turing test didn't just get passed, it got commoditized. Every platform built on the assumption that its users are human now faces a problem no one has solved. Facial recognition fails at scale. Government IDs weren't designed for a global internet.

• 1:22Erik Torenberg?

  I speak with Alex Bonya, co-founder and CEO at World, which is building the largest real human network, a proof-of-human layer for the AI era, alongside A16Z co-founder and general partner Ben Horowitz.

• 1:38Erik Torenberg?

  Alex, welcome to the podcast. Great to have you.

• 1:41Speaker 01

  Thanks for having me.

• 1:42Erik Torenberg?

  So, proof-of-human is having a moment right now. Why don't you first give a background for people who are unfamiliar? What is the moment that's happening and how did we get here?

• 1:50Ben Horowitz?

  Yeah, and what is proof-of-human?

• 1:52Speaker 01

  Proof-of-human, as the name suggests, is do you know if you interact with a human or like something else on the internet? And I actually think the kinds of questions that we're now asking is, are you interacting with a human? An agent on behalf of a human? Or just an agent? I think these are like roughly the three areas that you wanna split apart.

• 2:12Ben Horowitz?

  And describe a little bit the difference between just an agent and an agent acting on behalf of a human. How do you see that distinction?

• 2:19Speaker 01

  Yeah, so quickly explaining just the term proof-of-human and I think what is hard about it, and then I'll explain how it fits into an agent on behalf of a human. What proof of human really means is that every individual that interacts on a platform has only one, ideally one account or a limited number of accounts, and stays the owner of that account. Like, that's kind of the property that you're looking for. So like, you're looking for an initial verification, that ideally should be something like anonymous or very extremely privacy preserving, and then ongoing authentication, that the same person remains in control of that account. And then there's like some secondary properties that I think are good to have. But that actually tells you that the really hard thing is uniqueness.

• 3:01Speaker 01

  Like, what is happening on a platform like Twitter right now is that there's all these accounts, all these bots that are in replies, that there's probably one human sitting somewhere and sending out 10,000 or 100,000 of AIs. And there's this catch-up game where Twitter and X are trying to just find them and block probably millions a day of these.

• 3:22Ben Horowitz?

  Which is what, a one-hundredth of the bots?

• 3:25Speaker 01

  That's right. That's how it feels like. And then agent on behalf of human, I think how it will look like is, I think all of us will have agents. It's unclear how it will look. Is it's gonna be one or there are multiple ones, maybe with different tasks and different even types of characters. And I think it will then come down to, I approve a certain action of my agent. I give him certain rights. So act on my behalf.

• 3:47Ben Horowitz?

  Okay. Post to my X account, post to my Instagram.

• 3:51Speaker 01

  For example.

• 3:51Ben Horowitz?

  But it's my Instagram and I'm a unique human that onset.

• 3:56Speaker 01

  That's right. You know, then X or Instagram could decide that if that's actually something they want as a platform.

• 4:00Ben Horowitz?

  Right.

• 4:00Speaker 01

  But that's how you could do it.

• 4:03Ben Horowitz?

  That makes sense. And so, how do you prove somebody is human?

• 4:08Speaker 01

  It is a surprisingly hard problem.

• 4:10Ben Horowitz?

  Yeah.

• 4:10Speaker 01

  So it's-

• 4:11Ben Horowitz?

  Those agents are very, very clever.

• 4:14Speaker 01

  It's funny, we started this company now a couple of years ago, before ChatGPT and before all of that. But we kind of took that as an assumption that eventually we will have AIs that pass the Turing test, so they can just claim to be a human. You will not be able to tell that anymore on the internet. And also that they would be highly agentic and just run around with their own thing. And so that makes it really, really hard because- Back then, when we started the company, there were like roughly three big ideas that people were interested in. One was this idea of web of trust or like related ideas. So this idea that you look how someone behaves on the internet or did behave in the past. So like usually a combination of you have these certain number of accounts that you own

• 4:59Speaker 01

  since a couple of years and then you post regularly or you comment regularly to GitHub. These were the kinds of things that people are using. And then, let's say, all three of us have them. And then I attest also that I know you in the real world and I attest to you that I know you in the real world and that's how you would build a certain graph. And that was like a very hot idea back then for this, but we disregarded it basically immediately because we assumed that eventually everything that is just digital and AI will be able to do as well.

• 5:27Ben Horowitz?

  Yep. We're there.

• 5:30Speaker 01

  Yeah, exactly. So an AI will be able to have a GitHub account and will be able to post and own an account and like also attest to five other AIs that these are in fact humans and even though they're not. So that was area number one. Area number two was to just use government IDs for everything, which we just all seemingly disregarded for a couple of reasons. One is that I think, you know, it's strictly better if the government would not control such an infrastructure in terms of free speech and actually breaking that apart, but then also.

• 5:59Ben Horowitz?

  Right, you lose anonymity instantly, right?

• 6:03Speaker 01

  You could hypothetically set up a system that maybe preserves it, but it's very hard to do. And then the second thing is also the government identity system is just not built for that. And what is so hard about this problem is it's going to be a global problem. And so it doesn't really matter if one government maybe has the perfect infrastructure. For example, Singapore is like an example of a government that has perfect infrastructure all around, but that barely doesn't matter because, for example, I don't know, Meta is a global product with three billion users and a lot of other countries.

• 6:32Ben Horowitz?

  Yeah, Singapore is two million people or a million people.

• 6:35Speaker 01

  Yeah, exactly. So do you want to lock everyone else out? So and then there's a long list of other things why we disregarded that basically immediately. And then the last one is biometrics, which actually immediately gives us this egg reaction. It's like, and it even went further because what is so hard about this problem, as I mentioned in the beginning, is uniqueness. And so just like in very simple words, how you can describe the problem is. Well, first of all, for example, what does Face ID do? Face ID checks that I'm the same person again using my phone. And so it's a one-to-one authentication. So there's an embedding start on my phone. It takes a picture of my face, creates a new picture, compares it to the previous one. And if that is close enough, I can use my phone.

• 7:19Speaker 01

  So that's a one-to-one, one embedding to one new embedding. To solve the proof of human problem, you will need to distinguish one new individual from all previous individuals. You need to make sure that Ben is trying to sign up and Ben did not sign up before.

• 7:33Ben Horowitz?

  Yeah.

• 7:34Speaker 01

  And then suddenly it goes from one-to-one to one-to-N. N is the size of your network, essentially, that you're trying to prove that to.

• 7:41Ben Horowitz?

  Right.

• 7:42Speaker 01

  And then you can just do the math and you can calculate how much mathematical entropy, like how much information, just information theoretically, do you need to prove that? And it turns out that's a pretty high number because it's an exponential problem.

• 7:54Ben Horowitz?

  Right.

• 7:55Speaker 01

  And so then you can just do the math and you find out that things like a face or even fingerprints or something doesn't work. Like then you would basically hit a wall after tens of millions of users. And so then you end up with something like iris, which is the muscle of your eye. That actually has enough entropy.

• 8:11Ben Horowitz?

  That it's unique.

• 8:12Speaker 01

  That is unique. That is unique enough.

• 8:14Ben Horowitz?

  And how do you also then solve the one thing that biometrics have been subject to historically is just replay attacks? Where, okay, I may not have your eyeball, but I've got enough information that I can run a replay attack on you.

• 8:30Speaker 01

  So again, it is important, I think, to split up the problem and verification, which is essentially in old terms, it's like you getting your passport.

• 8:39Ben Horowitz?

  Right.

• 8:39Speaker 01

  And then authentication, which is you showing your passport constantly for certain kinds of things. And on the, you know, on the verification piece, we've went down, if you know world, you know that we've built this thing called an orb.

• 8:53Speaker 01

  It's doing a lot of things to prevent these kinds of attacks. So it's, for example, it has multiple sensors in the electromagnetic spectrum to just make sure that you cannot show a display to it and it would recognize that. So I think on that side, we've, we've got it handled. On the consumer side, you know, to then re-authenticate, it turns out to be much harder because... You would need to trust the phone in some sense. Because what we actually do in that moment is when you verify with an orb, not only do we check your uniqueness in a fully anonymous and privacy preserving way, and we should talk about that, but also we send to your phone a signed face image that you then can later use to re-authenticate against it.

• 9:32Ben Horowitz?

  Right.

• 9:33Speaker 01

  And with a new iPhone, you can have meaningful amount of trust against that, but with old Android phones, basically. And so.

• 9:39Ben Horowitz?

  Oh, yeah, yeah, yeah.

• 9:40Speaker 01

  Because like you can just, you can just show a deep pic essentially either through a display or just directly injected in the camera stream. So that's a problem. And so it's going to be a mix of, you know, if you have a new enough, let's say iPhone or a general phone, then you can just re-authenticate against that picture that you took on verification. Otherwise, you would probably have to even go back to an orb somewhat frequently, let's say a couple of times a year if you just.

• 10:03Ben Horowitz?

  I see.

• 10:04Speaker 01

  You don't have.

• 10:04Ben Horowitz?

  Right to re-authenticate.

• 10:05Speaker 01

  Yeah, that's right.

• 10:06Ben Horowitz?

  Interesting. And then one of the kind of incorrect criticisms of the approach early was, oh, my God, they've got my eyeball. You know, now they're, you know, they somehow have access to my privacy and they're gonna, you know, do all these things to me and, and that's my access. And then they can, they, WorldCoin can impersonate me and all these kinds of things, but that's not the case. And so that was also like a non-trivial engineering problem.

• 10:39Speaker 01

  That was, that was very much non-trivial. So actually, I think one point on Iris that I think people don't appreciate enough, and that's a bet we took back then, but it was essentially that Iris will turn out to be super normal as a, as a modality, just because I think we will all wear AR and VR systems to do that. You know, Apple already does it.

• 11:00Ben Horowitz?

  Yep.

• 11:01Speaker 01

  Already has Iris ID in the Vision Pro. So I think it's, so maybe that's a general point. I think it's going, it's going to be, become something that we will use across many different devices and will normalize in that sense. But I think on the, on the privacy piece, that took us a lot of time because like when, when we, when we decided back then that, you know, with our assumptions. You know, which was six years ago, that we will need a custom hardware device for biometrics. It was actually quite scary, um, you know, to, to come to that conclusion because like

• 11:33Ben Horowitz?

  Yeah, that's an expensive conclusion.

• 11:34Speaker 01

  It's like, it's like very expensive. And then just having this idea that you would need to distribute them all over the world. Like that, that just assumes that you would be able to like somehow bring up billions of dollars and to like a massive effort to, to distribute it all to the world. But then also the privacy challenge of like, how could you build such a system that has all the, all the requirements that we care about? And the, the two main high level, you know, ideas on how to solve it were uh, multi-party computation and zero knowledge proofs. And so, um, to, again, what is different to Face ID? Because Face ID actually is, it, you know, can be very private just because the embedding is stored on the phone.

• 12:16Speaker 01

  It doesn't have to leave the phone ever, just because it's just you against you in the past. But to check uniqueness, uh, you need to check against all previous people. So, so, so something needs to leave.

• 12:30Ben Horowitz?

  Yeah.

• 12:31Speaker 01

  You know, something needs to leave something and be compared to someone else. Uh, and that's, uh, and that's a much harder, uh, challenge. And, um, how we approach that is with a multi-party computation. And so that essentially means that, so in our case, when you, uh, verify with an ORB, you know, we, we take all these pictures. They get computed on the device and, uh, then they actually get split up in multiple pieces. So, for example, we take a picture of the iris, we calculate an iris code. Then we break that iris code in multiple pieces and sell, send it to multiple computers such that, um, there is no central database in some sort. So no one actually has the information about you.

• 13:15Ben Horowitz?

  Correct.

• 13:15Speaker 01

  And then you do some clever tricks of how these different parties need to come together to do a computation that still leaves the pieces apart.

• 13:25Ben Horowitz?

  Right, right, right.

• 13:25Speaker 01

  In such a way.

• 13:26Ben Horowitz?

  Where nobody has the whole thing.

• 13:27Speaker 01

  Yeah. So no one has the whole thing. And also during the computation, no one has the whole thing.

• 13:31Ben Horowitz?

  Yeah.

• 13:32Speaker 01

  But they do some, you know, some clever interactions to come to the conclusion.

• 13:36Ben Horowitz?

  A little like a zero knowledge proof kind of technique.

• 13:39Speaker 01

  Uh, it's, I mean, it, it's very different, but I think in terms of the properties it achieves, it's somewhat similar. Where like you. No one knows anything about you, but you can actually together make a statement about you.

• 13:51Ben Horowitz?

  Right.

• 13:52Speaker 01

  And so, you know, you send it to this multi-party computation and what comes back is yes, that individual is unique. And then the second thing we do is we we separate all of this from you with a zero knowledge proof. So meaning you have that secret on your phone, but no one else has it, no server has it, we don't have it. And then you can later go back to this multi-party computation and say like, hey, I have a secret that is part of that computation and I am in fact unique. And you can prove that to a platform. You could go to the social network and prove that you're a unique user to the social platform without us knowing anything about you or the social network knowing anything about you.

• 14:34Speaker 01

  And so it's this like very counterintuitive property that you there is like, even though it uses biometrics, you, you know, you preserve anonymity and and extreme levels of privacy, which I think is super cool.

• 14:47Ben Horowitz?

  You know, social media is one kind of vector of, you know, things that were annoying and are now becoming overwhelming in terms of just bots, you know, particularly with psyops, propaganda, all these kinds of things. What are some of the other, you know, uses of bots that are going to be kind of impossible to live with if we don't get the proof of human in the future?

• 15:14Speaker 01

  Yeah, actually, I think the the simple model I have read is every moment on the internet that is primarily about humans interacting with each other, you know, or or even indirectly interacting with each other. So, you know, you can, you can start with simple ones like dating, you know? That really matters.

• 15:34Speaker 01

  That what does the other side is in fact a person.

• 15:37Ben Horowitz?

  Yeah, well, the

• 15:38Speaker 01

  Got bad news for listeners.

• 15:41Ben Horowitz?

  And the person who you expect it to be.

• 15:43Speaker 01

  Yeah. We had this problem even before. Yeah, exactly. Yeah, so that's an obvious one. And so, for example, Tinder is already using it for that reason. I think.

• 15:55Ben Horowitz?

  And what's the Tinder use case?

• 15:59Speaker 01

  So we started in Japan. And like as a test market. And it's essentially exactly what we just discussed. It is if you verify it with an orb, you get a little badge that, you know, signals to other people that you are in fact a human. So it has a high level of verification. And then also, I don't think that's live yet, but what will come next is that you're actually the person you claim to be. So meaning you have a world ID that is associated to the kind of profile pictures that you use. So you just run a quick check that this is all correct.

• 16:36Speaker 01

  And so, you know, you then know you're not interacting with bot. But also, you know, you interact with a fully authentic profile. Another fun one, because I think it's somewhat condescending, but I think it will be video conferencing. Because, you know, you already have deep fakes.

• 16:52Ben Horowitz?

  I don't feel like going to this video conference. Just put my deep fake up.

• 16:56Speaker 01

  Yeah, and actually, you raised it to me first. And that's why we started building a product for it. Because, you know, it would actually start with very high value users. Like, for example, people, you know, like yourself, that maybe manage a fund. And, you know, sometimes calls actually could be very high value if it's about borrowing money or.

• 17:14Ben Horowitz?

  Oh, yeah, yeah. Well, so somebody can be me and say, Eric, can you please wire this Nigerian prince $400 million?

• 17:24Speaker 01

  Right, exactly.

• 17:26Ben Horowitz?

  It would be good to know.

• 17:28Speaker 01

  Yeah, like, you know, that's still slightly hypothetical, because these things are not fully real time and you can somewhat.

• 17:35Ben Horowitz?

  They're very close.

• 17:36Speaker 01

  But they're very close. And so I think, you know, in a year from now, it's just going to be a full commodity. And it's going to be super photorealistic and absolutely real time. And you will just not know anything anymore on these video calls. And so I think that's another one. I think another one then will be, which I think is fun, but it's going to be gaming. Uh, you know, because

• 17:57Ben Horowitz?

  Oh, yeah, yeah.

• 17:57Speaker 01

  Because gamers really care.

• 17:59Ben Horowitz?

  Oh, yeah, they're playing an AI.

• 18:03Ben Horowitz?

  Oh, my God, that's frustrating. Especially if we bet money.

• 18:07Speaker 01

  Exactly. And you you lose money, you train multiple hours a day to get like really good at this thing. And then suddenly you get, you know, you you get destroyed by an AI that is just superhuman on every dimension.

• 18:20Speaker 01

  Funny enough, I was like, I wonder what you think about this, but because I don't have a good mental model about it. But even the the whole model for video platforms, I think, is about to break. Because there's a couple of dimensions to their problem. But one, if if the if the creation of content is is becoming super scalable. Like, for example, I heard about this one guy that created, I think, like, it was like on the order of a hundred videos a day on YouTube and made tens of thousands of dollars a month, all of them are fully AI generated.

• 18:54Ben Horowitz?

  Yeah.

• 18:55Speaker 01

  Um, and people just fell for it. So now the question is, is that actually something that YouTube wants to monetize that way? Yeah, like, is that?

• 19:02Ben Horowitz?

  Yeah, well, it's it's interesting, right? They fell for it.

• 19:08Ben Horowitz?

  But maybe they liked it. Yeah, yeah, like that could be, but it it would sure be nice to know, like, okay, this is a human video or this is an AI video.

• 19:20Speaker 01

  Actually, my thesis about this is like something something along the lines of, I think there's categories of content that are clearly just fictional.

• 19:27Ben Horowitz?

  Yeah.

• 19:27Speaker 01

  Like, movies are that, you know, it's like you you don't care that there's any connection to reality. It's just a fully fictional story. But now, if you think about something like TikTok or, you know, all all these kinds of things, like, people actually really care about them mostly because there is some connection to reality.

• 19:44Ben Horowitz?

  Yeah. Yeah, well, there's reality and there's connection to human, right? So

• 19:47Speaker 01

  That's right.

• 19:49Ben Horowitz?

  You can create a pretty good podcast, like you can take a scientific paper and give it to Gemini and say, make this into a podcast. And, you know, it'll be like a pretty entertaining podcast.

• 20:00Speaker 01

  Right.

• 20:00Ben Horowitz?

  And it will be reality in that it came from, you know, some real thing. But you would like to know that.

• 20:07Speaker 01

  You would like to know that.

• 20:08Ben Horowitz?

  Yeah, I would like to know that.

• 20:09Speaker 01

  And then it continues. As an advertiser, you would like to know, did a human watch it?

• 20:14Ben Horowitz?

  Yeah.

• 20:14Speaker 01

  Or did an AI watch it?

• 20:16Ben Horowitz?

  Yes, right, right. Well, right, that's the other thing is I created 100 AI videos. I had a million AIs watch it. And then I made a lot of money off of YouTube.

• 20:27Speaker 01

  Exactly. I actually saw that video today of a YouTube farm. Like that is like thousands of phones that just watch videos all day for a reason.

• 20:35Ben Horowitz?

  Yeah, yeah. And then like that's got zero value to the YouTube advertisers. And so that's, that's actually a real problem for them.

• 20:42Speaker 01

  Right.

• 20:43Erik Torenberg?

  Well, the whole sort of the creator economy platforms of the last decade, you know, Substack, Spotify, and all the people who support artists or, you know, Patreon, is that creators, YouTubers, they have a personal relationship with these people. It's not just they like the art. And so if they all of a sudden found out that they were, you know, bots, that might, you know, they might not want to support them in the same way.

• 21:05Ben Horowitz?

  Yeah, you might not want to give them a big YouTube tip or.

• 21:10Erik Torenberg?

  Yeah, I think there's a certain subset of people who support, you know, want to support actual people and feel like they're having a real relationship.

• 21:17Speaker 01

  And the thing that I think like people don't really get is that, you know, it should be obvious, but I don't think people really understand the consequence of that. I think two things. One is that what we currently experience is like a super, super tiny thing of what is about to happen, you know, just because.

• 21:36Ben Horowitz?

  Yeah, right. It's a glimpse.

• 21:37Speaker 01

  It's a glimpse. Like, you know, cost of intelligence is dropping almost exponentially. AGNT capabilities are increasing, you know, in like some super linear forms. Like, yeah, what we currently see is less than 1% of what it will look like in probably a year or two. And so, and then second, these things will be actually, they will be superhuman in many ways. They would be like perfectly able to understand you and like talking the right way to you. For example, there's like one paper that I, that I think you could lead after, but it was. It was the Change My Mind subreddit,

• 22:12Speaker 01

  where the University of Zurich did this thing where they had AIs actually interact with Change My Mind. And they were like, superhuman in their ability to change it because they were going back to the profile of the people posting it. They were like, understanding their political motivation, the way they talk. And like, and they're just interacting in perfect, in the perfect way. You know, and just like, hit all the buttons and like.

• 22:35Ben Horowitz?

  AIs are really good at programming humans. That's much better than humans are at programming AIs.

• 22:41Speaker 01

  Absolutely, there's no question. And so I think that's gonna get quite scary also, but.

• 22:45Ben Horowitz?

  I think at least if you know you're being a victim of a psy-op, then, or it's a very advanced one done by an AI, that would be extremely useful to understand.

• 22:57Speaker 01

  Totally.

• 22:57Erik Torenberg?

  Talk a little bit more about the state of the product and the business today. Like, how many IDs are out there? Why don't you give a little bit of an update? Maybe you can talk about the evolution as well.

• 23:06Speaker 01

  Well, first of all, it's a multi-sided problem. And I think there's like roughly three that you have to consider. One is, well, you need platforms to use the technology.

• 23:18Speaker 01

  Then, you know, like, things like Reddit or, you know, X or, you know, things like that. Secondly, you need a distribution of these devices. And I think the right mental model to have for it is, how many minutes does it take a person to reach such a device on average? And, you know, currently, it's, if you would take the global average, it would be a terrible number. It would be like, you know, days or something because many people would need to fly. But, but you know, how do we get it down to below 15 minutes across the US? And so that's probably roughly around 50,000 devices that you need to deploy. That's like, it's not crazy, but it's also not nothing. It's, you know, it's hard to do.

• 23:59Speaker 01

  And then the last one is, how does all of that come together to something that a lot of people really want to use it? And that's a combination of, you know, the utility of all the sub-platforms essentially. But, but all of that layers on top, like, maybe you can use any Reddit account. Maybe you get like, you know, a certain amount of TCHP subscription for free or like. So I think it's gonna be a combination of things, but you need to, you need to land all three at some point at the same time, which is, which is hard to do. We are now at 18 million users that are verified, 40 million total in the app. But. The biggest thing is because of the past administration, because we use crypto, we did not really invest in the US for a long time.

• 24:42Speaker 01

  And that's not the main shift that we're going through.

• 24:45Ben Horowitz?

  Yeah.

• 24:46Speaker 01

  For all of this, the main thing that matters is the US.

• 24:48Ben Horowitz?

  And hopefully, we get the Clarity Act passed shortly.

• 24:52Speaker 01

  Yeah, exactly. That would be really great. So to get clarity on that. Yeah, so the big focus that we now are going through right now is to kind of go all in on the US. So I think over the next year, 90% of the effort of the company is just gonna go about the US. And how do you get, for example, device distribution up? How do you eventually have this in every Starbucks? So it becomes just, you know, super normal and people just use it every day. So that's kind of the... And then on the platform side, actually, we went through a... It was a very interesting experience to go through personally, because I think, like a couple of years ago, universally, people just made fun of us.

• 25:36Speaker 01

  Yeah, like it was like the universal reaction. Well, minus in recent and a couple of other people that believed in it, but...

• 25:44Ben Horowitz?

  Yeah, and the press, like the amount of fun-making of something that... It just shows how short-sighted people are.

• 25:53Speaker 01

  That's right.

• 25:53Ben Horowitz?

  It's like, you don't think the bots are coming?

• 25:55Speaker 01

  What did you think when we first pitched, actually? Because even you must have thought this is crazy.

• 26:00Ben Horowitz?

  Well, because you had the orb. Like, the orb was so wild. You know, okay, we're gonna scan people's retinas and that's how we're gonna know they're human and so forth. And this was, I mean, you pitched us...

• 26:14Speaker 01

  Six years ago?

• 26:16Ben Horowitz?

  Yeah, it was before COVID, because you were there with the orb. And, you know, AI just hadn't happened yet. And, you know, you could kind of see, but there's bots. But they were kind of very crude compared to what there are now. But it seemed inevitable, at least. At the time, you know, the thing was, it was so out, it was so from the future that... You know, we always worry about, okay, like, what's the timing of this and this and that and the other and so forth. But, you know, you were impressive enough and it was gonna happen

• 26:57Ben Horowitz?

  eventually. And it was an exciting enough idea that I think all those things kind of got us to go, okay, we're. But it was not, it was one of, it wasn't obvious that like, it was gonna work in that timeframe.

• 27:12Erik Torenberg?

  It seemed very inobvious for a long time. And how different was that pitch from what it ended up being?

• 27:17Speaker 01

  It was actually pretty much exactly the same.

• 27:19Ben Horowitz?

  I think it's the same thing. The device changed. You know, they've, they've made it much more economical and convenient, but.

• 27:26Speaker 01

  That's right.

• 27:26Ben Horowitz?

  It's.

• 27:27Erik Torenberg?

  But the initial instincts was right, was there?

• 27:29Ben Horowitz?

  It was basically, everybody's got to prove their, you're either gonna have to have some proof that you're human on in cyberspace, or like, it's gonna be a very bad world. I mean, the robots are gonna get us. We're done.

• 27:45Speaker 01

  Right. And then actually, the second piece that was like, this was the first thing is like, it's gonna be, that itself is gonna be a big deal. But in second of all that, you know, when it's gonna become a big deal, we will be able to build one of the most valuable networks as a result of that. Because in a world of AI, having a human network is going to be this incredibly important thing. And, and so actually, yeah, two things, like, one, you will need to prove a human. But in second, it will have very strong network effects.

• 28:10Ben Horowitz?

  And even as the platforms, as you get into platforms, even as the platform's largest problem has been bots. I mean, you remember Elon and, you know, he backed out of buying Twitter because all the stats were based on bots. They still, even knowing that, it was hard for them to get all the way to the future and they're thinking and go, yeah, we need proof of human.

• 28:34Erik Torenberg?

  Yeah.

• 28:35Ben Horowitz?

  Like, it's kind of obvious.

• 28:37Speaker 01

  Yeah, because people were like, what does it even mean? You know, like, what does proof of human even mean? We can just, we can just, you know.

• 28:43Erik Torenberg?

  And did you have the language?

• 28:44Speaker 01

  Detection tools.

• 28:44Erik Torenberg?

  When did you come up with the language proof of human?

• 28:47Speaker 01

  We had, actually, we had proof of personhood for the longest time. It's even here on this, on this brief.

• 28:52Erik Torenberg?

  Yeah.

• 28:52Speaker 01

  But then, uh, at some point, we were like, shit, well, at some point, AIs will have personhood too, so.

• 29:02Speaker 01

  So like, that's not gonna fly.

• 29:03Ben Horowitz?

  But they're not gonna have retinas for a long time.

• 29:06Speaker 01

  It was actually.

• 29:07Ben Horowitz?

  Although that's coming eventually.

• 29:08Speaker 01

  It was actually really funny. It was like some of the, some of the OpenAI people, uh, that I met were like, man, no, like, this is gonna, this is gonna be so dark. Like, people will hate you for, like, not giving personhood to AIs. I was like, Jesus.

• 29:24Speaker 01

  Let's call it proof of human then.

• 29:26Erik Torenberg?

  That's funny.

• 29:26Speaker 01

  So that, that's how it changed. Um, but then actually, so then I would say like last year, so post, then there was like a big shift post, post chat GPT. Like people were like, that was like the AI suddenly got real to people. And then actually, I think, and so that's when people started talking to us, but still were not like, you know, like it's a future problem. It's probably a couple of years out. Like, we don't really care about it. Let's stay in touch. Like, it was like the common response. And then,

• 29:56Speaker 01

  you know, and well, but you also, you had a couple CEOs that really believed it and were like willing to take the long-term bet, um, to, to give them credit. But I think the second big shift was actually Claudebots and Moltbook recently.

• 30:09Erik Torenberg?

  Yeah.

• 30:11Ben Horowitz?

  Just because. Yeah, that, that kind of means like the, the cow is way out of the barn.

• 30:19Speaker 01

  Yeah. And so like, honestly, if you don't take it serious now, then I think you just, you, you should get a different job or something.

• 30:25Erik Torenberg?

  Yeah, what you're doing.

• 30:27Ben Horowitz?

  Yeah.

• 30:27Speaker 01

  They're just like not thinking about problems the right way. Like it's, and so that's, that was like the moment when many, many people started reaching out. And now, now it feels like much more of an executional problem, not, not anymore, um,

• 30:38Erik Torenberg?

  market risk.

• 30:39Speaker 01

  Like a market risk or like a thesis problem or like, like just, uh, and which is still a big fucking problem. It's like, how do you, how do, how do you get 50,000 devices out there? How, how do you make it cheap enough? How do you make it economic? Like, you know, how do, how do you meet all these three things at the same time is still a very hard.

• 30:56Erik Torenberg?

  How do you normalize the behavior, et cetera? So people aren't weirded out in a Starbucks or something.

• 31:00Speaker 01

  Although I, I think that's now gonna be.

• 31:04Speaker 01

  Told you you're used to it. Just because I think people will hate the alternatives so much.

• 31:08Ben Horowitz?

  And I think people are gonna, by the way, take a lot more pride in being human, particularly online, because I think that people are gonna start getting accused of being bots. I mean, it's gonna get really weird. And without like clear delineation, it's it's gonna be a mess. Like, I don't understand how somebody can think they're gonna have a social media platform that doesn't distinguish between humans and bots. Like, that seems absurd to me.

• 31:40Speaker 01

  Sounds absurd. I think we will, my guess is over the next couple of months, we will see, we will see things like these platforms trying to use things like face biometrics on the phone, which, you know, I know it will break, so it's fine, but I think we'll go through that cycle now. And yeah, so we just need to get to scale fast enough to to meet the market to what comes after, which I think something like the orb is the only solution. I think currently there's no real competition. I think we will also see that.

• 32:11Ben Horowitz?

  I have not seen a competitor yet.

• 32:14Speaker 01

  Because it's so ridiculous.

• 32:16Ben Horowitz?

  It's so ridiculous and it is so hard to get to in terms of building it.

• 32:20Speaker 01

  The fixed costs are so high.

• 32:21Ben Horowitz?

  And then there's a massive network effect, right? Which like people are starting six years behind you on that. But yeah, I'm sure they'll come because it's just such an obvious problem now.

• 32:35Speaker 01

  What actually do you think about like AI continues? What in your mind are the economic policies that we will need to implement or directionally?

• 32:44Ben Horowitz?

  I think governments do have to figure out how to send citizens money. They're good at taking money from citizens, but not the reverse. I mean, well, just if you go back to COVID, the stimulus program, like, I think $400 billion was stolen.

• 33:01Ben Horowitz?

  That's pretty great. You would have liked to know that you were sending the money to unique humans. I mean, even if not citizens, as long as they were unique humans, that would have been good.

• 33:10Speaker 01

  Yeah, I mean, the social security system, for example, is a mess in the US.

• 33:13Ben Horowitz?

  It's insane.

• 33:14Speaker 01

  It's a total disaster, so.

• 33:16Ben Horowitz?

  We're gonna have to get to some kind of way to cryptographically strong way to identify who's the citizen of what country like like like that's gonna be a really bad problem. I think so. Otherwise, there's no way to even have a democracy. I mean, you know, like the it's pretty crude what they're trying to do with the SAVE Act, but it's not completely insane, which is how do you even know like the people are voting are actual people or living people or anything? And we really don't know now. Like, we genuinely don't know. And then if you go to, I mean, the whole mail in ballot thing like is built

• 34:01Ben Horowitz?

  for a whole very different world, right? That's right. So like, I don't think in an AI world where you can have like, very high scale impersonation that and then with a broken social security system that like you're going to have the will of the people anymore. Like, I think that's going to be gone pretty fast. So I think we're going to need some kind of, you know, cryptographically strong infrastructure on like who's who. And then, you know, similarly, I think we're gonna have to be able to get people money much more efficiently than through these this crazy apparatus of social programs

• 34:40Ben Horowitz?

  that we have. Just because like how lossy is and fraudulent is social security or Medicare or any of these things. I mean, like the Medicare is so frustrating for people that they shot the CEO of United Healthcare. Like, and people are happy about that, like really happy. So like, think about how bad a system that is. When, you know, and the government spends a lot of money sending you money for your healthcare, but they do it in a like super inefficient way. But we have the technology to do that now. So I think that. AI is going to make that problem so bad because the ability to file fraudulent claims and create fake, you know,

• 35:25Ben Horowitz?

  buy social, I mean, you can buy social security numbers on the black market. Like, for those of you don't know, that's an easy thing. That's a real thing like that is like everybody's social security number is for sale. And so, you know, like AI is just a way of making that kind of loose, black market, underground fraud thing, just massive and extremely scalable.

• 35:54Speaker 01

  I agree with that.

• 35:54Ben Horowitz?

  Yeah, so I think, you know, proof of human is a piece of a very important puzzle where we have to upgrade that entire infrastructure or we're not going to be a democracy anymore. I mean, that'd just be my guess.

• 36:07Speaker 01

  I agree with that.

• 36:09Erik Torenberg?

  Sharon Moore, you said, okay, next year, go to market is focused on the US. Say more about how you're thinking about that is the incentive for people to do it because they get to use a set of services. Is there some other economic incentive or how do you envision it?

• 36:22Speaker 01

  Basically, a month ago, we entered a very different phase as a project where I do believe many of the platforms that we're now integrating with will really, you know, bring a lot of users to our platform. And that changes, you know, how you think about it entirely. Like, if you have a, if you have a platform of a billion users, sending users to you, then it's really just all about like, how do you meet that demand? It's like, you know, and that's, that's, that's what we're now entering. And so, um, yeah, so I think the response is first. I think you will see, and we're already working on it, but you will see a lot of really large platforms that you know, integrate in the, in the near term future.

• 37:06Speaker 01

  I think that will, just to set expectations, I think that will be slow initially because it also should be just to, you know, to get, understand the product. It will be focused on certain geographies, like what we did with Tinder, we started in Japan just to, you know, to, uh, to test the product and also to just normalize the concept. But that will happen. And then, secondly, which is now becoming like one of the main priorities for me is just how do you get this orp distribution up, which is? Which is broadly speaking, there's a couple of different dimensions to that. But one is, first of all, the product needs to work at scale without supervision, which is, turns out to be much harder than you would think.

• 37:51Speaker 01

  Every engineering problem at scale turns out to be much more complicated than you would think. Because fighting for 1% of improvement in quality is this clusterfuck of all these dependencies that come together. So I think that's like one of the biggest engineering focuses right now. But then, second, you need to find places to deploy them at. And the way to think about it is, there are large-scale distribution partnerships. That could be something like Walmart, or if you're very ambitious, it could be something like Starbucks. Or it can just be, you go to one-off hip coffee shops and you just put it there.

• 38:32Speaker 01

  Or, and then you could eventually even go to the DMV and just put it right there. So that's the problem we're currently trying to puzzle together. And it's going to be some of all of that. I think there's going to be some large-scale distribution partnerships, many one-off coffee shops. Actually, one thing that we will launch soon, and the team is going to hate that I'm saying this now, but it's going to be ORB on Demand.

• 39:02Speaker 01

  Just because, actually, it's such a gnarly problem to get an ORB to truly everyone. It's like, to get that, the capex is insane. So it's actually much cheaper and easier to just put an ORB on a motorbike and drive it to you, as crazy as it sounds. So like, in places like the Bay Area or New York, you will just be able to say like, "Yeah, I want to verify now." And 15 minutes later, there's, an ORB comes to you, and you can verify.

• 39:34Ben Horowitz?

  Did you ever think about, this is probably a terrible idea, but having kind of different levels? Like, we know you're a unique human, or like, this guy may be a unique human because he's done it on his iPhone, it's not quite the same, but...

• 39:52Speaker 01

  Yeah, we have that. So actually, generally, we just have to...

• 39:58Speaker 01

  You know, we have the principle of, you know, whatever could be useful for this problem, we just build it. And, and, and so we have something called face check that does that. So it uses, it uses face from the camera. It still uses multi-party computation, what we've built for the entire system. So you're still anonymous. And, you know, it of course reaches way less accuracy. So, you know, as a system, you will know something along the lines of, well, this is, you know, at least one person cannot create 100 accounts. Maybe it's just 10 or 20. So like, it's like, at least it's some measure of rate limiting.

• 40:39Speaker 01

  And I do think, just to set a disclaimer, I think with deepfakes and, you know, all this stuff, I think that will fundamentally break. So it's a it's a temporary solution that I think can get us to scale. That's kind of how I think about it. We also actually use government IDs similarly. We're like, we use just the ones that have NFC ID chip.

• 41:01Speaker 01

  And we use multi-party computation, so you remain anonymous. And platforms can choose to use that as well, but no one really did. It's just somehow they have this like very negative stigma, which I think makes sense.

• 41:11Ben Horowitz?

  Yeah.

• 41:12Speaker 01

  But yeah, basically whatever could do it.

• 41:15Ben Horowitz?

  Yeah. By any means necessary.

• 41:17Speaker 01

  That's right.

• 41:19Erik Torenberg?

  Well, thanks so much for coming to the podcast. It's been great.

• 41:21Ben Horowitz?

  Yeah, thank you, thank you.

• 41:22Speaker 01

  Thanks for having me.

• 41:25Erik Torenberg?

  Thanks for listening to this episode of the A16Z Podcast. If you liked this episode, be sure to like, comment, subscribe, leave us a rating or a review and share it with your friends and family. For more episodes, go to YouTube, Apple Podcasts and Spotify. Follow us on X at A16Z and subscribe to our Substack at A16Z.substack.com. Thanks again for listening and I'll see you in the next episode.

• 41:51Erik Torenberg?

  As a reminder, the content here is for informational purposes only, should not be taken as legal, business, tax or investment advice, or be used to evaluate any investment or security, and is not directed at any investors or potential investors in any A16Z fund. Please note that A16Z and its affiliates may also maintain investments in the companies discussed in this podcast. For more details, including a link to our investments, please see A16Z.com/disclosures.