#37 - Uma Roy

23:17Uma Roy:And then they found that the image classifier is more robust to these adversarial perturbations. So you could always kind of find some perturbation of an image. Like you would take an image of a panda, you would add some simple blurring. It would look the same to a human, but then the classifier would flip from panda to like dog. Right. And this is to do with basically just the fact that you would never actually see a point of that kind in the manifold of where pandas live. You could perturb it out to the manifold where dogs live because there was no training data along that vector typically. It's like very thin on that axis.

23:58Uma Roy:Yeah. Again, I wasn't in this research line. So my naive like way I think about it is like just these are such high dimensional decision boundaries. Like we're going to mess up at some point. And like there is going to be some point in the decision boundary where you think it's a dog, but like too human. It looks like a panda. And like it's just inevitable because like the decision you're just operating over such a high dimensional space. That's kind of how I think about it. Yeah, there's a there's actually a like a the pedal width versus length thing. like there's this irish data set in um in r i'll bring this up here oh yeah yeah i've heard of the famous one you know what i'm talking about right and so it's like um like something like this is uh probably a 3d actually you know what a better one is like swiss roll or something like that right um in 3d basically let's see if i can pull this up so something like this so swiss roll right is sort of something where um you have like the yellow category and the green category aquamarine light yellow blue right and in three space they're clearly distinct um but if and let's say this was you know uh the panda and this is the dog or something like that if you put a vector and you perturbed it in such a way that you had a point that was i don't know 60 percent of the way towards this blue part and there's no normal points that existed here in image space.

25:32That's my intuition for how the perturbation works. I should look that up, but that's certainly how it works with low dimensional things and probably something like that works with higher dimensional. And similarly to the pedal width one over here. Anyway, I want to get into succinct because this is the probabilistic. Let's get into your deterministic. Go, go, go. So this also, So if you had something over here that'd be outside of the training set, you could misclassify it as a circle when it was actually a triangle or vice versa. Okay, go, go, go. It's all your ball.

26:08Uma Roy:Yeah, so we fully established that, yeah, the AI detecting AI, so it's like not going to work. That seems bad. So it's the same. Well, okay, AI makes everything fake. That's what you said. What's the solution? Crypto makes it real again. Yep. So we're big believers of that. It's a thing doesn't apply to cryptography company. So now, like, let's dive into what that actually means. So today, like, how does content actually get posted online? I mean, basically, first, it gets captured, whether it's on like a smartphone or a camera or a microphone for audio or some other sensor. then it goes through some editing uh whether it's like photoshop or these ai editing tools and then it gets published so it's like across social media news services news wires traditional media youtube and then it gets consumed so you look at the content and you say like you you just look at the content so that's kind of like the current life cycle and yeah throughout all this there's like no verification so it would be impossible for you to tell if something's real or something's fake.

27:15Uma Roy:Now, how does crypto help with this? So this is like what we're building at Sysynct, but we think there's this notion of basically what we call the provable technology stack. So at every point in this like capture, edit, publish, consume lifecycle, you insert in cryptography and provable technology to prove its role. So to start, when you capture something - Yeah, this is exact. This is you must have taken some of my content and maybe. Yeah, yeah. OK, OK. A lot of it is very inspired by like a lot of your work. Yeah. OK, well, this is great. So basically there's a crypto camera and then chain of custody, ledger of record, public verification.

27:56Exactly. This is exactly the stuff that I've wanted out there for whether it's scientific experiments or something. Keep going. I'm listening. I know this. Say what you're going to say.

28:05Uma Roy:Yeah, yeah. I mean, and yeah, like all credit words do. I think you identified that this is the solution maybe like five years ahead of its time, five years ahead of the problem. And you're always very ahead of your time. So a lot of this stuff is like very inspired by your work. And I think there's a lot of other, like I think Mark Andreessen has talked about this actually, and I'll get to this later, like the head of Instagram is now talking about this. But yeah, okay. Just to get into what is a provable tech stack. So at capture, things are captured on hardware devices. Hardware devices can have private keys that are binded to the device.

28:41Uma Roy:So you have a cryptographic chip with the key. That's kind of how you can think of it. And basically, like as the raw sensor data is coming into the camera, the cryptographic chip signs like the content of the raw sensor data, and it binds like the content being captured to the specific device time and location. So that's cryptographic capture. Then as the content gets edited, you have this like chain of custody and chain of edits. So there's a cryptographically signed manifest for every transformation you do, whether it's like cropping or color correction or grading or things like that. And you basically keep this append only record of what's going on to the image.

29:21Uma Roy:and then finally you publish the piece of content and the manifest of the original signature when it got captured to the chain of edits and you publish that to a unbiased permanent ledger which is like this ledger record and then when the content actually gets consumed so it's like in some front end whether it's youtube or instagram or x um the front end integrates with the ledger and it basically verifies all the signatures, verifies they're real and displays that information to the user. And if the user wants more information, they can just click and verify all the signatures for themselves.

30:01Uma Roy:So today on most content platforms, we have the blue check mark for your verified identity. You can imagine in the future, maybe all content comes with a pink check mark that says, hey, this content is actually real and here's the device and here's the series of transformations that happened to it. Mm-hmm. Very cool. So, okay, keep going. So, yeah, this is the provable tech stack, and this is, like, all the stuff we're building at Succinct. And, yeah, I think, to your point, you talked about this for a really long time, which is, like, very cool. And I think, finally, like, other people are starting to catch on because, like, the problem is finally very evident.

30:40Uma Roy:So, there's this quote from Adam Masseri who runs Instagram. Cryptograph, please sign a capture. Yep. So yeah, he posted at the start of 2026, he posted like, hey, here's Instagram's like kind of what we're thinking about, what I'm thinking about right now. And he says that basically we're going to move from assuming what we see is real by default to starting with skepticism. So he's kind of identifying this like AI mix everything fake problem. And then he said, okay, platforms like Instagram will do good work identifying AI content, but they'll get worse at it over time as AI gets better. it will be more practical to fingerprint real media than fake media.

31:18Uma Roy:And then this is kind of like the thesis of Prove What's Real and all this cryptography stuff. Camera manufacturers will cryptographically sign images at Capture, creating a chain of custody. So, yeah, I mean, even like people like Adam who are running Instagram are saying that crypto is going, cryptography is going to be the solution to this like AI, the problems that AI creates for like content platform. That's right. Now I think actually crypto social and AI are all interlinked here because another piece of this, which is actually implicit in like the first part of what he's saying, starting with skepticism, pay attention to who is sharing something and why.

31:58I think actually AI and crypto together are going to result in, you know, like, you know, I think the future is China versus the internet. Did we talk about that? Have you heard me say it, talk right about that?

32:12Uma Roy:I've heard you say a little bit about it. So I think the future is a billion person Chinese super state or a thousand million person network states. Why? Because everybody thinks about AI improving productivity, but that was only true within a tribe where you can trust, you know, you can share information. And whether you call it indexing or surveillance, right? Because one is good and one is consensual and one is bad and one is not, right? So it is indexing everything and it's learning everything and it doesn't really miss like a single remark somewhere. AI can pull out a remark from like three years ago and surface it and synthesize in a way that no human, you know, or you'd have to have a very attentive, smart human.

32:56It was human limited, that level of surveillance from before, right? Right. So, or that level of synthesis, you know, the look over every commit and find security holes from years ago. It's amazing. Right. But that operates within the tribe. Outside the tribe, it's spam, it's scams, it's slop. Right. And so basically the cost of production goes way down, but the cost of verification goes way up. And so this part about paying attention to who is sharing something and why, I think another big piece of this is web three of trust. So you take web of trust, like I trust you because I know you and I've known you in person.

33:40And when you cryptographically sign something on a camera, there is the human part of that as well as the machine part. like ultimately if i wasn't actually there with you in the room i have to trust at some point some human assertion that this data because i can see it on chain that it was stamped at this time and um there's various proofs that one can put on there like proof of location proof of this proof of that but ultimately at like you as a human have to tell me that you didn't manipulate it before you cryptographically signed it, like you, because you could do something upstream, like the analog hole upstream, you know, the equivalent of putting something in front of the camera, right?

34:23And we can make it hard to do that, but we can make it impossible to do that. And unless like every single camera has one of these, and I think maybe it'll get there eventually, but there'll also be a demand for those things that don't have these, kind of like burner phones, you know what I mean, right? And so, and there's so many phones out there, there's billions of phones that do not have crypto chips in them that, just like you can get an old laptop, you could get a fakeable phone, right? And people will also revolt against too much tracking or what have you. They want it to be free, whatever.

34:56Anyway, I think that's another piece of this is the full supply chain of custody includes the person who's sending it to you. And so who is sharing something and why? If they're within your crypto tribe, crypto thinks tribally natively and ai is going to make people think tribally necessarily and so everything reduces to digital tribes where digital borders and physical borders become the same and china is the biggest digital tribe of all because they can centrally moderate all of their chat apps and so on and so forth like they just whatever ai detection stuff they roll out and we chat they can force human verification and so on and say i have just a central choke point where basically a billion people get onboarded into whatever AI detection, prevention, fake detection thing that they want, but the rest of the world doesn't have the same level of, I mean, Google and others can roll out certain levels of things, but they've almost opted for a more anarchic standard because of the whole freedom of speech fight, right?

35:56Which I get, but there's a undercorrection and an overcorrection on anything. And what you want is consensual moderation, I think. Anyway, so it's a compliment to what you're saying. Keep going.

36:05Uma Roy:Um, yeah, I, I think what you're, I think in the future, like it's not, I don't imagine a future where every photo posted Instagram is required that it's real. Cause like, I mean, some AI pictures are really cool or like really interesting. I think it's more like to your point of consensual moderation. It's like, if you want to prove something's real, and I think a lot of people deeply care about that, well then now you finally using cryptography actually have the tools to do that. And then, yeah, if you want to follow content creators that have those capabilities or only post real stuff, you can do that.

36:41Uma Roy:And then, you know, social media is one thing, but obviously for things like journalism, I think Nikita Beer, who's the head of product at X, tweeted about this. There's these accounts posting totally fake pictures from the Iranian war, and it's like pretty bad and like people are getting misinformed. And so obviously that's like not OK. And I think this sort of technology, I'm hopeful will help with much higher stakes situations like that, or, you know, political ads or like what the president is saying or things like that, I think will be really important to like prove what's real there. Great.

37:12Okay, cool. All right, keep going. Cool.

37:15Uma Roy:I mean, yeah, I think the rest of the slides are just like a little more detail about what's going on. So already today, you said, you know, how many cameras actually have this cryptographic chip. Well, fun fact, every single iPhone does have a secure enclave that has this capability. And so, you know, interacting with these enclaves across all the device types is really hard. And so we've built this SDK to kind of provide a unified experience for people who want to use it. Is it free? How does it cost? How much does it cost? Yeah, yeah. The SDK, well, it's not published yet, but we're going to publish it.

37:49Okay. I want to try, I will commission some apps on this once you publish this.

37:53Uma Roy:Oh, okay. Yeah, yeah. That'll be cool. So that is actually the foundation of a new kind of media. Yes. Yeah, yeah. Yes. Yeah. I think there is a lot of potential there. I think incentivizing decentralized media collection in an AI first, crypto first, social first, mobile first, internet first way, this is like a missing piece of that. Where we have all of these, quote, reporters from around the world. and on any topic that we care about, we can incentivize first party reporting where we pay in crypto and we verify in crypto, where we pay in cryptocurrency and verify with cryptography. We essentially have like a decentralized news outlet.

38:39So this is something that I want to get going and maybe we can collaborate on this. We can talk about this right after this.

38:44Uma Roy:Yeah, that would be very cool.

38:49Uma Roy:And yeah, with citizen journalism, Like you kind of, well, especially now with the AI generation stuff, you actually do need a way to verify that it's actually real. And so I totally agree with this. And I think we would focus it on the news of the network state and startup societies and cryptocurrency and technology, biotech, areas that I think are not well covered but should be because they are for tech decision makers. because the thing is news is a huge topic, right? And rather than the news of the state, we'd focus on the news of the network and those types of things that are, like with a relatively small amount of money, you could get much more coverage of them because they're more important for technical decision makers.

39:37And that's kind of the niche that all of these tech outlets basically abdicated. And actually in part, the reason they abdicated is because a full-time journalist is, like a professional journalist, is often somebody who doesn't actually know technology because if they did, they wouldn't be a full-time journalist. They'd be actually like a player on the field, right, building. So, moreover, by being a, quote, full-time journalist, they're loyal to the journalist tribe as opposed to the technologist tribe, and technologist tribe is taking away revenue from journalist tribes, so a lot of their coverage is very hostile.

40:14So the way we solve both of those problems, in my view, is rather than one full-time journalist making, I don't know, 50K, whatever it is, we have 50 part-time journalists who earn$1 ,000 bounties for writing up what they know. And because they have domain knowledge, if they write up one article a year, we're good.

40:34Uma Roy:Right. So that's like NS News. And so maybe we can integrate. Yeah, yeah. Yeah. Okay, yeah. We should talk about that. Yeah, you can build that with our stuff now. It's like pretty, the whole point of that is it makes it easy. Okay, great. Go, keep going and let's talk more. Go. Cool. Yeah, then there's the provable edit history part where after you get the provable capture, you do all the stuff you want to do with it. And there's actually these existing standards for it called C2PA, which kind of tracks, which is a metadata standard that kind of tracks, okay, who, what series of edits did you do?

41:07Uma Roy:What production did you do? And then it appends it to a manifest. and then finally after you've kind of compiled the proof of capture the proof of edits um it gets published to this thing which you came up with this name the ledger of record which uh is this like open unbiased you know place where all this content gets published and then that's where all the content that gets displayed in front ends so for example instagram or x or whatever it can read from this ledger, which is basically just a database of like what is actually real or not. So that's kind of our vision for provable technologies and like the whole stack.

41:53Uma Roy:And yeah, we kind of imagine that this stuff will show up one day in every single app, every single real picture on the internet will have a pink checkmark that says it's real with all the signatures and all the cryptographic proof. And you can, anyone viewing a picture can just look at that and know what's actually real. So that's our kind of vision for how cryptography is going to solve a lot of the problems posed by AI. Amazing. Okay. So, um, people should go to succinct.xyz? Yeah. People can go to succinct.xyz, um, or follow us on Twitter at Succinct Labs. And we will be posting, we're building this whole stack and we're going to be releasing like a lot of products and related technologies, you know, in the coming months.

42:44Okay, awesome. Okay, so...

42:48Uma Roy:It'd be interesting to hear kind of your vision for how you think this is going to like be put into the world or like, you know, you've been talking about these ideas for so long. I'm just curious to know like more about why I got what got you excited about it and like how you think this is going to like proliferate. Sure. So, um, well, what got me excited about this? Um, you know, in the nineties, like, you know, when I was, I was a kid then, so I'm about maybe 10, 15 years older than you, something like that. Uh, or I mean, I, I would never presume to know your age or whatever, just saying like probably, probably in that ballpark, right.

43:23In the nineties, nobody cared about politics. It was something where it was literally being interested in politics was like being interested in the train tables or the bus schedule or something like that. And it was genuinely something, why would you care about this legislative, this and that? No one cares. And you cared about music, movies, sports, video games, whatever, right? It was just a vacation from history. And so for much of my life, I was essentially just an apolitical academic. And all I care about was math, computer science, bioinformatics, all that kind of stuff. And then after essentially the full political breakdown of arguably, you can argue when it started 2001, 2008, 2015, 2020.

44:21Everyone's got a different moment, right?

44:26There's a saying, which is an amazing tweet, if the news is fake, imagine history. Okay. And you actually start realizing a lot of the movies in the 90s were almost like the collective unconscious was putting out movies like The Matrix, Eternal Sunshine of the Spotless Mind, The Game, Dark City, Fight Club, 12 Monkeys, all of which were essentially about your memento, right? Your memory playing tricks on you. And in some sense, the world was not what it seemed, right? The Truman Show, right? The Truman Show, The Matrix, all of these are like you're living in a constructed world, right? Memento, your memory of the past isn't the same, right?

45:15And it was as if like almost the collective world was waking up to realize that the centralized century of the 20th century was an illusion in some ways, and that there was more to the past and they'd sort of been, you know, hypnotized, zombified or what have you. And so putting those together, you know, I started asking questions like, how do we actually know what's really true? Like, let me give an example, maybe a seemingly trivial example, but this is in the network state book. Let's even take F equals MA. How would you actually know that's true? If you track it all the way back, ultimately there are scatter plots.

45:58You know, when people rolling balls down inclined planes, right, where they are taking X and Ys and correlating them and then effectively doing a line fit that is then generalized into this deterministic physical law, right? Underpinning everything that we think is true is ultimately a set of observations that you could track all the way back to Newton, like, you know, the famous, you know, apocryphal apple falling down, right? Like what you think you know is true, if you can track back all the citations all the way back to root, that's the reason that we think it's true. Why is that actually sometimes important to do?

46:37Well, I'm forgetting, this is a whole complicated story. And I think it's something like, there's a story about vitamin C, I believe, in medicine. I'm probably getting this wrong and I'll look it up, but it's like vitamin C supplementation, but it's, what was it, spinach? There's a whole medical story. Hold on, let me find this. The iron myth, right? Spinach is a good source of iron, right? And this is one of those things where somebody tried to track it back and it was either this or something else where when you tried to track the citations all the way back, It was a complicated mixture of multiple mistaken citations on top of each other.

47:28I think this is it here.

47:39Look at this.

47:44The sudden thing. I think this is it.

47:46Uma Roy:Um, basically the complex and convoluted myths is the one call for want of a less complex name, the iron decimal point error myth.

48:00And essentially it is a decimal error knowledge gap. It's like a myth piled on top of a myth. It's like something complicated enough that I have to go and remember it. Right. You can look at this document. The point being that that is a concrete example of something where someone literally dug through every citation going all the way back, and they found that the thing that people thought was solid was actually based on nothing. right? All kinds of social science has failed the reproducibility crisis in this way, right? So all kinds of political science, history, social science is something where now with LLMs, we can back solve and go all the way back, right?

48:51Because it's much better search, right? So you can track it all the way back to all the original citations behind the claim, right? You can push it pretty hard to do that deep research, whatever you want to call it. Like, you know, the team of agents thing that Grok has can pull like a thousand sources or something like that much faster than a human can. And so now we can really, remember that Trugel thing that I was talking about?

49:12Uma Roy:Yeah. We can really start interrogating. It's almost like the, you know, the Bertrand Russell program in math of really trying to put math on an axiomatic basis, right? And really trying to have as few axioms as possible. He builds the whole thing from set theory. And I think it's like on page 347, he says, and thus we prove that one plus one equals two. You know the thing I'm talking about, right? It's like a famous thing in math, right? So you're probably aware of it. So like that, I realized how ignorant I was about what had actually happened in the past, about what scientific facts were actually true, about how scoped my knowledge was.

49:54And I started to ask what, I know this is a longer answer than you wanted, but this led me to this, right? It's like, I was like, you know, as a research scientist, and you're a research scientist also, we're in the unusual position of being pre-headline people. And what I mean by that is, like, this was more true on the Twitter of like five years ago, but there's a fair number of, let's call them normie NPC type people who genuinely cannot believe something is true until it's appeared in a headline. That is to say, until NYT or the State Department or something like that, their implicit epistemology was, is a reputable source saying it?

50:37If so, then true. If not, then false. Now, this was always bizarre to me because as a research scientist, you're used to figuring out if something is true on your own using logic and reason. And eventually I was able to figure out this difference between pre-headline people and post-headline people. A pre-headline person, you have some scientific finding and you are going to publish it and you are actually the upstream source of that finding. Like the press release will be based on your paper, right? Or conversely, you have some VC investment round and you know something is true before the world knows it's true.

51:14So you're actually upstream. It's like a miner. You're mining truth before it's being sold at the market. However, you realize that actually the guy who's a post-headline person has some wisdom all his own because he implicitly, I'm not saying they're doing this explicitly, they kind of know that you can only be a pre-headline person in so many areas. Right. Like you can't be an expert on Turkish and Japanese and I don't know, Brazilian iron ore and so on and so forth. Much of what you're sensing is going to be essentially on some web three of trust, which is based on some information supply chain.

51:49Right. Anyway, it was through thinking through things like this and how we build a higher standard of truth that got me to where we were. Let me pause here.

51:59Uma Roy:Interesting. um yeah i guess you've been thinking about this for a really long time and then i think we've been thinking about this for honestly maybe the past three to six months as we saw the ai problem get worse and worse and there's this interesting asymmetry i mean our team is based on software there's so many smart people working on accelerating all this ai stuff which is really good there's obviously incredible positive externalities. But I think if there's a technology that's genuinely so powerful, obviously, it's going to have negative externalities. And I think there's very few people focused on combating these negative externalities.

52:40Uma Roy:And I think in this domain, with the pictures and images and fake audio, and, you know, that poses real problems. And I do think this is an area where the combination of cryptographic hardware, cryptographic software, chain of trust, custody, ledger record, provable technology broadly as a category can actually help some solve those negative externalities. Amazing. Yeah, that's how I got to it. But you got to it much earlier than all of us, which is kind of your specialty, which is very cool. Well, thank you. But I appreciate you also grinding through all the details to actually build the SDK and so on, because obviously that's non-trivial.

53:25So let's talk more about that. And Uma, thank you for coming on Never See a Podcast.

53:31Uma Roy:Thank you for having me.