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Created: 10/11/2026 4:25:06 PM
Duration: 5219.135
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Yeah. Well, welcome.
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Hello, and welcome, dude. We are on, like, a regular cadence now. This is Magic. Magic Internet Math podcast.
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We're doing it. We are, like like,
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what what the hell did we agree to do,
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when we decided
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to do this math? I mean, I started a math podcast two years ago.
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And
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when it had to end, I remember thinking at the time it
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can't end,
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Right? And it had to continue. Didn't really,
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you know, we were not in the world we're in now. But like, there was just something
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nagging inside of me. Like there's no way that
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this math podcast can stop. Then we pick it up. Pick it up again, I pick it up again, you know, with you
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and
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we start in January.
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God, we started in January, it's October now.
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And
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it's a... It's... It feels like we have been running into a storm the whole time.
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Yeah.
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Well,
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you know, sometimes you do things, you know, because you just have
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you you you you do things like start a podcast sometimes because you just feel a calling, and there's no one else occupying that space. Right?
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And
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the entire domain of math was just basically
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disregarded.
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It was something that would get
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coverage as a guest on a podcast. Like, you'd maybe bring a cryptographer on, like, once a year. An insane guest on a podcast typically. Like, I'm thinking, like, it's a Terrence Howard on Joe Rogan. You know? Like, you would get the little things like that where somebody would be painted as insane but with
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semi interesting views.
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Yeah. Yeah. I mean, when,
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I mean, listen. Alan is one of our four listeners of this podcast. We don't have to make fun of him, like, right on the show. They they would bring Alan out every once in a while.
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What's his title again for this podcast? The, executive... Is he the board member of the... Like, what is he? The executive director?
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Spiritual guide? What is what is he? Like that. But we Yeah. Yeah. We we we think we're we think we're gonna do something this week, so everybody, watch out. But by the way, so we named Alan, I am Rob.
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This is... I am Rob. I am Brian. This is Rob. Mix up the clankers. We're killing the clankers right now. I am Brian. My partner here is Rob,
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CEO of Bitcoin.
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Needs no introduction.
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And, we think we're gonna have Alan on this week. So Yeah. But what what am I... One of my big directives as CEO going into... I joined in the middle of the fiscal quarter. So we're doing some transitional stuff right now. But the math podcast was one of my top priorities as CEO of Bitcoin to make sure that everyone's gonna eat their damn vegetables. And if you wanna live in a world of not trusting and verifying, you're gonna have to look at some math. I'm sorry. I'm sorry. You're gonna have to do it, and we're gonna make it as painless as possible.
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And to which I will start with
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something that we spent 10 episodes talking about, elliptic curve cryptography
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is
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right back at the top of the news. We'll get to that in a little bit. Gets old. Old. Never
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It never gets old because it's holding trillions of dollars of wealth. So That's right. We will be getting back to that shortly.
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But mathematicians
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not doing great this week.
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They're they're, I
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think as the kids say, they're crashing out. They are crashing out as some... You know, they're crashing out. They're they're going crazy.
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You know, I had some long conversations with Kayla,
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who if you guys listen to the podcast may know my daughter who, you know, has been on podcast. She's
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a math major. She's a senior.
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She's pretty dug in.
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Not much that can happen in the world that's gonna change the trajectory of the fact that she's gonna be a mathematician.
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And we had a couple of long conversations
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after,
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know, she's she is neck deep in the academic
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academic environment
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in college. So she's getting...
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The conversation she's getting is from
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people who are mostly getting... Who got blindsided by
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OpenAI throwing
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what was it like
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the solutions to like 18, essentially
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18 long standing problems with
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like lean proofs
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and
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the whole kit and caboodle.
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I've since brought all of that onto Magic Internet Math. So if you want summaries of any of all of those things, you can go there and look at it. Like,
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you know, what seems so... Mathematicians
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are very upset
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And it's it's complicated, but the mathematicians are upset mostly because...
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Here, I'm
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gonna get killed. If anyone besides Alan and three other people listen to this, I'm gonna get killed for this. But, like, the reason mathematicians are upset right now
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is because their entire complex of how they get funded is being dismantled by AI essentially. It's like these problems, what gets funded is the attempts to solve these problems. And then,
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you know, universities, programs,
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all these programs get funded to do it. And then, you know, some computer just solves them all in a second. And,
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you know, you are your sort of economy is in shambles.
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But that's not even like the big picture thing. But that's what everyone I think that's what everyone's really upset about is like,
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they're now their careers on a chopping block like all the others.
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Right. As though there was a bit like as those society like as those society viewed mathematicians like accountants in terms of having careers,
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you know, people... Right?
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Yeah. But nonetheless, what little what little they had has been snatched.
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It's been really carved up. Yeah. And I think there's actually an uplifting part of the story here. But... So we had, what, was it, like, 300 papers that got put out by
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Open
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By OpenAI. Yeah. It was, like, 300.
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Yeah. They just, like, dropped it.
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And so I think the one that probably everyone saw was this,
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packing of, what was it, 11 squares optimally into a space,
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and it looks
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sloppy and horrific.
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Like, it doesn't look clean and nice.
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And was this, like, basically the one
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maybe accessible
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thing that can be put out for people? Is that really... Is that why, you know... Is that why this was the one that was chosen to sort of be
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be the example? Well, was nice to see,
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like, something in a clear picture. Right?
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Or did or did they put a lot of things out and that one just happened to be the thing that got memed? I think that one got memed. It had good meme It
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did get memed Yeah. Pretty
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And I don't think everything's lost though.
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I agree completely.
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Because there's the...
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So maybe to take a half step back here and explain, like, Lean.
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Right? It's a it's a programming language
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that...
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And and maybe there's actually a really good video. I'm gonna send it to you right now to throw in the show notes. There's this
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content creator who does, like, coding stuff called Primogen, and he actually did a really cool video, like, talking about this
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and laying down, like, some of the context. But,
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lean is a programming language that you use for mathematical proofs. Right? And the reason why,
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AI models are able to attack this, whereas if I was using,
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OpenAI's
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latest model to try and find some scientific breakthrough in chemistry,
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it could come up with a theory, but then it's like, now I need your wet lab to pair
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to do the observation and the experiment. But since abstract
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math is purely just numbers,
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you can actually in parallel sequence out and kind of like build these things.
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And so
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that's why you're kinda seeing this, like, this, like, little bit of a takeoff and hitting all of this stuff.
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Some of the papers so would you say lean is, like, going to the math store and
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asking to verify
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Lean is
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Lean is going to the Home Depot of the math store, and you just take all of the raw inputs, and you just start excel... Like, you just start... It's not quite a brute forcing, but you just start taking all of these small concepts, and you start building them up into one interconnected thing. Right? So you can start all the way at the foundations of math and use those as sub proofs for future proofs. Right? And then you kind of build a chain of validated logic.
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And But it's how a person actually
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sees what the computer did.
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Yeah. It's essentially an audit trail of what AI did to solve the problem.
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Yep.
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Exactly.
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Yeah. And so you're seeing these solutions. Like if you look at this one with the
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five... The six aligned squares in the box and the five tilted squares, You could even see that, like, one square is wedged into the gap of the two other squares. Like, it doesn't look clean. It doesn't look nice, and everyone's trying to understand, like, why is that? This is, I think, actually where mathematicians
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step back into the fold though because someone looking at that original proof
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realized,
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wait a second,
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you could
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do a transformation.
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And, are you familiar with the Fibonacci Taurus?
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No.
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So I'm sending you a screenshot right now so you can see this. If you actually rearrange
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the squares
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into a Fibonacci... Through a Fibonacci Taurus,
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you actually get a beautifully symmetric clean picture. I just sent it to you. Oh, man. That's crazy. Do you see that? Yep.
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A torus, by the way, is typically
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viewed as like a donut. It's
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like a topological
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object.
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In math, like you learn about a torus in like algebraic geometry or topology
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and it typically looks like a donut.
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Right. In this picture, I mean, it doesn't have to look like a donut but that's typically the visual that almost
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to, you know,
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some continuous object. But in this picture, it's I'm not seeing the donut. So that's Well, so it's a
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I'm pulling up a model right now that can load it for me. But yeah, so it's using the golden ratio and it actually does a transformation.
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And
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if you wild, though. Were to do that It does look So this is the beauty of mathematicians,
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though. Right. Is the fact that ordered is this thing was orderly. Bingo. And I think we're gonna talk about this. If you wanna, like, tee up Terence Tau and, like, math stuff, but, like, these proofs are really...
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Are incredible
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in being able to kind of, like,
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shake up the known domain knowledge and kind of solve some problems, but we're not getting clean solutions, like one with
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linear
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algebra multiplication,
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right? Matrix multiplication.
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We always thought it was, I think it was what, n log n was it for the
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for the, like the the the computation
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time to do this stuff. And we're actually finding like a race now of getting fractionally smaller and smaller and smaller, which implies there's probably some lower limit that we haven't even thought of before. You wanna step back, you wanna just step back and say
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two minutes on
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that what computation, how computational
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time is discussed and measured and what you mean by n log n versus say two to the n or versus,
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you know, do you wanna just say something? Yeah. Real quick there. So this is something that
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anyone in computer science,
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any sort of background would have experience in. And it's kind of this idea of big O notation, right? And so the time it takes to compute something, let's keep it very simple to start. Let's say you have a for loop. You wanna count from zero to 100 or zero, and you just print one, two, three, four, five, six. Right? And let's say you wanna do that,
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up to
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any length you want. Well, the time it would take for that algorithm to even run would be n, big o m. Right? And then
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the... Like, the the the next example that would be like what people talk about when you're thinking about programming design things would be like, what if you had a nested for loop? So it was a loop within a loop. Well, now you're at n squared. Right? Because you have to take the length of the list through both of those things.
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And
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as a starting place, this is, you know, teed up for... As it relates to computer sciences because oftentimes you can rewrite algorithms more efficiently
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than the naive way. Like, if you're a simple brain, it's like, I need to do this, and then for each of those, need to do that. Right? I'll do two loops. It'll work. It'll just take longer, but oftentimes there are,
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mathematical
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transformations and ways you can reevaluate the problem where you can actually do it much faster.
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And so,
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you can have it,
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you know, in things that take n log n, n log n. Right? These are all
different ways and approaches.
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Square root of n. Right? Depending on whatever the given
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transformation is, like, you'll be able to understand that. And the thing I'll add is what it shows is how
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time how it takes scales
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over,
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like you want to know in the moment over the
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infinitude of computations you're going to actually do. You just want to know how does
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the time it takes scale over that like infinitude.
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And that sort of tells you in the moment.
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I think one of the I think I mentioned this on the podcast before, but everyone should check out Neil Koblitz's
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book.
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It's on my it's on the website on the magic internet math website,
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but
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I think it's called number theory and cryptography. It's considered a graduate level book, but it's really very accessible.
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Excellent. I went through the whole thing last January when I started this podcast originally.
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And literally
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in the first page of the book
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is Big O notation.
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It is like the most fundamental thing to know about cryptography.
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Because in the if you're, you know, if everything is completely random,
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okay, right, and you have perfect entropy, and then it really just comes down to you.
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Is the force you're applying with your cryptographic algorithm?
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Does it overwhelm
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the force an attacker can
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Right. Can provide? Which trivially, we always say that, like, if you're trying to brute force... If you're trying to... If I'm trying to get your Bitcoin key, my really, in general, best way of doing that is brute forcing and guessing all possible numbers between zero and two to the two fifty six. Right? And that's the asymmetric
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defense that you get with cryptography.
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Right. So what big o notation measures is the... Really the force that can be computationally applied to a problem.
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And
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that's how so
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when we talk about
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like when we say the big O is N, we're saying that the
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power scales linearly,
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like one to one linearly.
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When
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it scales at like the log of n, we're saying it scales less than linearly.
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Correct. So when we say it scales at like n squared, we're saying it scales way, way more Exponentially.
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Exponentially. Right? So, like, that... I I wanted to just make sure we have that out there.
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I just wanna make sure for posterity, we have that out there for people. Because,
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know? Yep. We're probably gonna talk about it a good bit with these these examples.
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The other thing I wanted to say was,
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if this is a yin and yang situation
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with AI solving these problems, and I think you explained
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it really well, but like,
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there's this one side where everyone's upset about
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you know, the, these projects were funded and AIs come to solve these problems. And then there's this thing where, okay, well, then immediately somebody just came and made
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an extension on it that made beautiful sense. And the thing is nobody paid that guy to do that. And
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that... But, you know, we still have...
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Like, mathematics is still filled with people who just want... Who have love of the game and want to continue to make sense of things.
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Right? And it's like Yep. That's
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the thing that's gonna matter long term, and it's amazing that we saw it immediately. Like, we saw somebody do this immediately because it's like,
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you know, in in one sense,
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it's
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it's like you're trying to play a game,
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and the game might have to take hundreds of years. Like like we talked about Fermat's last theorem on the podcast about how over the three hundred plus years of trying to solve that, we invented algebraic number theory.
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We figured out fray elliptic curves. There were
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like multiple fields that we had to invent in order to solve that. And if you just go back in the thought exercise and say, if a computer what if Fermat had actually provided the proof?
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Would
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we actually have done all that?
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Probably because
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he would have provided the proof and everyone would have been in the same spot that they were in without the proof, which is like, what the hell? What the hell is this? Right.
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Right?
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So then it would start that we would just start,
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you know, and it's just, you know, it happened that there was there was prize money funding for Vermont's Last Theorem
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all that time, but maybe there would have been also to make sense out of it. Right? Maybe we will be offering funding and prize money to say, okay, OpenAI just dropped a bomb.
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It's time to make sense. It's time for people to think about rationalize and make sense of it. Yes. Which I think is gonna be the standing value of the mathematicians because
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these machines and their, like,
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strict mathematical
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precision are able to show breaks in previous mental models of what we thought was a theoretical end, And now you need to re rally the theoreticians,
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you know, the mathematicians
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that are doing the theoretical stuff. They need to reorient their career trajectory and not have it just be, I'm gonna sit around and try and solve this problem.
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They're gonna have to be like the human cipher that comes in and tries to do these transformations to understand, okay. But why is this happening? And the reason why you want them to explain why it's happening,
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one, in theory, it's possible that that the machines could also do this job.
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But
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you want to be able to just not say, well, we have a proof, and we now know something's broken.
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It needs a new,
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like, theoretical,
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like, abstract scaffolding to go around it to explain why it's happening. And then the recur... The loop would be once you have that and you flesh that out and you formally prove whatever the new scaffolding is, maybe you can break things another leg. Right? Like, it's gonna be like a... It's gonna be a lobbying back and forth, like a dialogue that happens between the machines and man to be able do that because just because you can prove something breaks. Obviously, that is
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a massive significant, like, advancement in the field. But you're gonna wanna be able to, like, make it into a pretty picture. Like, we'll show in the study guides with this,
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this torus,
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the Fibonacci torus,
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of the pack squares. Like, it just... It shows you that the, like, the beauty in the math is still there. You just have to... The way we were looking at the problem doesn't work. And and in that video that I... That I'll link, we'll put in the show notes, they talk about how if you were to just basically,
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like, take, like, a spiral graph out from, like, like, on planar coordinates to, like, graph that, it looks really weird. But if you shift it to polar coordinates, it's instant. You just, like, increase your number, like, just, like, linearly. And that's to show you that like if you just rearrange and rethink the problem
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going from traditional coordinates to polar coordinates,
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something that looks like really hard and complicated gets like trivially easy. We have to put a pin in that one and definitely save that for another conversation. That's a big, big, big, big one.
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Polar coordinates or Yeah. Like, would it meet that exactly? Like presenting something in polar coordinates and then having it be just a different world where everything makes sense.
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But
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don't remember the
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math book that I got at BTC Prague by the author Jan Kopas. Yes. And I showed you the cover. I did this with Alan on. I showed the cover and basically he represented the elliptic curve as a torus, proper donut.
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And I found that to be beautiful. That's what really got me starting to think about toruses
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in general. And like how... Like I thought it was powerful for us to go through all the episodes we did and be able to see the elliptic curve the way we did as a finite field. But
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to be able to visualize it as this one object, is like
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really where like the Steiner explanations
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come
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to fruition for me, where it's like, just to be able to call
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it one thing to see something as one thing is extraordinarily
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powerful.
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And that one thing that this guy probably did for nothing.
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You know, I think there'll be a world where
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people, you know, when at scale people are visualizing elliptic curves as toreses, as tori or I don't know how you pronounce it.
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It's
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a remarkable thing. And,
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know, was talking to my daughter about
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this whole situation and she said to me like, Look, I don't know if I want to spend my entire life
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validating lien proofs.
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And I said, I totally understand. I don't think you're going to have to, however,
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you may want to spend the next
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couple of years doing it.
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It's not a bad
thing.
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So like you're meeting
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this problem now, think at the perfect time. You're senior in college,
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you're going to go work for people doing research. You can be valuable to them. It's the most exciting time in mathematics ever. Yeah. It's the... Like you are at the precipice and you're not in ensconced
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in like the hierarchy of the math world. You get to go in and just break shit.
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Absolute... And you Like, this is the best time for her. Like like, there is no better time to be a senior
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with a math, like, entering the field than this moment in the entire history of humanity.
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Like Yeah. The ability to just actually raise your hand and say, I wanted
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want to spend like
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a lot of time validating Lean Proofs for somebody because I want to do it once
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or twice
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then never then I'm gonna be able to go do my research. Right. Right. I think that's totally and that's such a great point. Yeah, like you cut your teeth a little bit, learn the skill.
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There's a small corollary of,
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when my wife was getting her PhD in biochemistry.
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It was just
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like CRISPR had had been out for like a couple of years, and people were starting to do RNA sequencing and doing all of the... It wasn't just wet lab work anymore. It was the computational biology, like bioinformatics.
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Yeah. And she pivoted right into that. And it was amazing for her career. And now like it's what a lot of people are doing like in the field and like linking this stuff up. But all that to say that like, when there's major step functions like in changes in math,
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like in in whatever industry it is, you wanna lean into that and be versed and skilled in it. And this is just general career advice.
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Oh, yeah. You want you wanna you wanna be familiar with this stuff, because then you become the expert. You then be able... You're then you're able to speak about authoritatively. You then get to see the the entire world of your field differently than all of your peers, and you're gonna be able to do some amazing, incredible stuff, like, for sure. And you will have it... I mean, I do think it's probably an important skill to gain. You don't have to spend the rest of your career doing it, but you probably should do consider
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yourself an apprentice at this point and that this being a needed skill like blacksmithing at this moment.
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Yeah. Right? That see the writing on the wall, but still skate to where the puck is going. Yep. And by the way, as a math podcast, I think we're going to be able to snatch all the lean puns until you know, essentially,
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we're gonna get we're gonna be able to snatch them first. Yeah, absolutely.
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And I actually maybe another thing to drop into the notes, the stress and algorithm. So originally linear algebra multiplication thought was thought to be n cubed.
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And then the stress and algorithm was thought to kind of be the floor
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was like two point,
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like end of the 2.8.
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And then it kind of goes down a little bit, expanding
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upon that to like, 2.3755.
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And now like what's happening over the past
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couple of weeks is like, we're extending that even more. Like, we're going shades and hairs below that where at first it was like, ninety nine thousand nine ninety nine, like 80 times, but it was
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it was to the 0.9999.
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So technically, it was a fractionally smaller number, and now we're at like five nines. And all this is saying is similar to that packing the square problem that, like, there's probably some misalignment in how we're actually viewing the problem that will be to get more efficient.
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And this is,
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do you wanna talk about the Terrence Tau step before we get deep into the, elliptic curve piece specifically? Yeah, let's do that. But I'll also just, I'll just say like, I also ironically, I mean, there is a lot of money now behind getting linear algebra to compute faster. Bingo. Because little... And maybe to tease out that context,
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AI, these large language models is just a bunch of linear algebra. So if all of a sudden you can more efficiently can do the linear algebra mathematic... Like, this is like a Moore's... Not literally Moore's law, but, like, you're finding more productivity. So with the same amount of energy, you're able to do more math, which means lower cost of compute. So, like, this is
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making a run at probably some of the most significant problems, which is actually an interesting point
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of of all the papers that you would wanna publish and produce. Why would it be this one? Because now you're letting the entire world know how they could do math more efficiently where in theory,
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OpenAI could have held this to themselves and gotten a leg up on
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getting more efficient compute. But maybe that gets a little bit too complicated because the second you go to the chip
fabrication, you're kind of laying out the algorithm on the circuits. They're gonna realize, oh, shit. This happened. So they just wanna get all of the the glaze and glory up front.
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Seems that way, and it just seems like they are... They're all out to
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seems very low level. They're trying to disrupt industries and create sort of create FUD and create chaos right now. That's what it feels like. It doesn't feel like there's a high level strategy here. Yeah. Well, I mean, they're, they're trying to IPO, so they have to make it seem like they're they're making a run at literally all things, and then they vague... Like, basically,
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I think they help,
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accelerate the vague posting about there's no cryptography out there. Maybe all cryptography is k fabe. Like, they're staging pretty terrific k fabe. And so Terrence Tao is... Whether he knows it or not or likes it or not, anytime he speaks, he's part of the k fabe.
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And he's either imposing his own k fabe or
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he's just part
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of this machine's kayfabe.
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But the
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big thing was
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he posted some slide from,
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I guess one of his slides got on Twitter of this presentation he did yesterday. And just
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to summarize,
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he's
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basically making a case for why humans matter, why mathematicians matter. And he used this analogy of
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pharmaceutical
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development that like, if we knew a thing worked, but we didn't know why would you actually inject it into your bloodstream?
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It's
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just now more in the kayfabe of, I think, framing this argument.
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It's like, you know, what is it a Hegelian dialect or like where there's like, know, you're trying to you're forcing two sides, but none of them are actually good arguments.
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We're gonna have bring Eric Kason onto the podcast. He can break that down for us. We should he just he just started following me. I should... We should be Oh, hell yeah. Bring him up. We should We should definitely bring Eric Kason. We should. But, like,
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it's it's more about the... This is now, like...
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You also now have to navigate the k fave.
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I I I have a personal view that human beings matter. I don't know what Terence Tao is trying... Is doing. I understand that his world is get... Like, imagine being like...
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You know, I don't know what the analogy is for who Terrence Tau is, but maybe like there's
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a
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like you worked your whole life to become a great NBA player and all of a sudden,
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the 13 foot
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prediction that I made about quantum actually came true. And
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now you're
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dealing with it, right? So he's dealing with the fact that he was like,
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he was special. And I think the world is asking for his views, right? The world wants him to speak on these things.
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He's sort of the CEO of math right now,
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right? He's the CEO of big math.
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You know what I mean?
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So he's making this case that, yes, human beings matter. That's a case I've made here. Like, I've made the case here that, like, okay, what really good is it if a machine takes
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the shortcut just like I mentioned with Fermat's Less Theorem?
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I just think it's it's just interesting though. You also have to navigate it. That's... You have to navigate the k fabe
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while
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observing this because he's getting so much shit on Twitter. For some reason, the Twitter...
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Like the Twitter take is that fuck these mathematicians,
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they're entitled shits.
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They're lucky to do... They're lucky to make a living doing what they do anyway, and they should stop complaining. And there's like... That's like 80% true,
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you know? So
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which is all good Twitter. All good Twitter takes are like 80% true. Right.
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Right?
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So I think that's what this is what we're seeing here. That there's gonna... It's gonna look like a fight between humans
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and the robots. I feel like that's what they're they're staging here. Doctor. That's the cape maybe in stage up. But to my point, I think the actual answer is working together. Right? So his example is that like, let's say someone made a bleed proof for a drug cocktail that could cure your disease, whatever disease you had, but no person
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could explain the mechanism.
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But there's a lean proof. And this is an abstract like thought experiment, because to actually do a lean proof that proved you were able to do
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take this medicine safely would mean that you would need a lean proof for the entire human body and physio,
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the entire
anatomy and all of like chemical interactions and all the protein binding and the entire like human,
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system, like the entire like biochemical
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system of the human body, you would need lean proofs and how they all default operate. And then from there, you could
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plug a drug in and show that there won't be negative side effects. Like, that's why it's like more of a thought experiment. This isn't something that's in the reason of what we're able to do at the moment.
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But that would be wild if over the next, know, decade, we're able to formalize out the entire human like
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bio biochemical soup that we are. And then you could start actually figuring this stuff out. But the point is,
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if you had a mathematical proof, but no one could actually explain the mechanism, would you take the Right, but what's interesting, I guess about it is I mean, the fact is what we consider the standard for pharmaceuticals is are these reverse control studies.
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A lean proof is like a billion times more powerful than anything from a reverse control study. Oh, it's way more direct too.
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You know, like we, the illusion is, oh, we have these reverse control studies and therefore we understand all the side effects and all this thing, you know, yet not to get off a tangent here, but you know, something like three hundred and fifty thousand
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people die every year just from normal pharmaceutical accidents.
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Because these reverse controls, we can talk about the modeling of these things, but they have, there's a lot of model bias, you can't, you know, this is partly why there may be tyranny in the world because they want the entire world to be in the set of training data. Yeah, because when you reverse control for certain groups, you may not be capturing everybody. The
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classic one is that men are way oversampled because women with their hormonal cycles plus pregnancies,
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like pregnant women don't typically sign up for clinical trials to do stuff, right? So like the entire like, the knowledge that we have on the medical treatment of pregnant women is entirely different than a generic man.
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Because no woman is going to subject herself to a clinical trial while she's
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nursing or while she's, you know, while she's pregnant, right?
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Which was always kind of the wildest thing about like, with the COVID vaccines, Oh, it's fine if you're pregnant. I was like, hold the fuck on. Know, I know for a fact you weren't injecting pregnant women with this. Like, that would have violated every single ethical standard, so fuck you. Like, that was, like, that was one of those moments where, like, they put... Like, a half step too far where they had to be so absolutist with, like, the structure of this. They're like, it's safe for pregnant women. I'm like, you actually can't say that. And you know that's not true. Like, anyway, that's just a little nugget of a side note of a tangent within a tangent. We can't not go there with this, but,
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you know, to... I guess to piggyback your last point before we then get into the study guide is that what I have been saying for the last couple of days, and this is like the light bulb that kind of went off for me talking to Kayla about this, is that
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what we're seeing in real time is a division of labor. Yes.
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And there are probably now problems that just should be solved by machines. And it just so happens that we're dealing a division of labor with an incredibly asymmetric
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ability.
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Well, like machines have an asymmetric ability over people for certain things, and we have an asymmetric ability over them over certain things.
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And we are now we are going to be in an awkward
393
00:33:18.380 --> 00:33:23.995
process of discovering that division of labor. Know it's so funny, dude, like in Bitcoin, we talk about
394
00:33:25.675 --> 00:33:34.075
these concepts as though they're romantic, you know, like, yes, man, dude, like what it takes to discover division of labor is painful,
395
00:33:34.155 --> 00:33:34.715
awkward,
396
00:33:35.010 --> 00:33:41.169
and really crappy. And we're about to go through that in this generation now with math. Yeah.
397
00:33:42.450 --> 00:33:43.010
Exactly.
398
00:33:44.450 --> 00:33:48.290
Is cycle time. Humans haven't made their move yet, really. That's
399
00:33:48.290 --> 00:33:49.570
the thing. And so we have this
400
00:33:50.285 --> 00:33:51.725
k fave. We have this
401
00:33:52.045 --> 00:33:57.485
societal conversation. We just haven't... We really haven't seen humans make their move yet. Right.
402
00:33:57.965 --> 00:34:00.924
We have to figure out how to respond to this all. Right? So
403
00:34:01.405 --> 00:34:02.765
let's
404
00:34:02.765 --> 00:34:05.085
get into it with
405
00:34:07.700 --> 00:34:11.860
elliptic curves, why everyone's tuned in today because the extension...
406
00:34:12.020 --> 00:34:19.140
The high level just extension of this before we get into the specifics is math is... You know, OpenEye puts out hundreds of papers and lean proofs,
407
00:34:19.925 --> 00:34:21.925
know, solving different fields of mathematics
408
00:34:22.085 --> 00:34:23.045
conspicuously.
409
00:34:23.045 --> 00:34:25.285
There are no cryptography results.
410
00:34:25.365 --> 00:34:26.965
The implication
411
00:34:26.965 --> 00:34:27.765
and,
412
00:34:28.885 --> 00:34:34.700
OpenAI
has not come out to say anything either way, because I think it's a handy narrative for them to go wield, is that
413
00:34:34.940 --> 00:34:37.819
there are advancements that are happening currently in cryptography,
414
00:34:38.220 --> 00:34:41.420
and that we may be able to actually break things like elliptic curves
415
00:34:41.740 --> 00:34:43.180
that we use in Bitcoin,
416
00:34:43.260 --> 00:34:44.780
not with a quantum computer,
417
00:34:45.339 --> 00:34:48.619
but just using the foundational math and our understanding
418
00:34:48.619 --> 00:34:53.545
of the math behind elliptic curves, which we've gone into extensively in this podcast previously.
419
00:34:53.625 --> 00:34:55.625
And we have a study guide. I'd encourage you.
420
00:34:55.865 --> 00:35:05.470
Go check the episode with Riordan that we did with Riordan about this. Yeah. Talk a lot about this. Yeah. Yeah. Yeah. We did an episode with Riordan. I'd encourage you to go through the study guide and go through,
421
00:35:06.349 --> 00:35:10.670
the entire series if you wanna go deep, deep, deep into the elliptic curve stuff.
422
00:35:13.950 --> 00:35:14.510
And
423
00:35:14.925 --> 00:35:21.885
because even in... Even at the level of elliptic curves, there's elliptic curves, and there's Bitcoin's elliptic curve. Right.
424
00:35:22.365 --> 00:35:25.325
Right. And we've talked a lot about that. Right?
425
00:35:25.725 --> 00:35:26.525
Indeed.
426
00:35:26.525 --> 00:35:27.325
Indeed. Yeah.
427
00:35:27.805 --> 00:35:28.125
So
428
00:35:29.200 --> 00:35:32.400
maybe to tee up the the nature of the problem
429
00:35:33.040 --> 00:35:34.320
for those at home,
430
00:35:36.000 --> 00:35:36.960
Bitcoin
431
00:35:37.520 --> 00:35:39.360
has an equation y
432
00:35:39.360 --> 00:35:47.935
q... Y equals, x cubed plus seven. Y squared equals Sorry. Y squared equals x cubed plus seven. Yes. Correct. Sorry. Y squared equals x cubed plus seven.
433
00:35:48.335 --> 00:36:01.830
And that creates a curve. It looks kind of like a c, if you're thinking about looking on a graph plane like that. It it fans out and goes wider, but like the initial start of it looks like like a c, if you're trying to think about that, and goes across
434
00:36:02.070 --> 00:36:04.310
positive and negative, coordinates,
435
00:36:05.510 --> 00:36:06.230
you
436
00:36:06.550 --> 00:36:17.325
know, kinda mirrored across the x axis. That's what the y squared. That's sort of what the that's what the y squared means. That's right. Y squared equals something. And if that something is negative
437
00:36:18.045 --> 00:36:23.085
or positive, it'll resolve to the y squared. So that's why it's symmetric over the x
438
00:36:23.085 --> 00:36:24.540
axis. Right.
439
00:36:24.780 --> 00:36:25.740
And so
440
00:36:27.500 --> 00:36:28.220
we...
441
00:36:28.300 --> 00:36:30.700
It is not literally a continuous curve.
442
00:36:31.100 --> 00:36:33.260
It is a finite field,
443
00:36:34.540 --> 00:36:36.220
and it is a group
444
00:36:36.780 --> 00:36:37.580
of points.
445
00:36:39.005 --> 00:36:40.045
Those points
446
00:36:40.285 --> 00:36:41.405
are actually
447
00:36:41.805 --> 00:36:43.165
raw public
448
00:36:43.965 --> 00:36:45.005
keys
449
00:36:45.165 --> 00:36:49.725
that... And private keys that exist on the curve. I will... Well, just to jump in there.
450
00:36:50.340 --> 00:37:00.980
If you read a book on elliptic curves, the first thing you'll especially in Bitcoin, like elliptic curves and Bitcoin, you'll first learn of elliptic curves over the reals, which is a continuous curve.
451
00:37:02.195 --> 00:37:03.715
Over the real numbers,
452
00:37:03.795 --> 00:37:06.115
that's just you have every possible
453
00:37:06.515 --> 00:37:08.675
x value is now drawing.
454
00:37:09.075 --> 00:37:09.955
We
455
00:37:09.955 --> 00:37:14.275
like to do that in math, we like to visualize things in the reals as though they're continuous.
456
00:37:15.170 --> 00:37:18.610
And then we do it over that finite field.
457
00:37:19.010 --> 00:37:22.530
Finite field is a different number system than the reals. It's basically
458
00:37:23.250 --> 00:37:26.050
every integer up to that prime,
459
00:37:26.370 --> 00:37:28.450
up to the modulus minus one. Yeah.
460
00:37:29.545 --> 00:37:41.705
Then it's a bunch of points that people will wanna connect the lines, but they don't connect. It's just a bunch of points. We we for our monkey brains talking and reasoning about this stuff, connect the points to make a pretty little curve, but it's actually,
461
00:37:42.690 --> 00:37:44.210
you know, roughly
462
00:37:44.770 --> 00:37:47.010
two to the two fifty six dots
463
00:37:47.010 --> 00:37:48.450
that are Antinopoulos,
464
00:37:48.450 --> 00:37:50.930
the mastering Bitcoin book. I
465
00:37:51.730 --> 00:37:54.530
think it's chapter four, it does some visuals of
466
00:37:54.865 --> 00:38:03.665
what if the prime modulus they takes the prime modulus leaves is like twenty three and thirty seven. And it just shows how it starts even at those low numbers.
467
00:38:04.225 --> 00:38:06.305
The curve starts to a look
468
00:38:06.545 --> 00:38:07.825
like
469
00:38:08.530 --> 00:38:10.290
it starts to look like a form.
470
00:38:10.450 --> 00:38:11.650
Yeah. You know?
471
00:38:12.130 --> 00:38:12.690
Yeah.
472
00:38:13.330 --> 00:38:19.170
So the the general nature of how this all works is you take your private key,
473
00:38:19.650 --> 00:38:20.370
which is a number,
474
00:38:21.395 --> 00:38:22.675
and you basically
475
00:38:23.075 --> 00:38:31.315
want, you use modular arithmetic and you fold it over this curve. That's the amount of times you kind of step through the curve starting at the generator point.
476
00:38:31.714 --> 00:38:34.195
Well, there's an operation called point addition.
477
00:38:34.275 --> 00:38:35.954
Yes. That's the so and it,
478
00:38:37.070 --> 00:38:49.070
there's... When you take a point and add it to another point, it becomes another point on the
curve. It's... There's a way to visualize it, but it's not entirely intuitive. The cool thing about it not being entirely intuitive is
479
00:38:49.815 --> 00:38:51.735
it's really hard to trace,
480
00:38:52.215 --> 00:38:54.775
like, you know, if you do this point edition
481
00:38:54.775 --> 00:38:59.655
a number of times, it's kind of hard to keep track. It's hard to really visualize.
482
00:38:59.655 --> 00:39:01.335
It looks like it looks kind of random,
483
00:39:02.210 --> 00:39:03.330
even though it's not.
484
00:39:03.730 --> 00:39:07.730
But that's and that's what makes it hard. It's sort of what makes it hard to
485
00:39:08.529 --> 00:39:13.329
even to make it makes like if you had a circle or a continuous
486
00:39:13.329 --> 00:39:19.655
curve real number and you knew the generator point you can solve, you can actually solve the private key.
487
00:39:19.895 --> 00:39:22.615
Yep. But over the, so you have this
488
00:39:23.335 --> 00:39:26.295
point and you have this operation called point addition
489
00:39:27.015 --> 00:39:28.695
that has a specific definition.
490
00:39:29.780 --> 00:39:36.180
It's probably closer to like vector addition, if you're familiar, say, than adding numbers.
491
00:39:36.500 --> 00:39:36.900
Right.
492
00:39:37.940 --> 00:39:40.500
The point is you know that the closure
493
00:39:40.500 --> 00:39:47.075
tells you that adding two points keeps you on the curve, gives you Which is important. You always wanna stay within the curve, right?
494
00:39:48.195 --> 00:39:53.955
And I'm actually looking at the study guide at the moment. This is because we're kinda teeing up
495
00:39:54.515 --> 00:39:54.835
why
496
00:39:56.170 --> 00:39:57.370
this is important
497
00:39:57.770 --> 00:39:58.810
is that
498
00:40:00.090 --> 00:40:03.850
these properties basically lend itself to the fact that
499
00:40:04.090 --> 00:40:07.610
to go from a private key to a public key is trivially easy,
500
00:40:08.135 --> 00:40:10.695
but to get from that public key to work backwards
501
00:40:11.335 --> 00:40:12.135
is
502
00:40:12.454 --> 00:40:13.255
basically
503
00:40:13.335 --> 00:40:15.895
impossible as known through our
504
00:40:16.375 --> 00:40:18.295
understanding of math today.
505
00:40:18.375 --> 00:40:23.015
And this is usually described as, you know, there's more possible keys than atoms in the universe,
506
00:40:23.870 --> 00:40:29.070
and your best shot at trying to get my private key is actually just to guess all of the numbers.
507
00:40:29.470 --> 00:40:33.070
You have to just guess all of the numbers, which is not really a practical
508
00:40:33.870 --> 00:40:38.415
not really a practical exercise at all. Assuming you rolled own dice
509
00:40:39.375 --> 00:40:41.535
to get the Assuming you have good entropy.
510
00:40:41.535 --> 00:40:43.535
Right? You have to have good entropy.
511
00:40:43.615 --> 00:40:44.255
Now,
512
00:40:45.775 --> 00:40:47.775
there is one known,
513
00:40:48.975 --> 00:40:49.855
optimization.
514
00:40:49.855 --> 00:40:51.375
It's even in the study guide.
515
00:40:51.950 --> 00:40:53.230
Theorem 5.2,
516
00:40:53.230 --> 00:40:55.070
Polar's row complexity,
517
00:40:55.630 --> 00:41:00.590
running rows out... Polar's row's algorithm for the group, you're actually able to take the square root
518
00:41:00.910 --> 00:41:05.870
of the field. So if it's two to the two fifty six, you're still at two to the one twenty eight, which is still
519
00:41:06.190 --> 00:41:10.585
pretty damn good. Right? Two to the one twenty eight. So just incidentally, like,
520
00:41:10.905 --> 00:41:20.025
I told you about the Neil Koblitz book. Yeah. And we haven't really gotten to the ETH KFADE because Neil Koblitz actually works for the Ethereum Foundation as a No shit. But
521
00:41:21.810 --> 00:41:30.450
But his book is so good. And the first chapter, the first section's big O notation. Then the next thing he gets into is Paul Droe and the algorithms that reduce,
522
00:41:31.010 --> 00:41:31.810
that do
523
00:41:32.050 --> 00:41:33.170
reduce the
524
00:41:33.650 --> 00:41:35.730
solution set, solution space.
525
00:41:36.210 --> 00:41:36.370
Yeah.
526
00:41:37.355 --> 00:41:45.275
And so that's kind of like what we know today is like the things you can do in general and do It's also known as Shanks, I think, Shanks algorithm. But
527
00:41:46.395 --> 00:41:47.275
it
528
00:41:47.275 --> 00:41:48.795
essentially square roots
529
00:41:49.434 --> 00:41:50.155
the set.
530
00:41:50.395 --> 00:41:51.740
Yeah. Yeah.
531
00:41:51.980 --> 00:41:53.260
Yeah. So now
532
00:41:53.579 --> 00:41:54.380
I
533
00:41:56.140 --> 00:42:03.740
try to take a little bit of time. So it's two to one twenty eight. Sorry. So it's basically not two to the two fifty six, it's essentially two to the one twenty eight is really
534
00:42:04.305 --> 00:42:10.065
the defense line. Yeah. That's the defense line, which is cryptographically secure. Because remember each
535
00:42:10.785 --> 00:42:11.665
each
536
00:42:11.665 --> 00:42:15.585
number to go from two to the one twenty seven to go to the two to the one twenty eight
537
00:42:16.305 --> 00:42:17.265
is not
538
00:42:17.984 --> 00:42:19.665
small. It's a doubling.
539
00:42:20.520 --> 00:42:21.160
Yes.
540
00:42:21.560 --> 00:42:24.440
Right? We're talking about base two and increasing the exponent.
541
00:42:24.680 --> 00:42:28.120
That's why, maybe to make it a little topical for everyone,
542
00:42:30.040 --> 00:42:33.480
the issue with the cold card hack with the MK three, it was two to the 32,
543
00:42:33.875 --> 00:42:41.475
which is trivial for one computer to brute force the entire known space of numbers. Yep. The MK four was at two to the 70, which can be done,
544
00:42:42.035 --> 00:42:49.970
but that is to go from 32 to 70 makes it so that, like, you're gonna have to spend a lot of money to get there. Right. Is it fair to assume
545
00:42:50.450 --> 00:42:51.810
that that's
546
00:42:51.970 --> 00:42:53.410
probably still grinding?
547
00:42:54.130 --> 00:42:54.690
Maybe.
548
00:42:54.930 --> 00:43:00.369
It's also like I didn't do the final math on two to the 70 versus it may have been like two to the 56
549
00:43:00.369 --> 00:43:02.050
versus two to the 67.
550
00:43:02.050 --> 00:43:04.265
Like, there was some fuzz space in there.
551
00:43:05.545 --> 00:43:06.585
The hope
552
00:43:07.065 --> 00:43:10.265
the hope is that with months of notice,
553
00:43:12.424 --> 00:43:13.625
people move off,
554
00:43:14.280 --> 00:43:18.600
and then the prize gets smaller which then resets the computation
555
00:43:18.600 --> 00:43:32.095
relevant for is this even worth going after anymore. If I'm the attacker, I'm gonna just keep doing it because I think there'll be one whale that I can get. Maybe. Yeah. But you've... Then then it's a calculated risk. Right? Whereas if you were able to keep this private somehow,
556
00:43:33.055 --> 00:43:36.495
you would have, you know, probably won for the whole whole gambit.
557
00:43:36.975 --> 00:43:42.335
I might have I might have been looking at... I might have been looking to see really how effective
558
00:43:42.770 --> 00:43:43.410
the
559
00:43:45.170 --> 00:43:48.210
public outcry is and how responsive The it would
560
00:43:48.849 --> 00:43:53.650
other thing too is to procure that level of compute is, it's not impossible, but you're
561
00:43:53.650 --> 00:43:57.250
not gonna log onto AWS and start grinding it out because
562
00:43:58.935 --> 00:44:00.455
you know, like it's
563
00:44:00.855 --> 00:44:08.615
gonna be pretty obvious, right? So not impossible, but like it's just something to keep in mind. So by the way, so just, I mean, how encouraging is that
564
00:44:08.935 --> 00:44:13.495
that two to the 70... It was a two to the seventieth? Is that... What was the MK four?
565
00:44:14.880 --> 00:44:29.295
I think m k four or five and q are all, like, two to the 70 because it did a 32 bit recede in the we live in now, we know two to the 70 is a far cry from... It's a far cry from two to the one twenty eighth. Yes. And yet it's still it's still really
566
00:44:29.455 --> 00:44:38.495
a unlikely and difficult to get the resources to do that attack. Casually. Yeah. That's like it's it's not quite nation state. Like nation state is like two to the 90,
567
00:44:38.815 --> 00:44:39.215
but like,
568
00:44:40.410 --> 00:44:47.050
you know, it's it's on it's on... Yeah. Like, of what they could... And reasonably on opportunity cost point their problem there versus elsewhere.
569
00:44:47.290 --> 00:44:57.965
But, like, once... But now, like, you're going from two to the 90, which is, like, nation state level grinding to, like, two to the one twenty eight, you're like, oh, this is more compute than the entire available compute in Earth,
570
00:44:58.125 --> 00:45:09.080
you know, with many, many orders of magnitude in between padding you. Again, I'm gonna say something really
stupid, but, like, it's just... Again, a nation state might have... Like, they might have just imprisoned
571
00:45:09.160 --> 00:45:19.240
the guy that ran Silk Road, and they may know that... They they know that he's on an MK four, and they know they have him for, like, eleven years, and they may just decide to do it. Maybe.
572
00:45:19.525 --> 00:45:25.845
Like that's... But it's still getting so specific that it's not like you can't... You can think like generally
573
00:45:26.244 --> 00:45:28.165
these things aren't gonna happen today.
574
00:45:28.405 --> 00:45:32.565
Yeah. A year from now, things may be very different. I'm just thinking like the fact that
575
00:45:32.820 --> 00:45:34.100
even subpar,
576
00:45:34.420 --> 00:45:37.540
even you know, you just can't be so subpar.
577
00:45:37.620 --> 00:45:38.020
Yeah.
578
00:45:39.780 --> 00:45:41.940
I'm gonna do something I don't
579
00:45:42.100 --> 00:45:44.500
think I've ever done before. I'm going to
580
00:45:45.075 --> 00:45:48.115
because I fed basically the study guide into
581
00:45:48.195 --> 00:45:49.795
all of the elliptic curve,
582
00:45:50.595 --> 00:45:59.875
math and the open theorems and proofs. And I'm gonna just read this to you cold. Love it. And we're gonna try and take this as a conversation because I had... I actually went and got an obliterated model
583
00:46:00.350 --> 00:46:07.950
talking about it. I'm trying to crack all the Bitcoin. Like, here's all of the data points we have. Like, help me walk through what are the things I should go attack. Right?
584
00:46:08.350 --> 00:46:16.155
And then the reason why I'm doing this is because I wanna actually have a grounded conversation in, like, one, attackers already do this. But, like, secondly,
585
00:46:18.075 --> 00:46:28.955
I wanna have an actual conversation around the math that needs to break for this elliptic curve stuff to be relevant rather than it'd be vague posting and and, like, hand waving, and I tie it into the study guide to talk about the parts that specifically matter. So
586
00:46:30.460 --> 00:46:31.660
section 5.6
587
00:46:31.660 --> 00:46:32.940
of the study guide
588
00:46:33.500 --> 00:46:49.385
has a little thing called the bottom line. You actually have a whole section here about the discrete log problem, which is basically the asymmetry of advancing forward to go from a pub... Private key to a public key versus the difficulty of going backwards from a public key to find that private key is the discrete log problem. That is the big universe of
589
00:46:49.704 --> 00:46:50.984
the mathematical...
590
00:46:50.984 --> 00:46:54.425
Like, that is Atlas holding up the security of
591
00:46:55.065 --> 00:46:59.240
elliptic curves. That's the hardness. That's where the hardness lives. Absolutely.
592
00:46:59.720 --> 00:47:07.880
And so you can go to section 5.6 of the study guide if you wanna go through that there, but I'm gonna just jump off from here. And so from the guide,
593
00:47:08.040 --> 00:47:10.440
we know that every signature verification
594
00:47:10.440 --> 00:47:12.680
when I provide a signature, it's actually
595
00:47:13.135 --> 00:47:14.735
a linear algebra problem.
596
00:47:14.975 --> 00:47:31.480
Right? You're just doing a quick check of the signature versus the public key and seeing that it's there. It's quick to verify. That's why it's so great. Because I can have a secret. You don't know that secret, but you can quickly verify that you know that I know the secret. Like, that's the whole under... When I send you Bitcoin, I don't have to give you my private key.
597
00:47:31.720 --> 00:47:39.640
I just give you a signature tied to that private key, and you can quickly mathematically verify that I have the private key. That is what checking a signature is in Bitcoin.
598
00:47:40.360 --> 00:47:41.000
Now
599
00:47:43.135 --> 00:47:44.495
in 2020,
600
00:47:45.215 --> 00:47:56.335
a team of researchers at... Like, we're starting to program and ask a question. It was like, what if the discrete lock problem itself was a linear algebra problem that you could quickly backwards verify? Right? Could you, in theory, walk backwards and instantly get that key?
601
00:47:57.295 --> 00:47:58.335
In plain words,
602
00:47:59.030 --> 00:48:04.470
you take your public point and the generator, and you build a big matrix out of many random combinations.
603
00:48:05.349 --> 00:48:07.109
And now every determinant
604
00:48:07.109 --> 00:48:16.765
of every square sub block of that matrix is called a minor. Yeah. And by the way, just to pause. But this is Yeah, please. So if you go back to when we said looking at the elliptic curve
605
00:48:17.085 --> 00:48:18.365
over the reals,
606
00:48:18.365 --> 00:48:26.605
and I was saying how you could just... If you know... Basically, it's an algebra problem now where if you know all but one thing, you can solve for the one thing.
607
00:48:28.349 --> 00:48:31.070
Right? If you know the generator point, you
608
00:48:31.950 --> 00:48:33.869
know the public key and say,
609
00:48:34.109 --> 00:48:45.535
you know, basically when you say solving using linear algebra, the equation is simple. It's Ax equals basically Ax equals b, where A is your big, big matrix,
610
00:48:45.615 --> 00:48:52.415
X is a vector that you're solving for and B is the answer. It's a vector. That's the answer.
611
00:48:52.895 --> 00:48:54.175
And so all
612
00:48:54.175 --> 00:48:57.375
the linear algebra problems is Ax equals b. It sounds really simple.
613
00:48:58.930 --> 00:49:02.850
Again, this is like the question that this is now the question is,
614
00:49:03.570 --> 00:49:06.770
you know, in a linear system, it's actually really easy to solve
615
00:49:07.250 --> 00:49:11.330
for x. So like one of the most famous solutions is least squares,
616
00:49:11.785 --> 00:49:12.745
Where
617
00:49:12.745 --> 00:49:16.905
it's like x prime x inverse x prime b something.
618
00:49:18.025 --> 00:49:18.585
Sorry,
619
00:49:19.465 --> 00:49:23.305
a prime a inverse a prime b that would equals x.
620
00:49:23.829 --> 00:49:44.515
Right. You take the inverse. I'm gonna fuck that up. Like anyway, By like taking the inverse, yeah. There are certain systems that are really known and easy and already have like analytical solutions. And so what Rob is saying right now is that now they're trying to see if that can be done on an elliptic curve of a finite field. Yeah. And so what they're doing is is they're saying you take your public point in the generator and you build a big matrix,
621
00:49:44.675 --> 00:49:47.315
right, out of bunch of these random combinations.
622
00:49:47.875 --> 00:49:51.955
And what you do is you take the determinant of every one of these sub blocks,
623
00:49:52.680 --> 00:49:56.440
and that sub block is called a miner. And they
624
00:49:57.000 --> 00:50:03.560
prove that here o r. M I n o r. M I n o r. Yeah. And if you were to find one of these miners,
625
00:50:04.615 --> 00:50:07.255
if you can find one that has a determinant...
626
00:50:07.655 --> 00:50:11.015
If you find one with zero, a block where the determinant vanishes,
627
00:50:11.255 --> 00:50:13.575
meaning there's some dependence.
628
00:50:13.575 --> 00:50:17.015
We'll we'll get... Well, I'll I'll go to this in a second. There's some dependence of this matrix.
629
00:50:17.680 --> 00:50:18.800
There is a,
630
00:50:19.520 --> 00:50:24.160
and it's zero. There's a coincidence among the points that solves the discrete log.
631
00:50:24.480 --> 00:50:30.400
That's because the determinant is zero, you no longer have an inverse. And I think that it's called degenerate.
632
00:50:30.825 --> 00:50:31.625
Yeah.
633
00:50:31.625 --> 00:50:42.265
And so this is from my linear algebra days. I got a... I mean, I got a bachelor's in math over a decade ago. But if you view a matrix, right, like, can just think about maybe a two by two matrix with x and y coordinates.
634
00:50:43.809 --> 00:50:45.010
The determinant...
635
00:50:45.170 --> 00:50:47.810
The linear dependence piece is really important because,
636
00:50:49.170 --> 00:51:02.815
it means that you can actually express that matrix in a simpler form. Ah, we talked about this last week, by the way. We talked about linear independence last week. Yeah. So you just jarred me to do is imagine a matrix with two vectors. One is one, two,
637
00:51:03.455 --> 00:51:14.160
and then the other below it is two, four. Mhmm. This is the same... These are clearly the same line. Right? So The same line. Exactly. And if I just did the determinant in my head,
638
00:51:15.120 --> 00:51:23.840
it's zero. It is zero. Yeah. Because you're taking the same vector just on different, point. You're taking up... If you have two lines and you're just taking... The lines overlap.
639
00:51:24.105 --> 00:51:26.985
So it shows you you lack linear independence,
640
00:51:27.145 --> 00:51:33.625
also means you can't Within that matrix. Means you can't have an inverse. It's a... Yeah. All of these... This is... It gives you all of this information
641
00:51:33.705 --> 00:51:35.065
that kinda
642
00:51:35.705 --> 00:51:37.225
means something now. Right.
643
00:51:38.040 --> 00:51:44.680
And so not all is lost. Right? Because we're talking about a two by two matrix. You're gonna be taking something that's gonna be
644
00:51:45.400 --> 00:51:46.440
way larger,
645
00:51:46.520 --> 00:51:50.360
way, way larger to do all of the combinations and the pieces. Right?
646
00:51:50.600 --> 00:51:55.185
And the idea though is that this could be a way that you could shortcut your way through
647
00:51:56.065 --> 00:51:57.665
the discrete log problem
648
00:51:57.744 --> 00:52:03.105
because you're basically taking a subset of the randomness in the universe and you're finding a way to accelerate
649
00:52:03.345 --> 00:52:04.385
computationally.
650
00:52:04.464 --> 00:52:12.010
How do you maybe find a key that could work And if you don't have perfect entropy, you may open the door for this. That's that's really Always.
651
00:52:12.170 --> 00:52:12.810
Always.
652
00:52:13.130 --> 00:52:39.400
That that... That's really what it comes down to. Like, perfect entropy gives you per... Gives you linear independence in the highest amount of dimensions, I. E. The two fifty six minuteus two thirty two. If someone wants to go do... Take some homework away from this podcast, you could take the subset of the entropy that was generated by the Colt Carton show it didn't have linear independence and how quickly you could collapse back down on this probably. Like, go ask your clanker that question. I I would say recommend that to people. Yeah. Yeah. Yeah. So this
653
00:52:39.560 --> 00:52:48.200
field, like... So, like, just a... This is the why do you care? Because if a polynomial if the polynomial version is true and the set is cheap to find,
654
00:52:49.765 --> 00:52:50.965
then this...
655
00:52:51.605 --> 00:52:57.445
The security ends. There... It's not that it reduces. This is a a one shot, so to speak, destruction
656
00:52:57.445 --> 00:52:59.605
of elliptic curves as we know it.
657
00:53:00.244 --> 00:53:10.569
Yep. The door is open whether you... Whether anyone realizes it or not, the door is open at that point. Yeah. So they solved some toy examples using a space of two to the 50 back in 2021.
658
00:53:10.569 --> 00:53:15.130
So if your elliptic curve was two to the 50, you could use this method to break it.
659
00:53:15.369 --> 00:53:22.005
Now you're still protected because, again, the universe between two to the fifty and two to the one twenty eight, two fifty six, whatever,
660
00:53:22.244 --> 00:53:24.165
is massively, massively
661
00:53:24.244 --> 00:53:25.045
larger,
662
00:53:26.005 --> 00:53:27.204
unfathomably
663
00:53:27.204 --> 00:53:28.005
larger,
664
00:53:28.165 --> 00:53:29.845
right, in the ability to do this.
665
00:53:30.244 --> 00:53:31.285
In August
666
00:53:31.285 -->
00:53:32.085
2026,
667
00:53:32.484 --> 00:53:33.605
right, so
668
00:53:33.925 --> 00:53:34.645
two months ago,
669
00:53:35.300 --> 00:53:39.540
same researcher published a reality check, and his new search algorithm
670
00:53:39.540 --> 00:53:45.860
is polynomial, but only for a fixed parameter. Enforcing that parameter to make success likely costs more than it saves,
671
00:53:46.340 --> 00:54:04.290
which is the saving grace. To apply this algorithm to try and crack it is actually less efficient than just brute forcing all the numbers. Right? You just... You you go back to square one. You're back to, yeah, there is a hypothetical way you could solve this, but at the larger scales that we're talking about, you're actually just way better off just going to the brute force method. Method. So that's kinda protected. But,
672
00:54:04.770 --> 00:54:06.370
the conjecture sits there,
673
00:54:07.250 --> 00:54:08.450
and it's something that...
674
00:54:09.330 --> 00:54:19.035
As a precisely stated problem, if you were able to prove it that it's not polynomial, that it's linear, that you could actually collapse the space down, that you would be able to basically break elliptic curves.
675
00:54:21.675 --> 00:54:29.595
The... This is the one that if you wanted to go grind lean proofs to see if you can find some marginal improvement, this would be the area you'd go to, like, for the most straightforward one.
676
00:54:31.050 --> 00:54:31.690
And,
677
00:54:31.850 --> 00:54:44.250
you know, so that's, like, an example. Right? And the reason I'm talking about this is because rather than being like this really... Because I kept, like, I kept asking this question. Like, everyone's just, like, hand waving math is broken, so cryptography is gonna break. I was like, can you at least point me to
678
00:54:44.570 --> 00:54:46.170
the thing that's gonna break?
679
00:54:47.195 --> 00:54:58.155
Because you... Like, to even just say the discrete log problem is gonna break is actually insufficient detail. That's just saying that, like, cryptography will break. You're just repeating yourself. This isn't a hypothetical theorem that could, in theory,
680
00:54:58.715 --> 00:55:04.530
if you found a lean proof that found it to be linear, that you would be able to break the whole thing. It's the same extrapolation
681
00:55:05.010 --> 00:55:18.775
that, like, same low level, low thinking extrapolation that is just more like there's gonna be super intelligence. This... You know what I mean? It's just like that there's gonna be some state change from a to b. So they're
682
00:55:19.255 --> 00:55:27.095
not looking at like, Oh, I know exactly how they're gonna break cryptography. It's just, Oh, we're gonna have a state change where it's gonna be
683
00:55:27.735 --> 00:55:31.095
more intelligent in a way we can't even comprehend. And obviously,
684
00:55:31.095 --> 00:55:34.090
it will break. Obviously, that will break all of our Yeah. Powder.
685
00:55:34.490 --> 00:55:35.210
Yeah.
686
00:55:35.290 --> 00:55:36.330
There's
687
00:55:36.330 --> 00:55:41.370
actually a little bit on Shoop's theorem, as we mentioned earlier in this podcast with
688
00:55:43.210 --> 00:55:43.930
Polar Dzrow.
689
00:55:44.724 --> 00:55:48.005
And the very brief one of that is that
690
00:55:48.724 --> 00:55:52.325
it's not actually looking at the numbers inside. Could you, in theory,
691
00:55:53.125 --> 00:55:56.325
do curve points leak structure to an attacker who reads them?
692
00:55:56.980 --> 00:55:59.860
The starting point right now is no, but
693
00:56:00.100 --> 00:56:05.620
in theory, you could start grinding away at that problem with formal proofs to be able to
694
00:56:05.940 --> 00:56:06.740
break things down.
695
00:56:09.665 --> 00:56:14.465
And then one other... I mean, just kinda thinking if it was a menu jump in at any point.
696
00:56:14.785 --> 00:56:15.425
We
697
00:56:15.585 --> 00:56:17.585
we were just talking about coblets.
698
00:56:17.585 --> 00:56:18.465
You know? Mhmm.
699
00:56:19.105 --> 00:56:21.665
Bitcoin uses a coblets curve, and that's because,
700
00:56:23.339 --> 00:56:27.660
you know, we have y squared equals x cubed plus seven.
701
00:56:28.140 --> 00:56:29.740
In theory, there is a
702
00:56:30.779 --> 00:56:39.355
x squared value, but the constant is zero, so it just disappears, and that's the last one more. There's also an x value. There's also an x value. Yeah. If in the ax
703
00:56:39.355 --> 00:56:42.875
cubed plus bx squared plus cx plus d,
704
00:56:43.915 --> 00:56:47.995
in the Bitcoin's elliptic curve, the coefficients b and c are zero.
705
00:56:48.555 --> 00:56:51.610
Yeah. A is one and D is seven.
706
00:56:52.250 --> 00:56:54.330
Yeah. Right? And so it
707
00:56:54.570 --> 00:56:56.570
was also known as the wire stress
708
00:56:56.810 --> 00:56:57.530
form
709
00:56:57.770 --> 00:56:59.850
and this was done intentionally
710
00:57:00.570 --> 00:57:02.330
by Satoshi
711
00:57:03.610 --> 00:57:04.330
for speed.
712
00:57:05.535 --> 00:57:06.335
Yeah.
713
00:57:06.335 --> 00:57:08.095
Right? Yes. Correct.
714
00:57:08.575 --> 00:57:09.295
And
715
00:57:12.734 --> 00:57:14.494
I think there are a lot of idiosyncratic
716
00:57:14.494 --> 00:57:17.135
things that Satoshi did that probably will
717
00:57:17.214 --> 00:57:18.895
keep Bitcoin's
718
00:57:19.380 --> 00:57:20.580
elliptic curve
719
00:57:21.380 --> 00:57:22.340
ahead of
720
00:57:22.980 --> 00:57:23.619
the
721
00:57:24.420 --> 00:57:26.340
other people that the bear is chasing.
722
00:57:26.579 --> 00:57:27.300
Mhmm.
723
00:57:27.859 --> 00:57:36.315
Right? Like the resistance to certain NIST standards, the resistance to certain prime numbers that we know already have been already have been compromised.
724
00:57:36.315 --> 00:57:37.195
Right.
725
00:57:37.675 --> 00:57:41.515
Right. We did a lot of talk about that, Satoshi picking this curve in particular.
726
00:57:42.475 --> 00:57:44.235
That was not a
NIST certified
727
00:57:44.555 --> 00:57:46.155
curve. It wasn't, you know,
728
00:57:46.990 --> 00:58:06.315
Well, sorry. NIST cert... But it wasn't one that was really used anywhere. And the reason why Satoshi picked it was because there were no weird constants to explain away, which is typically where backdoors come in. But it's important to talk about this because the head... We know what's gonna happen. I... It may happen this year where the headline is going to be elliptic curve cryptography has been broken.
729
00:58:06.635 --> 00:58:10.635
And they're gonna break some rinky dink curve that isn't used in Bitcoin.
730
00:58:11.115 --> 00:58:21.060
Yeah. Or Is that your theory? Yeah. My theory is it... Or they don't. It's just they're gonna be able to... Anytime... If anyone says elliptic curve theory... Elliptic curve cryptography has been broken,
731
00:58:21.460 --> 00:58:23.620
it's going to be chaos
732
00:58:23.700 --> 00:58:24.740
in our world.
733
00:58:24.980 --> 00:58:27.060
Of course. Right? And this is like...
734
00:58:27.855 --> 00:58:31.055
I hate to be a broken record, but this is why we do this podcast.
735
00:58:31.215 --> 00:58:36.255
Yeah. Is so that at the very least, we're not in chaos. We're like asking
736
00:58:36.415 --> 00:58:37.935
other questions like,
737
00:58:39.055 --> 00:58:40.415
Oh, well, you know,
738
00:58:41.870 --> 00:58:42.990
was that curve?
739
00:58:43.150 --> 00:58:47.870
Right? I mean, because it's, you know, what we talk about here is not all elliptic curves are equal.
740
00:58:48.270 --> 00:58:52.430
And a lot of what protects us is not at the level of what you would say is an elliptic curve.
741
00:58:53.645 --> 00:58:58.845
Right. It's the very large prime numbers. It's underneath that level. The specific prime number that...
742
00:58:59.405 --> 00:59:08.840
Right. I wanna... There's a tweet thread that I'm gonna... When I... Because I'm just closing out the rest of these, like, possible areas that are open at the moment. But Yehuda,
743
00:59:09.240 --> 00:59:16.360
Lindell, the head cryptographer at Coinbase, one the leading cryptographers in the world talks exactly about this, that the nature of elliptic curves
744
00:59:16.760 --> 00:59:18.520
and the strength of them don't come from
745
00:59:19.164 --> 00:59:25.645
the same area of math that these machines are kinda finding more optimal algorithms. Maybe I'll just jump into it briefly to talk about it now.
746
00:59:25.964 --> 00:59:28.125
He did a really good Twitter, thread about We
747
00:59:29.484 --> 00:59:31.165
we rely on fundamental
748
00:59:32.125 --> 00:59:33.005
hardness.
749
00:59:33.005 --> 00:59:34.605
You you cut out for a second. Are back?
750
00:59:35.970 --> 00:59:40.290
You're back? Cool. You're back now. Sorry. You you were breaking up for a second. No. You're good.
751
00:59:42.050 --> 00:59:45.890
That... Basically, the fact that AI... I'm gonna read his thread verbatim.
752
00:59:46.050 --> 00:59:58.265
I wasn't gonna comment on this because it's a really bad take, this whole bunker mode, like, general thud. But since it's taken off, he feels the need to. To my understanding, there's no evidence whatsoever pointed to a break of decades old hardness assumptions like elliptic curve cryptography.
753
00:59:58.345 --> 01:00:00.185
The fact that AI can prove theorems
754
01:00:00.345 --> 01:00:08.580
and and that have been hard does not indicate in any way that problems are assumed to be hard or not hard. Our assumptions on the hard problems are not based merely on human fallibility,
755
01:00:08.580 --> 01:00:11.540
but on the belief that inherent hardness exists.
756
01:00:12.180 --> 01:00:16.180
Of course, we cannot prove that elliptic curve discrete log is hard.
757
01:00:16.500 --> 01:00:20.455
Since we haven't been able to prove p does not equal NP,
758
01:00:20.455 --> 01:00:21.735
we'll get to that in a minute,
759
01:00:22.535 --> 01:00:29.095
but throwing out that AI is doing amazing math, so elliptic curve hardness must be in danger has no logical basis whatsoever.
760
01:00:29.175 --> 01:00:29.975
Furthermore,
761
01:00:30.215 --> 01:00:31.255
it would be really...
762
01:00:32.619 --> 01:00:54.455
If it really were to be broken, the ramifications to our digital world, including traditional financial industry, would be immense. Once I can break elliptic curve cryptography, I can generate fake public key infrastructure certificates and impersonate bank websites. Worse, I can generate malicious banking apps and even operating systems and sign them and push them to people's phones and computers and completely take them over. This is the fear mongering since there's zero evidence to back that this capability exists.
763
01:00:54.775 --> 01:00:57.335
And there's zero evidence that elliptic curve hardness
764
01:00:57.415 --> 01:01:00.535
is more vulnerable than hash function hardness. In fact, historically,
765
01:01:00.840 --> 01:01:06.360
hash functions have been broken more than elliptic curves. So this is based on conjecture rather than any evidence.
766
01:01:06.520 --> 01:01:18.065
In conclusion, making such statements without evidence is the opposite of responsible behavior. It is the very definition of FUD, fear, uncertainty, and doubt. It cannot be proven wrong, but then there's no evidence whatsoever of it being true.
767
01:01:18.625 --> 01:01:21.665
And that's just trying to talk about the nature of these problems.
768
01:01:22.625 --> 01:01:35.530
It's just immensely different. So I think that... I I quote tweeted that talking about it. Like, it is absolutely kind of the big, like, walking away piece we should talk about here to... Do you have anything to add to that? Compliments to the chef. You're on mute.
769
01:01:35.850 --> 01:01:40.570
There you go. Oh, there you are. You're you're just delayed. Okay. We'll we'll we'll... You got like a...
770
01:01:40.810 --> 01:01:43.484
You're in the... Now you're back. Basically
771
01:01:43.484 --> 01:01:48.285
compliments to the chef. I gave some applause. I mean, that's a really great, it's a terrific rant.
772
01:01:48.765 --> 01:01:50.045
Excellent. Yeah, So
773
01:01:51.805 --> 01:01:56.444
we're just to tie this off. I wish it was from a place that people respected
774
01:01:56.444 --> 01:01:57.244
more, unfortunately.
775
01:01:58.170 --> 01:01:59.050
This
776
01:02:00.569 --> 01:02:02.650
is like, again, why we do this. You
777
01:02:03.450 --> 01:02:04.730
got to see the message,
778
01:02:05.210 --> 01:02:06.330
not the messenger. Absolutely.
779
01:02:06.730 --> 01:02:14.825
Absolutely. Right? Not that I don't even know this person. I'm just saying people. Oh, he's he's a world round cryptographer. He's the head of cryptography at Coinbase. Like, he
780
01:02:15.705 --> 01:02:24.105
he's not doing this for engagement. You know what I mean? Totally. It seems like he's on the same mission we are. He's like, let's let's let's have some freaking sense here. Absolutely. Yeah.
781
01:02:24.940 --> 01:02:27.020
So to tie it off with cobblets curves.
782
01:02:27.340 --> 01:02:37.260
In theory, we have this increased efficiency with the computation, and it technically gives the attacker a small discount, but nothing that is relative to the benefit everyone who's honestly using it gets.
783
01:02:37.935 --> 01:02:38.975
In theory,
784
01:02:39.535 --> 01:02:40.095
basically,
785
01:02:42.015 --> 01:02:51.455
could this be degraded as a Koblet's curve in a way that could result in some issues? In 2026, a lean formalization proof stress tested one combination of the symmetry
786
01:02:51.615 --> 01:02:53.060
around this with,
787
01:02:53.460 --> 01:03:03.220
Samed's polynomials and found only the trivial symmetry survives, so a bounded negative result. Basically, it was a lean proof proving that this is not a path to be able to break it. But in theory,
788
01:03:03.460 --> 01:03:06.180
that could be a path you could try and go for from a different approach.
789
01:03:08.305 --> 01:03:09.745
Another one here,
790
01:03:11.745 --> 01:03:12.385
so
791
01:03:13.425 --> 01:03:18.545
in chapter sixes through seven, we start talking about elliptic curves over the reels and the smooth loop picture.
792
01:03:18.705 --> 01:03:21.585
And to say now you modulo
793
01:03:20.970 --> 01:03:33.290
P the prime around it, which is the two to the two fifty six minus two to the 32 minus nine seventy seven, right? That's the prime number that we use the base all of our math around in the Oh, let's call it big P. Big P, that's right.
794
01:03:34.845 --> 01:03:36.285
So we talked about this.
795
01:03:37.565 --> 01:03:39.005
Here's an attack idea.
796
01:03:40.125 --> 01:03:40.765
The
797
01:03:42.045 --> 01:04:03.775
guide basically teaches it backwards. What if we could take a scatterplot problem and lift it back up over the smooth curves, solve it there, where we have calculus, geometry, and all of our existing mathematical tools, then push the answer back down to mod p. Why doesn't this obviously work? Because when you lift, the numbers grow. There's a height function. Think of it as an altitude of the point. And the classical theorem says the altitude you need blows up exponentially.
798
01:04:03.775 --> 01:04:12.575
So you're basically trying to walk backwards across the curve, but every time you take a try and take a step back, the competent metrics get bigger and bigger and bigger. Like that is like the inherent hardness of this problem.
799
01:04:13.935 --> 01:04:14.255
So
800
01:04:15.039 --> 01:04:17.920
in theory, you could actually maybe find,
801
01:04:18.799 --> 01:04:25.119
some weakness, not like a total break, but like a weakness. The bounds aren't tight in every regime. In twenty twenty five,
802
01:04:26.079 --> 01:04:44.545
some of the work people are doing in quantum for completely different reasons show that high altitude versions of this exact curve are arithmetically rich, and there are lifts and twists with huge amounts of structure. Nobody has connected that richness richness to a classical attack, but nobody has proven it can't be connected. So it's kind of like an open problem. So there's a low probability high payoff
803
01:04:45.640 --> 01:04:49.240
that the attacker route we talk about in our study guide for doing all this.
804
01:04:49.880 --> 01:04:55.640
Basically could try and collapse it back, but it's an open question. It hasn't been proven positively or
805
01:04:56.280 --> 01:04:56.920
negatively
806
01:04:57.444 --> 01:05:10.484
in either way. But it... This is kind of talking about Shor's algorithm. We talk about the ability to be able to walk backwards on this. It requires a quantum computer. Like, this is Shor's... Like, it's an algorithm that if you had a quantum computer, you can, in theory, walk backwards
807
01:05:10.960 --> 01:05:27.485
across many points simultaneously to be able to collapse and get back to the original key. This is basically the bucket of the quantum attack as a thing. Talked about with Reardon, you know, that it's it's not a math prob... Just because it's not a math problem doesn't mean it's solvable. It's... So it's an engineering problem.
808
01:05:28.125 --> 01:05:30.525
Yeah. It's an engineering and physics problem
809
01:05:31.085 --> 01:05:36.925
that, okay, they know them. The math is solved. Great. That doesn't really mean that they're any closer
810
01:05:38.845 --> 01:05:41.005
to launching the attack because
811
01:05:41.460 --> 01:05:44.420
you know, there's a lot of math problems that require physical
812
01:05:44.500 --> 01:05:49.140
and engineering solutions that Mhmm. You know, that's really the trick, isn't it?
813
01:05:50.820 --> 01:05:51.540
Yes.
814
01:05:52.339 --> 01:05:55.060
And so the last bucket,
815
01:05:55.460 --> 01:05:56.740
which I briefly mentioned earlier,
816
01:05:57.494 --> 01:06:01.895
basically distills down to p equals NP, p does not equal NP.
817
01:06:02.055 -->
01:06:02.695
So
818
01:06:03.974 --> 01:06:06.295
this is, like, the most foundational
819
01:06:07.095 --> 01:06:07.895
problem
820
01:06:08.135 --> 01:06:15.320
in math. There was... So, like, there were, like, seven, like big millennial problems one of which was Naver Stokes.
821
01:06:15.640 --> 01:06:18.680
Yeah. And this this is also one of these fundamentally
822
01:06:19.000 --> 01:06:29.365
fundamental problems that there's like infinite funding to try to get somebody to try to solve. Yeah. And so in a sentence, p equals n p. When everyone ever says that in plain English, what they're talking about is,
823
01:06:30.485 --> 01:06:35.445
is finding an answer ever truly harder than checking one? Because remember,
824
01:06:36.085 --> 01:06:39.845
you get to check this stuff when you do signatures. I can verify these checks.
825
01:06:40.460 --> 01:06:44.300
I can quickly take a private key and quickly get to a public key and and check
826
01:06:44.460 --> 01:06:45.740
the the math.
827
01:06:46.619 --> 01:06:48.700
Can we get... There is no...
828
01:06:49.099 --> 01:06:50.940
And this is the reason why
829
01:06:51.819 --> 01:07:02.875
you can't prove elliptic curves are secure is because of p equals NP, and we can't... And related to that, the discrete log problem, you can't prove a negative because you'd have to conclusively prove
830
01:07:03.115 --> 01:07:13.720
all possible aug... Algorithms are insufficient. Right? So it's a it's a fundamental, like, ep... Epistemic problem of, like, the knowledge gathering. You cannot prove a negative
831
01:07:13.880 --> 01:07:14.920
in this sense.
832
01:07:16.680 --> 01:07:17.640
And so
833
01:07:18.920 --> 01:07:34.775
taking it off just from right here here, you know, all of the verification, all the stuff we've done with Bitcoin is traditionally defensive. We're proven like this path doesn't work. This path doesn't work. This path doesn't work. But the hypothetical amount of paths that could be taken to weaken elliptic cryptography
834
01:07:35.220 --> 01:07:36.100
is
835
01:07:36.260 --> 01:07:37.380
innumerable.
836
01:07:37.460 --> 01:07:39.140
And because of that,
837
01:07:39.619 --> 01:07:45.460
it's a... What we're relying on is, you know, this open problem of p equals NP. If we could prove
838
01:07:46.020 --> 01:07:47.140
that p
839
01:07:47.460 --> 01:07:48.260
equals NP,
840
01:07:49.295 --> 01:07:54.895
that would also break elliptic curves, because that would be able to mathematically represent that you will
841
01:07:55.215 --> 01:07:56.175
be able
842
01:07:56.575 --> 01:07:58.255
to... If you have a problem
843
01:07:58.495 --> 01:08:07.000
that, you know, that you will be able to in somehow trivially reverse engineer an answer. And that's just for all math and all numbers and all things. Like you... Like,
844
01:08:07.400 --> 01:08:09.480
in general. It probably is.
845
01:08:09.720 --> 01:08:12.280
I think it's true that it's breakable.
846
01:08:13.000 --> 01:08:16.040
I
think it's always true that it's breakable under
847
01:08:16.120 --> 01:08:16.680
a certain
848
01:08:18.295 --> 01:08:19.574
power and compute.
849
01:08:20.535 --> 01:08:21.255
Sure.
850
01:08:22.135 --> 01:08:22.775
And
851
01:08:23.095 --> 01:08:29.255
that's why... But that's why, like, you know, the Byzantine general's problem as a... Was not a math...
852
01:08:29.495 --> 01:08:30.615
It's not a math solution.
853
01:08:31.170 --> 01:08:33.969
You know? Like, it it combined physical
854
01:08:34.210 --> 01:08:36.210
it combined physical resources
855
01:08:36.210 --> 01:08:37.329
and value.
856
01:08:37.969 --> 01:08:40.769
And it's just... It's more of an agreement that,
857
01:08:41.010 --> 01:08:41.570
you
858
01:08:42.610 --> 01:08:50.795
know, like Bitcoin in year 18 that we're getting close to is becoming an agreement of like, it's just not worth it to
859
01:08:51.114 --> 01:08:53.354
really try to do it. Right.
860
01:08:53.835 --> 01:08:55.675
It's not worth it to undo this thing.
861
01:08:56.410 --> 01:08:58.489
So
862
01:08:59.210 --> 01:09:00.490
yes, we're
863
01:09:00.490 --> 01:09:02.810
just going to agree to a world where these
864
01:09:04.650 --> 01:09:07.450
things are much more trivial to verify than they are to calculate.
865
01:09:09.805 --> 01:09:17.885
Whatever gets done, like the whole system that gets done to create the blockchain is like a toy model, I feel like of what this concept is.
866
01:09:19.485 --> 01:09:26.040
It's like a toy model simulate like if you know, if we were to simulate it, this is exactly how we would do it with this
867
01:09:26.680 --> 01:09:27.960
kind of game here.
868
01:09:28.520 --> 01:09:29.080
And
869
01:09:30.680 --> 01:09:33.320
it's not like we don't, this in a lot of ways,
870
01:09:35.045 --> 01:09:38.405
it's like believing in God where I care
871
01:09:39.845 --> 01:09:42.485
if somebody proves it or not. It
872
01:09:43.125 --> 01:09:44.405
really doesn't change anything.
873
01:09:46.420 --> 01:09:47.300
Like, we're...
874
01:09:48.500 --> 01:09:50.899
We wanna live in this world where this exists,
875
01:09:51.539 --> 01:09:53.459
and it happens to be,
876
01:09:54.739 --> 01:10:06.325
you know, it happens to be crypt... Like, cryptographically secure doesn't mean it's proven in math. I guess that's my my point. Isn't that Yep. You know what I mean? It's more of like, okay. Well, if it becomes uncryptically cryptographically
877
01:10:06.325 --> 01:10:07.125
secure,
878
01:10:07.525 --> 01:10:08.885
we have to really...
879
01:10:10.885 --> 01:10:19.530
We have to hope that we've reached a point of maturity where we're able to make it... We're able to make the adjustment to make it re secure again. And it's, I think,
880
01:10:19.930 --> 01:10:26.010
it's all like, this is a part of, like, human existence that we're always going to have to collectively figure this out
881
01:10:26.490 --> 01:10:36.235
through time. The reason and the fact that it's valuable is that the
incentive will always be there to attack it. The incentive will always be there to create more efficient compute, more efficient
882
01:10:36.235 --> 01:10:43.355
algorithms and make operations more efficient to attack it so that we can accelerate
883
01:10:45.755 --> 01:10:49.570
the defense of it. You know, it almost reminds me of Dwight Schrute's
884
01:10:49.730 --> 01:11:01.489
quote in The Office where, you know, I think he's in the pilot, you know, and he was like, Oh, the Schrute blood is the best. I can raise and lower my cholesterol on command. Yeah. Why would you ever want to raise your cholesterol? And it's like, So I can lower it.
885
01:11:03.275 --> 01:11:04.554
Right. Yeah.
886
01:11:05.115 --> 01:11:08.155
But it's... You know what I mean? So, like, I... It... It's this...
887
01:11:08.795 --> 01:11:11.195
I just don't know. I I don't know if it even
888
01:11:12.475 --> 01:11:13.594
is meaningful
889
01:11:14.315 --> 01:11:17.035
to math... You know, to say, oh, we can prove
890
01:11:17.620 --> 01:11:22.980
that cryptography is like that that elliptic curve cryptography is or isn't secure
891
01:11:23.620 --> 01:11:33.394
per se. Yeah, I think it's also a good point too, as it relates to P equals NP we're talking about. Like it actually... Bitcoin doesn't determinately settle it either way. You could prove,
892
01:11:34.835 --> 01:11:38.434
if in theory you broke Bitcoin, it would not prove that p equals n p.
893
01:11:38.915 --> 01:11:43.554
And also Right. If we've proved that p does not equal n p, that that does not mean
894
01:11:44.760 --> 01:11:49.000
that we prove that p does not equal NP. Right? Like, it's just...
895
01:11:49.320 --> 01:11:53.960
It... It's something that if we're to found, we could have related, like, consequences to Bitcoin,
896
01:11:54.120 --> 01:11:59.905
but Bitcoin itself... Basically, p equals NP is a bigger problem than than elliptic curves. And so,
897
01:12:00.785 --> 01:12:08.305
if you get a terminate answers from p equals NP, that could have implications on Bitcoin. But if Bitcoin either stays secure or breaks,
898
01:12:08.465 --> 01:12:15.519
it doesn't really actually go up to the level of p equals NP. Basically because it's even a closed system. It's not It's Yeah.
899
01:12:15.760 --> 01:12:16.800
Bitcoin
900
01:12:16.800 --> 01:12:22.159
has bosses in the math store is basically what we're talking about here. And p equals MP is something that sits above Bitcoin,
901
01:12:22.719 --> 01:12:24.175
not the other way around.
902
01:12:25.695 --> 01:12:38.094
I think there were maybe even one or two other small things I skipped because I think there's like seven like open problems that we've talked about. Maybe just to recap for the class so far. On though, real quick, isn't it? Isn't... I mean, I'm just personally comforted
903
01:12:38.580 --> 01:12:42.500
by the fact that there's somebody at Coinbase that is as,
904
01:12:43.300 --> 01:12:52.580
on top of things as the person who
made that. The head of cryptography at Coinbase. Their head of cryptography, it's comforting, right? Just don't don't you think it's...
905
01:12:52.900 --> 01:12:53.460
Absolutely.
906
01:12:53.905 --> 01:12:54.625
Absolutely. So
907
01:12:55.185 --> 01:12:57.265
I'm just saying, you know, maybe
908
01:12:57.825 --> 01:13:00.705
there are more than three or four high priests out there
909
01:13:01.185 --> 01:13:05.745
that we have to... That we're trying to get closer to. I've exchanged emails with him. Maybe we'll try and get him on the podcast.
910
01:13:05.985 --> 01:13:08.170
That'd be pretty sick. Yeah. Well,
911
01:13:09.050 --> 01:13:12.170
he's done some podcasts before, so we can
912
01:13:12.730 --> 01:13:13.690
probably grab him.
913
01:13:15.770 --> 01:13:16.409
So
914
01:13:18.490 --> 01:13:23.925
to just go through the list of the problems we talked about, and I'm gonna go very quick because,
915
01:13:24.725 --> 01:13:30.085
you know, we're already an hour and fifteen minutes in. I don't wanna get everyone, lose everyone who's probably already asleep.
916
01:13:31.844 --> 01:13:32.724
Nonsense,
917
01:13:32.725 --> 01:13:33.125
nonsense. Right.
918
01:13:33.940 --> 01:13:34.659
Basically,
919
01:13:34.900 --> 01:13:38.659
the difficulty of factoring a point on the curve, like if you somehow could,
920
01:13:39.460 --> 01:13:41.139
break that, we talked about,
921
01:13:41.940 --> 01:13:45.060
the the initial minors con... Conjecture,
922
01:13:45.620 --> 01:13:51.244
where you could just take these like points, and if you could find a determinant equal to zero, could you collapse the space down?
923
01:13:52.844 --> 01:13:53.804
We had from,
924
01:13:54.445 --> 01:13:55.724
Shoop's theorem,
925
01:13:56.765 --> 01:13:58.364
basically, the the
926
01:13:59.480 --> 01:14:04.360
ability that the attacker gets the square root ability to get efficiency,
927
01:14:04.520 --> 01:14:08.440
could that be bled down to an even greater advantage that could collapse the whole thing?
928
01:14:09.800 --> 01:14:12.680
The cobblets curve angle
929
01:14:11.945 --> 01:14:15.225
of that there is an increase of the verification time, could that also,
930
01:14:15.945 --> 01:14:24.745
allow for an attacker to decrypt in a way and work... Walk... Not not decrypt, but walk backwards to be able to get to the final, key, your private key.
931
01:14:25.780 --> 01:14:27.460
We talked a little bit about
932
01:14:29.620 --> 01:14:30.900
P equals NP,
933
01:14:30.980 --> 01:14:32.500
and I think there's also
934
01:14:33.940 --> 01:14:35.140
what we have here.
935
01:14:36.180 --> 01:14:41.594
You can invent a point factoring, which I guess is kind of what we talked about earlier. I already caught that one. And then,
936
01:14:42.715 --> 01:14:47.275
there's one that actually uses a bit of isogenies cryptography,
937
01:14:47.275 --> 01:14:56.130
which is probably its own series you go down. This is one of the popular paths that are being discussed as it relates to quantum computing. You have three main camps of hash based algorithms,
938
01:14:56.290 --> 01:14:57.090
lattices,
939
01:14:57.090 --> 01:14:58.130
and isogenies.
940
01:14:58.130 --> 01:15:12.815
And people who listen to the podcast should be... Already be like a little familiar that an isogeny is an isomorph... It's like... It's it's a it's a something morphism. It's a morphism between elliptic curves. Yes. Second, an equivalence.
941
01:15:12.815 --> 01:15:19.614
It's not an isomorphism, but it's one of the morphisms where there's a there's an equivalence. So the idea here is leveraging
942
01:15:19.695 --> 01:15:20.815
these isomorphisms.
943
01:15:20.815 --> 01:15:28.030
Could you hop to a weak cousin This is basically like in plain English what we're talking about here. This is in the study guide chapter,
944
01:15:28.190 --> 01:15:39.934
7.3 and a little bit in chapter four, two, we talked about Hassa's theorem, and a curves point is pinned near p plus one, and that all curves points form one group. And one thing I didn't mention is curves come in families.
945
01:15:41.535 --> 01:15:52.649
And the idea here is that curves have cousins, right? For any curve, exists other curves, it's isogeny's class that can be connected to a biasogeny, it's a translation between curved languages. And isogenies is a map that sends a point
946
01:15:52.969 --> 01:16:00.650
to the end respects the group law, and sums go to sums, and it has one property that is very critical here.
947
01:16:02.075 --> 01:16:06.235
If q equal dp on curve egg, right, so this is the
948
01:16:06.635 --> 01:16:11.675
public key equals your private key times, you know, to do the arithmetic, the generator doing the arithmetic.
949
01:16:14.200 --> 01:16:27.880
You can actually have your secret number survive the translation between the two curves. So the idea is that could you find a cousin curve to sec p that could honor all the properties, break that curve, and since the private key survives, you'd be able to crack
950
01:16:28.435 --> 01:16:38.514
a different curve than sec p two fifty six k one and then hop that word backwards to the Bitcoin curve. Right? So it's like Right. So it preserves the hardness. It preserves the hardness of the discrete log problem.
951
01:16:38.835 --> 01:16:40.034
Yeah. It does. Exactly.
952
01:16:40.699 --> 01:16:42.539
Right. So maybe
953
01:16:42.699 --> 01:16:47.579
a hypothetical attack would be a common metrics of some of these things we're talking about to try and like get your way in.
954
01:16:48.940 --> 01:16:52.860
So does Bitcoin's curve have a weak cousin in the family? A curve that's that
955
01:16:52.860 --> 01:16:57.415
where the log is easy, anomalous and pairing friendly that you could tunnel to. The catch is,
956
01:16:57.735 --> 01:17:02.055
is that the curves connected by isogenies over the same field have the same number of points.
957
01:17:02.935 --> 01:17:07.415
So you're back to exactly what you're saying
is you're back to two to the two fifty six
958
01:17:07.655 --> 01:17:10.375
big P numbers of trying to break this stuff.
959
01:17:11.820 --> 01:17:13.020
In 2004,
960
01:17:13.020 --> 01:17:15.340
there was a theorem by Zhao Miller
961
01:17:16.380 --> 01:17:17.500
Van Costen,
962
01:17:17.740 --> 01:17:21.100
and this is like a belts and suspenders approach. They proved
963
01:17:22.060 --> 01:17:22.860
assuming
964
01:17:24.025 --> 01:17:25.065
GRH.
965
01:17:25.065 --> 01:17:29.225
Now I'm gonna be honest and sound, what is GRH?
966
01:17:29.225 --> 01:17:33.145
GRH
967
01:17:33.145 --> 01:17:37.465
math, elliptic curves. See, we're all just learning things on the show. That's what this is all about.
968
01:17:38.420 --> 01:17:40.580
The... Oh, the general Riemann hypothesis.
969
01:17:40.580 --> 01:17:41.780
Ah, okay.
970
01:17:41.860 --> 01:17:45.300
Yeah. Okay. That I know. Yeah. I just never saw it abbreviated that way.
971
01:17:46.900 --> 01:17:47.780
And so,
972
01:17:48.980 --> 01:18:10.610
plainly, all doors in the family have locks of equal strength, and the quarters of them, between them are short. So you're back to square one, basically. And it's probably worth noting for whatever it's worth that, Jonas Nick, one of the best cryptographers also in the world who probably fully understands what we're doing. He didn't seem to go the isogenies route. Correct. Right?
973
01:18:11.810 --> 01:18:15.650
Probably So good to have him on and maybe We should talk about... Yeah. I
974
01:18:15.890 --> 01:18:21.890
think that the emerging consensus right now is hash based algorithms because we already use hashes in Bitcoin. So it's the one that introduces
975
01:18:22.345 --> 01:18:26.185
no new security assumptions to Bitcoin, whereas lattices and isogenies do.
976
01:18:27.065 --> 01:18:29.945
The trade off is that, hash based algorithms are larger.
977
01:18:30.505 --> 01:18:32.745
And you have to maintain state,
978
01:18:33.145 --> 01:18:35.385
which means, you know, you can't have
979
01:18:36.040 --> 01:18:37.479
if you leak
980
01:18:37.719 --> 01:18:39.559
key information, if you
981
01:18:40.600 --> 01:18:45.800
basically aren't keeping a counter of when did I I signed this transaction, I signed this transaction,
982
01:18:46.520 --> 01:18:50.840
you need to keep a running count within your signer of how many times you've signed with the key.
983
01:18:51.615 --> 01:18:53.935
Otherwise, you will leak your private key.
984
01:18:54.255 --> 01:18:57.054
It's basically... Or parts of your private key, which is basically
985
01:18:57.375 --> 01:19:01.855
the unfortunate trade off that we would have to go do in a post quantum world with hash based algorithms.
986
01:19:03.550 --> 01:19:04.190
So,
987
01:19:04.590 --> 01:19:06.990
I mean, that's
988
01:19:06.990 --> 01:19:08.350
all part of those trade offs.
989
01:19:10.510 --> 01:19:12.030
I mean, the good news
990
01:19:12.350 --> 01:19:16.190
to me is based on where we are and all
the ideas that are out there, I mean,
991
01:19:17.195 --> 01:19:20.954
We have time to get comfortable with all of these things
992
01:19:22.074 --> 01:19:22.875
probably.
993
01:19:22.875 --> 01:19:23.675
We're
994
01:19:25.195 --> 01:19:27.274
probably not dealing with anything
995
01:19:27.434 --> 01:19:29.274
seriously threatening in the next
996
01:19:30.130 --> 01:19:33.410
don't think in the next five to ten years that we can
997
01:19:33.890 --> 01:19:37.090
have these people continue to do this work
998
01:19:37.570 --> 01:19:39.250
and
999
01:19:40.290 --> 01:19:41.090
get us comfortable.
1000
01:19:42.615 --> 01:19:48.935
Like, it's not gonna be a snap of the finger, oh, we're changing, you know? Yeah. Like, this is gonna take...
1001
01:19:49.575 --> 01:19:52.535
It's, you know, it's gonna have to be a slow process. Yeah.
1002
01:19:52.775 --> 01:19:53.655
And so
1003
01:19:54.215 --> 01:20:04.719
maybe just to quickly bullet point off all of the lists again, of all of the things in math that are related to the stuff that you should be thinking about. And if you see advancements in these kind of things, maybe revisiting the conversation.
1004
01:20:05.199 --> 01:20:06.400
We're gonna start with...
1005
01:20:07.360 --> 01:20:08.959
We have the
1006
01:20:10.080 --> 01:20:12.560
general route one family of point factoring.
1007
01:20:14.364 --> 01:20:19.084
That's been an open problem for a while. You would get basically the security drops
1008
01:20:19.645 --> 01:20:24.205
from two to the two fifty six to, like, two to the 80 to two to the 112.
1009
01:20:24.205 --> 01:20:26.605
So still pretty strong, but, like, that's what you need to think about.
1010
01:20:27.510 --> 01:20:30.230
The next one would the initial minors one we talked about with,
1011
01:20:30.710 --> 01:20:33.030
finding if you get the determinant to equal to zero.
1012
01:20:34.070 --> 01:20:35.349
Next, you're gonna have...
1013
01:20:36.309 --> 01:20:40.150
Can you can you hear my kids rioting in the background? It's awesome. Yeah.
1014
01:20:41.925 --> 01:20:45.525
I can hear my wife shushing them, but she is losing the battle, absolutely.
1015
01:20:46.085 --> 01:20:50.725
So you have, you know, the the the point factoring piece, you have the initial minors line,
1016
01:20:51.685 --> 01:20:52.965
with all of these, like,
1017
01:20:53.445 --> 01:21:01.659
submatrices that... Of minor matrices that you'd be able to, if you found the determinant equal to zero, you'd be able to quickly collapse things down. Curve- To me this is finding weaknesses
1018
01:21:02.139 --> 01:21:05.019
in the system, finding definitely and non perfect
1019
01:21:05.980 --> 01:21:06.699
finding
1020
01:21:07.420 --> 01:21:11.844
the weaknesses in the door. Yeah. This is finding the weaknesses for sure
1021
01:21:12.645 --> 01:21:21.925
because you need to do it for each point. So you maybe find a way to classically reduce the computation required to go from two to the two fifty six
unique points on the curve to something smaller.
1022
01:21:23.230 --> 01:21:28.989
Then we have the curved symmetry, which we were talking about. It's an open problem for you to do a lean proof on it. The
1023
01:21:31.869 --> 01:21:32.909
lifting one,
1024
01:21:34.270 --> 01:21:47.735
I guess, for the curved symmetry, talking about, you know, this was the cobblets curve and stuff. Right? Like, being able to, like, find your way backwards on that lifting. Can you beat the height penalty basically as you get further and further higher to try and walk backwards? Are you able to start,
1025
01:21:48.055 --> 01:21:49.895
efficiently breaking it down? It's
1026
01:21:52.309 --> 01:22:06.150
it's basically open, classical bound, say no, but it's not very tight. A 2025 quantum computer shows the curve lifts this arithmetically. This is Shor's algorithm. This is the whole quantum door. This is why... This is this is the door quantum is knocking on Yeah. For breaking elliptic curves.
1027
01:22:06.844 --> 01:22:11.965
Then we have isogenies, and could you, with the Riemann Hypo... Could you detour to a cousin curve?
1028
01:22:12.205 --> 01:22:21.920
As we just discussed though, for the curve to be part... The actual proper cousin curve, it needs to have the same level of modular p. So you're back to the square, you know, you're back to the beginning again. Can't be isomorphic
1029
01:22:21.920 --> 01:22:23.280
or homomorphic. So
1030
01:22:23.600 --> 01:22:26.159
this path by itself? Right. Unless this
1031
01:22:26.239 --> 01:22:28.239
is Lagrange's
1032
01:22:28.239 --> 01:22:30.639
theorem, but like you... It has to have the same amount of So
1033
01:22:31.040 --> 01:22:43.664
to use this, you would have to use this in combination with something else. If you would do a cousin curve with something else that would then break the whole thing. Like, is, this is an alley oop setup. This is not in of itself the solution because
1034
01:22:43.985 --> 01:22:46.545
walking through the cousin curve, you're just back to where you started.
1035
01:22:47.265 --> 01:22:54.920
I like it. And then there's just combo. Yeah. It's a combo billiards, combo pool shot. That... That's right. That's right. And then there's the general just
1036
01:22:55.320 --> 01:22:56.040
gap
1037
01:22:56.280 --> 01:22:57.000
of...
1038
01:22:59.160 --> 01:23:06.455
We talked about a Shupin blind attacker... Attackers can't beat square root of n. Could you, in theory, improve that to something more? We talked about that earlier.
1039
01:23:06.695 --> 01:23:11.815
And then the next, like, kind of tier, like defensive, improved theoretic stuff
1040
01:23:12.375 --> 01:23:16.295
with one way functions proving that they can maintain exist with p equals m p.
1041
01:23:17.090 --> 01:23:22.929
If you could somehow, in theory, you're not really able to, but just hypothetically, if you could prove that the discrete log problem was hard,
1042
01:23:23.329 --> 01:23:26.849
then that would be
a a defense buttress, not for cracking, but for defending.
1043
01:23:27.969 --> 01:23:30.289
The hardness of SHA two fifty six, which
1044
01:23:30.805 --> 01:23:37.445
I'll be honest, I wouldn't, I think SHA-two 56 in a long enough time frame also fails. It's just a question of when.
1045
01:23:39.045 --> 01:23:39.925
And then
1046
01:23:40.245 --> 01:23:48.059
there's some other things of just like... Those those are the big those are the big things. I'm looking through the rest of this here. There's formalization work that could be done in lean
1047
01:23:48.460 --> 01:23:49.659
to either...
1048
01:23:49.900 --> 01:23:52.460
That that all feed into this stuff. But that's...
1049
01:23:53.020 --> 01:24:02.425
So there's six offensive problems, point factoring, solving degrees, initial minors, the symmetry, the lift, and the cousin. And there's three defenses that no one can really climb. If we can prove one way functions
1050
01:24:02.585 --> 01:24:03.544
are strong,
1051
01:24:03.864 --> 01:24:06.824
p equals m p, improving the curve itself is hard.
1052
01:24:07.304 --> 01:24:13.304
Those are, like, the defense. So there's, like, five... We're looking at this. There's six offense, and there's, like, three defense, and they're all open problems.
1053
01:24:14.800 --> 01:24:20.000
And that's kind of, I think, a good just... When everyone's like, it's gonna break. It's like, okay. What... This was part of my...
1054
01:24:20.240 --> 01:24:27.840
Making this study guide this week was my journey because everyone's like, it's gonna break because math is gonna break. And I was like, okay. Can we talk about the specific things in math
1055
01:24:28.195 --> 01:24:29.474
that have to break
1056
01:24:29.955 --> 01:24:33.874
to actually have a problem here? And packing 11 squares,
1057
01:24:34.755 --> 01:24:37.394
optimally in a space while being very
1058
01:24:38.035 --> 01:24:41.475
interesting, I think, that could probably have downstream interesting applications.
1059
01:24:42.180 --> 01:24:44.980
Going back to, Yehuda's, like, Twitter thread,
1060
01:24:45.460 --> 01:24:59.834
we don't rely on elliptic curve cryptography because we just think that humans haven't figured out an efficient algorithm yet. We believe the problem itself is sufficiently hard and has hardness inherent to the nature of the math being done. And so I wanted to enumerate the hypothetical things that could be done
1061
01:25:00.475 --> 01:25:04.235
that could reduce the security, and that's, you know, that's what we went through today.
1062
01:25:04.475 --> 01:25:08.715
I think the title of this episode might be, like, red teaming elliptic curve.
1063
01:25:09.490 --> 01:25:18.130
Yeah. Something like This is red teaming. Yeah. This is honestly red teaming. This is going through and thinking about what are the doors to knock on, what are the things that could be plausibly insecure,
1064
01:25:18.530 --> 01:25:19.969
all of that stuff. Absolutely.
1065
01:25:20.850 --> 01:25:21.410
Awesome.
1066
01:25:22.035 --> 01:25:22.915
Great stuff.
1067
01:25:25.795 --> 01:25:28.035
Anything else you wanna do or?
1068
01:25:28.355 --> 01:25:29.395
Let's see.
1069
01:25:31.555 --> 01:25:39.739
I'm not sure. This was the meat and potatoes or vegetables. Well, it's meat and potatoes for you and me. Maybe it's vegetables for everyone else in the audience listening.
1070
01:25:41.260 --> 01:25:46.220
I'm trying to think through Things got real. I feel like shit got real today. A little bit. Yeah. We had to It has to.
1071
01:25:47.165 --> 01:25:54.285
Rather than like passively explain stuff, had to go on the offense a little bit and talk about the adversarial nature of the cryptography that holds up all of Bitcoin.
1072
01:25:55.005 --> 01:25:56.525
Maybe that would the
1073
01:25:58.285 --> 01:25:59.805
Amsterdam presentation
1074
01:26:00.045 --> 01:26:04.329
maybe. But we should do that. Because, and that's like, man, because like
1075
01:26:05.530 --> 01:26:06.169
my,
1076
01:26:06.809 --> 01:26:10.649
our contact at BTC Inc. Was really struggling to like,
1077
01:26:11.610 --> 01:26:17.385
tap and click like, am doing That's it. No, this is why we're doing the map panel. This is why we're doing the map panel. Gonna... I
1078
01:26:18.265 --> 01:26:30.745
this is absolutely it. Then he I've been holding off like, so he was like, hey, just give me the description and I'll put it on the website. And I was holding off because even for me, it wasn't fully clicking in now. This is it though. This is the talk. Got it. And now that I kinda teed this up for you today, I sent you my notes.
1079
01:26:32.360 --> 01:26:39.880
You... We could do... You could brush up on it now. We could have an interesting conversation around it. Yeah. Now we can do some work and prepare some... Like a pretty band on This
1080
01:26:40.520 --> 01:26:44.360
is perfectly pod conf aligned. Do a podcast to get inspiration for the conference talk.
1081
01:26:46.045 --> 01:26:47.885
Big Bitcoin's in control. Big Bitcoin
1082
01:26:48.204 --> 01:26:52.844
and big math are on a collision course. That's right. That's right. Good stuff.
1083
01:26:53.244 --> 01:26:54.284
Right. Well then
1084
01:26:54.605 --> 01:26:57.485
Magic Internet Math is in the books.