Quantum computing has practical use cases today—drug discovery, financial optimization, and defense—and is on a hockey-stick trajectory similar to early AI, already delivering significant improvements in speed and optimization for early adopters like AstraZeneca and HSBC.

(00:00:01) You're listening to TIP. (00:00:02) Hey everyone, welcome to this Wednesday's release of the Bitcoin Fundamentals Podcast. (00:00:07) Today I'm joined by Charles Edwards to talk about quantum computing, what it really is, where it's headed, and what it means for Bitcoin security. (00:00:16) We break down the differences between physical and logical qubits, the debate around how soon Q day could arrive, (00:00:23) and how upgrades like BIP 360 might protect the network. (00:00:26) We also explore the broader impacts that quantum tech could have on AI, material science, and finance. (00:00:33) This is one that you will not want to miss, so let's jump right into the conversation. (00:00:40) Celebrating 10 years, you are listening to Bitcoin Fundamentals by the Investors Podcast Network. (00:00:47) Now for your host, Preston Pish. (00:00:59) Hey everyone, welcome to the show. (00:01:00) I'm here with Charles Edwards and we're talking about a pretty difficult topic, but we're going to try to make it accessible and we're going to try to talk through the reality of whatever it is or whatever we think it is. (00:01:12) And we're talking about quantum computing. (00:01:14) This is going to get pretty Bitcoin heavy, but obviously the topic goes beyond Bitcoin and (00:01:21) Charles, as a person that's investing in this space in particular, I'm very curious to go down the paths that go beyond just Bitcoin itself. (00:01:29) But in short, welcome to the show. (00:01:31) Excited to get into this with you. (00:01:33) Yeah, likewise. (00:01:33) Great to be with Preston. (00:01:34) It's been too long. (00:01:35) I think it's been about four or five years. (00:01:39) It's been. (00:01:40) Yeah, it's been way too long. (00:01:42) Been good. (00:01:43) Been good. (00:01:43) I'm excited to have you back on the show, Charles. (00:01:46) So let's start here. (00:01:48) So I made a video about quantum probably back in maybe January of 2024. (00:01:54) No, of this year of 2025. (00:01:57) And (00:01:58) Where I started, I was just trying to define like, what in the world is it? (00:02:02) How does it work? (00:02:03) Just so I can wrap my own head around it. (00:02:05) Because if you can't kind of like describe what it is and what it's doing, it's really difficult to understand what problems or things that it's going to solve in the real world. (00:02:14) So this is a really hard question. (00:02:16) And you would think it'd be the easiest thing to kind of cover, but I find it to be one of the hardest things to cover is what in the world is quantum computing? (00:02:23) How does it work? (00:02:24) Give A layman's overview from your point of view as to what this is. (00:02:28) I suppose it's, at the most simplistic level, traditional transistor chips work in ones and zeros and you can have one state or the other. (00:02:36) As in most things in life, you can be here or there, but you can't be in both places at once. (00:02:40) Things get weird at the quantum level and Albert Einstein always struggled with this and basically wrestled with it his whole life even. (00:02:47) it doesn't make logical sense anymore. (00:02:49) And you get down to that atomic level that things can have multiple states at the same time or it's probability based. (00:02:55) So essentially, a quantum computer is trying to replicate the quantum state and physics, which is, you know, potentially being in multiple values at the same time. (00:03:03) So that where that becomes interesting in programming and especially what we're talking about here in encryption is you can essentially (00:03:10) model multiple values at the same time and zero in on an optimization really quickly. (00:03:16) So if you're trying to guess a password, if it's just a pin code and a lock and it is scrolling through the numbers and if it's got three different number options, you can get there eventually, it'll take you a while. (00:03:25) But with a quantum machine, you can basically simulate all of them at once more or less and solve things really quick. (00:03:31) And so Google had a really big headline about a year ago, I think it was, (00:03:35) with their wheeler chip where they solved a mathematical equation, which we're using any supercomputer today would take more time than the entire universe. (00:03:43) So like trillions of years, numbers that we can't even comprehend in our mind. (00:03:47) So it gets really exciting, I suppose, on the industry level where we can now unlock new innovations that were just deemed impossible and solve functions and models that were just (00:03:58) considered not unsolvable years ago. (00:04:00) And yeah, it's expected across multiple industries of basically every industry to have an impact in multiple improvements. (00:04:06) So drug discovery, AstraZeneca has been using it and done trials with it and found there's, you know, significant percentage improvements in speed and optimization there. (00:04:15) The defense has also been using it a bit. (00:04:17) There's also useful for communications, but you know, even landmine detection, that sort of thing. (00:04:22) HSBC also has done a case study to improve and it's improved bond optimization (00:04:27) processes. (00:04:27) So a lot of people say, quantum's not here today. (00:04:30) It's got no practical use. (00:04:31) It is here and it does have use today. (00:04:34) It's still very neat early in its development. (00:04:36) It's like if you were to use ChatGPT 5, six years ago, even Altman, the creator of it, said it was a terrible product, right? (00:04:42) So quantum is still like a really basic iteration of where it's at today. (00:04:46) So it's just really kind of, it's already proven those use cases and it's on that trajectory in my mind in the early stages of the hockey stick of any kind of technical adoption. (00:04:55) Amazing job. (00:04:56) It's a very hard thing to kind of put into words, especially because it's so complex and so abstract. (00:05:01) The use cases there that you were talking about at the end of your comment, I just put up a slide for people that are only listening to the audio. (00:05:09) And before we recorded this, I just was kind of curious myself as to what the top uses are for quantum moving forward. (00:05:16) And the top four things really kind of come down to material and chemistry simulations. (00:05:21) which can lead to all sorts of new innovation. (00:05:24) You could have new batteries, you could have semiconductors, you could use this in pharmaceuticals to come up with new molecules that can help people recover from whatever type of illness. (00:05:34) It's going to be really good at optimization problems for logistics. (00:05:38) So shipping routes, supply chains, traffic flows, I can only imagine in like fluid dynamics and like really complex interactions between (00:05:47) things that just, either it's humans or nature itself, migration patterns, call it, whatever. (00:05:54) Obviously in the crypto security thing, which we're going to cover at nauseum probably in the discussion here, so I'm going to leave that one aside. (00:06:01) And then finally, just in machine learning and AI acceleration, when we look at all the parallel processing that's happening with the Nvidia chips and all of that, this could potentially be massive in the implications of what that could do. (00:06:15) Yeah, go ahead, Charles. (00:06:16) It looks like you had something else. (00:06:17) Yeah, I totally agree. (00:06:18) I just also pulled up a couple of slides on my side. (00:06:21) You know, that multiple firms seeing performance records across many utilities today. (00:06:25) So protein folding, drug discovery talked about. (00:06:29) So yeah, there's multiple use cases across quantum. (00:06:32) So you mentioned a lot of them. (00:06:33) I've got a list here on my screen, but I can share later maybe. (00:06:36) But it's cryptography, drug discovery, disease, risk predictions, financial modeling, as you touched on, traffic optimization, anything we need to (00:06:44) optimize on something or scenario analysis, you can really zero in infinitely faster. (00:06:49) Design optimization and postconum communications is basically every industry is touched on in some format. (00:06:55) The one thing I wanted to add on just kind of defining what it is or what kind of the key components are that enable it, and then maybe something that can help people visualize how this works. (00:07:07) When I was doing the research for the video that I made, which I'll also have a link in the show notes if people want to watch this, but there's three key components. (00:07:13) You have to have the superposition. (00:07:15) You have to have entanglement of these two atoms or electrons that are in this superposition state. (00:07:21) They have to become entangled. (00:07:23) And then the interference that occurs between the entangled qubits (00:07:28) is how you're able to arrive at what I would refer to as an immediate solution or an immediate answer to what you're trying to solve for. (00:07:37) So for people that have done eigenmath, have you ever done equations where you got basically like 3 unknowns, you got 3 equations, and then you line them up into a matrices, and then you're solving for the answers of the three different variables. (00:07:51) For anybody that's ever done this in math, (00:07:53) Kind of think of it in this way, where you've got these three equations, you've got the three variables, and instead of having to go through line by line, first you're solving for A, then you're solving for B, then you're solving for C, and you're substituting them all in there. (00:08:07) Imagine kind of lining up those 3 equations and the interference of those 3 variables as they're interacting with each equation immediately produces the answer as opposed to having to go line by line in a very (00:08:21) ordered way to solve each one of them and then piece it all back together. (00:08:25) Through the physics of this superposition entanglement and interference, you're able to get that immediate answer. (00:08:31) Now just think of it more than three equations. (00:08:33) You're doing this with countless lines of variables and whatnot. (00:08:38) Yeah, exactly. (00:08:39) I think that's a good analogy. (00:08:40) And what kind of plays into that today is error rates. (00:08:44) So there's a difference that, and this often comes up as a debate on Twitter and people often think I'm referring to the wrong thing, but (00:08:51) There's physical qubits and logical qubits. (00:08:54) And this is a set done by very simplified. (00:08:56) It's basically the processing power of a quantum machine. (00:08:59) The difference between physical and logical is essentially there's a large error rate on most current physical qubits. (00:09:05) So that what we're trying to get towards is a logical qubit, which is basically error free. (00:09:10) So whenever I refer to qubits and probably in this conversation, I'm referring to logical. (00:09:14) It's a much smaller number, you know, orders of magnitude smaller because there is an error rate today. (00:09:19) And most people say, you need millions of qubits to solve XYZ equation or to break Bitcoin or any encryption. (00:09:26) It's actually a much smaller number at a logical qubit level. (00:09:29) It's a couple of 1000, that sort of magnitude. (00:09:32) And what people don't realize is the error rates are really dropping significantly in recent years. (00:09:38) And they're finding that the more qubits you add, the error kind of compresses. (00:09:42) So it's kind of it scales better. (00:09:44) So that's just kind of a sort of a brief summary on the processing units of quantum machines. (00:09:49) I think that this is a super important point. (00:09:52) And mostly because a lot of these labs that are working in this space, they're publishing their numbers in the news. (00:09:59) And the numbers that I always see are physical qubits. (00:10:02) And they're saying, oh, we're going to have this many hundreds of thousands of physical qubits. (00:10:07) And they don't say physical, they just say qubits. (00:10:09) by date, whatever. (00:10:11) And what people fail to realize, going back to this interference piece, the three pieces that I was mentioning earlier, when you entangle the qubits and you're creating these interference waves to get this immediate solution, the problem that kind of arises from this is this noise factor that Charles just brought up. (00:10:31) And so when you're doing this with a few, the noise factor is a little bit easier to control, but imagine doing this with (00:10:38) of thousands of physical qubits that are all entangled and you get any type of heat, you get any type of vibration or anything like that. (00:10:48) And immediately, because they all have to stay entangled in order to provide these, go back to that eigenvector math. (00:10:54) Imagine one of the equations getting fuzzy and you can't really know what's even in the equation because of this disturbance or this noise. (00:11:03) Well, you can't solve for the entire system of equations because that one (00:11:08) is out of sync or difficult to see or visualize compared in relative to all the other ones that are entangled. (00:11:15) So this is what makes it really challenging. (00:11:17) I also think that this is what makes the timeline of this really difficult to predict or know with a lot of precision and why there's such a wide range. (00:11:28) And I know, Charles, you're very bullish on the timeline and I'm sure I could go find somebody else very smart on the topic that would be very bearish on the timeline. (00:11:37) And it just seems like this understanding of the noise factor and how that's going to progress or get resolved in the coming decade is really kind of at the heart of the debate. (00:11:48) Would you agree with that? (00:11:49) And do you think that I properly quantified it? (00:11:52) Yes and no. (00:11:53) So I think currently the rate of qubits is progressing faster than Moore's law. (00:11:58) So if you plot, it's like the Bitcoin chart on a log scale, right? (00:12:01) It's a straight line on a log scale where progression is really consistently improving every year that's hit there. (00:12:06) and this is already a couple years old, but the trend is not slowing down and the number of qubits is doubling about every 18 months, so faster than Moore's law. (00:12:14) And at the same time, each year we're seeing like an extra 9 or an extra granular level of lower error rates. (00:12:21) So it's moving a lot faster than people think. (00:12:23) I think the people that say the timelines I talk about are pretty, you've got a slide, it looks like the one before, slide three. (00:12:29) These are kind of (00:12:30) Four sources I like to reference. (00:12:32) There's another one you can add to this list, which is the Department of War in the US. (00:12:36) They've recently said that they think there's a tangible risk of Q day within three years. (00:12:41) Now that's pretty aggressive, but it shows a really big confluence of people converging on this becoming a tangible risk to encryption within the next couple of years. (00:12:51) So this slide here is talking about where could it be a risk for Bitcoin, right? (00:12:54) So Bitcoin, the first thing to notice, Bitcoin's security, the weakest link is elliptic curve cryptography and Bitcoin's encryption. (00:13:01) And the first thing to note is that's weaker than RSA. (00:13:04) And so what we're talking about here is when can we break that? (00:13:07) And these four sources kind of converge in around 2:00 to 9 years from now. (00:13:11) The Jameson lot is a Bitcoin developer, is deep in the space, works in the code. (00:13:16) He's run the security business in (00:13:18) Bitcoin for many years. (00:13:19) He says it's a 50% risk in 4 to 9 years. (00:13:22) And remember, if it's 50 and 4 to 9 years, what if it's a 30% risk? (00:13:25) That's obviously earlier than that. (00:13:27) You know, there's always some risk earlier than these time frames. (00:13:30) Pierre Lucky is a PhD in maths and physics, specializing in quantum. (00:13:33) He thinks it's two to six years away. (00:13:35) McKinsey, obviously one of the biggest think tanks in the world, are saying Q day, that's RSA broken, is 2 to 10 years away. (00:13:43) And again, remember, (00:13:44) because ECC breaks years in advance because it's not as strong as RSA. (00:13:48) And then one of the big papers on this matter is that 2017 quantum paper at the bottom. (00:13:53) And they're saying you only need 2,330 qubits. (00:13:56) That's the logical ones. (00:13:57) to break Bitcoin's encryption. (00:13:59) And most leading firms right now are projecting that capability within four to five years. (00:14:04) And that's again written by multiple doctors at Microsoft, IronQ, the biggest quantum company in the world and Meta. (00:14:10) So all these time frames converge in the sort of two to nine year bracket with a very high probability in the sort of four to five years, which is why I talk about us having until 2027 to 2029 to solve this risk for Bitcoin. (00:14:24) And that considers also (00:14:26) we need to think also about lead times for implementing any change on Bitcoins. (00:14:30) It's a whole other topic to discuss. (00:14:32) But there's two major discussions and decisions that need to be had in my view on the Bitcoin front. (00:14:38) First is obviously agreeing a technology to upgrade to quantum proof encryption and wallet systems. (00:14:43) And then probably 70, 80% of the network will happily move across to that when that decision is made. (00:14:47) And then the second decision is what do we do with the lost coins, the 20 to 30% of coins, which are on really old addresses, (00:14:55) like Satoshi's coins, P2PK hash systems, and also any coins that, any coins have been lost or, just sitting in safes or just fail to upgrade in time, those will be taken with certainty by a quantum machine. (00:15:09) There's nothing we can do about it. (00:15:10) And so we need to decide as a community, do we just let that happen or do we initiate some kind of process to burn that in the code? (00:15:18) So there's a few two main discussion points that need to be, I think, seriously taken in the next 12 months. (00:15:24) Let's take a quick break and hear from today's sponsors. (00:15:27) Curious about online trading, but haven't taken the first step yet? (00:15:30) You're not alone. (00:15:31) And Plus 500 Futures is a great place to start. (00:15:34) The futures markets are moving fast, and with Plus 500, you can explore popular assets like oil, gold, S&P 500, Bitcoin, and more. (00:15:42) From crypto to commodities, there's always something happening. (00:15:47) The platform is super easy to use, so you can trade on the go right from your phone. (00:15:51) You can get started with just $100 and jump into the action. (00:15:55) See something interesting? (00:15:56) Once your account is open, you can trade it in just a couple of clicks. (00:15:59) And if you're not quite ready yet, you can practice with a free demo account. (00:16:03) No risk, no pressure. (00:16:05) With 20 years of experience, Plus500 makes trading more accessible than ever. (00:16:10) Check it out at plus500.com. (00:16:13) Trading and futures involves risks of loss and is not suitable for everyone. (00:16:17) Not all applicants will qualify. (00:16:18) Plus500. (00:16:19) It's trading with a plus. (00:16:22) They say every day your business is late to AI, you fall two days behind and the competition, they're only moving faster. (00:16:30) Fortunately, there's NetSuite next. (00:16:32) You probably already know NetSuite, the AI-powered business suite that securely connects all your data, financials, inventory, commerce, HR, and CRM all in one source of truth, trusted by over 43,000 customers. (00:16:46) NetSuite Next is the next huge leap because now AI is built to do everything you do. (00:16:52) It surfaces custom insights throughout your day. (00:16:55) AI agents work alongside you on the routine stuff. (00:16:58) And anytime you've got a question about anything, you just ask, like you're talking to a colleague. (00:17:02) And I use it, and really I think you should too. (00:17:05) For the first time ever, you can try NetSuite Next for free. (00:17:08) If your revenue is at least in the seven figures, go to netsuite.ai/tip. (00:17:13) Built for every industry. (00:17:16) As investors, we spend all day studying great businesses, but some of the best returns come from building one yourself. (00:17:28) If you've been sitting on a business idea, Shopify makes it easy to actually make it happen. (00:17:35) Everything you need to start selling is included and ready from day one. (00:17:39) Take the moment your first customer is ready to pay. (00:17:41) Shopify checkout helps more of them finish the purchase. (00:17:45) And when they come back, their details are already saved. (00:17:47) One tap and they're done. (00:17:50) And because Shopify handles the setup and the checkout, (00:17:53) you get more time to focus on what actually grows the business, plus the tools to do it. (00:17:58) If I were starting a business, I would absolutely use Shopify myself. (00:18:03) It powers millions of businesses worldwide, from names like Mattel and Gymshark to founders just getting started at shopify.com slash TIP. (00:18:15) With Shopify, nothing stands between your idea and a real business. (00:18:20) So go make it one. (00:18:22) Start your free trial at shopify.com slash TIP. (00:18:26) Start your free trial at shopify.com slash TIP. (00:18:32) All right, back to the show. (00:18:34) So where I want to start, I first want to push back on the timeline just to kind of provide a counter argument for people because a lot of people hear this. (00:18:43) They're going to immediately be like, oh my God. (00:18:45) And I think we kind of want a little bit of that for moving forward with like, call it BIP 360 in Bitcoin and get things moving in the right direction. (00:18:54) So I want to provide a counter argument for people to hear, but I also want them to understand the importance of everything that you just said and whether the timeline, (00:19:02) we don't know what the timeline really is going to be here. (00:19:05) But my first pushback would just be when I look at a lot of the people that are providing these accelerated timelines. (00:19:13) And by the way, I agree with the 2300 roughly logical qubits as far as like what it will take to break the elliptical curve cryptography. (00:19:22) I think that number is pretty accurate based on all the research that I've done. (00:19:26) So whether that is (00:19:28) 23,000 physical qubits to 200,000 physical qubits, I don't know, but it would be somewhere in that ballpark for people that are hearing numbers that are mostly in marketing jargon online to get the 2300 logical, you'd probably need anywhere from 20 to 200,000 physical qubits to do that. (00:19:48) But my pushback comes from everybody that's listed seems to have some type of financial incentive to either get more funding for their lab (00:19:58) to just kind of move along. (00:20:00) the entire movement of quantum as opposed to people that are outsiders that have a lot of expertise, which is really hard to find, by the way, because everybody that has a lot of expertise is deep in this and they have an incentive to make sure that it's moving forward and successful. (00:20:16) So that's the first thing. (00:20:18) And then the other counterargument or where I would push back, I'm just going to pull up a slide from a little bit of research that I did, Charles. (00:20:25) And what this is doing is it's showing the current layout (00:20:30) of like where we're at today as far as physical qubits for various organizations that have built a quantum computer, what the physical qubits are, and then what the logical qubits are today. (00:20:42) And again, this research isn't real extensive, but like finding anything that has logical qubits in excess of 24 to 28 is really difficult to even find where from my understanding, we haven't seen any (00:20:56) quantum processor that has exceeded 100 logical qubits today yet. (00:21:01) And I'm curious if that's what you understand to be true as well, Charles. (00:21:05) But the big one for me was it seems to be IBM is one of the front runners here. (00:21:11) What I had read was that they were going to have in excess of 100,000 physical qubits by 2029. (00:21:18) And off the IBM website, they're targeting 200 logical qubits by 2029. (00:21:24) And this is coming from, in my opinion, a company that is probably one of the biggest marketers in the space as far as like what it is they're going to do and when they're going to do it by. (00:21:35) And so four years from now, three years from now, they might be a 200 logical qubits. (00:21:40) And that's, in my opinion, probably their best case scenario based on what they're literally telling the market. (00:21:46) So I'm curious (00:21:47) how you view this and whether I'm out to lunch. (00:21:50) And again, I'm not really deep in this stuff. (00:21:52) I'm just looking at it really from an outsider's lens. (00:21:55) And I'm just kind of curious how you see that. (00:21:57) I think that's what we have to be careful with because if you survey, there's about 10 to 12 pure quantum companies that are public traded. (00:22:04) There's about another 20 like Google's, Amazon's, where they partially have a quantum team. (00:22:09) And then there's another sort of 30 private. (00:22:11) So there's about 60 roughly firms working on quantum at the moment. (00:22:14) And if you (00:22:15) do a survey, a lot of them are not very progressed, but some of the leading ones are very progressed. (00:22:20) And that's what we kind of need to be looking at. (00:22:21) So there's another slide now. (00:22:23) I can bring up a screen off that send later. (00:22:25) But IonQ is projecting 8,000 logical qubits in 2029. (00:22:30) More than you need to solve this. (00:22:31) CyQuantum is a private company, so they're not having the same incentive. (00:22:35) They're saying they're going to have a million physical (00:22:37) in 2028, which is way more than you'll need to break Bitcoin. (00:22:41) But what does that equate to in their logical? (00:22:43) So I hear the really big numbers on the physical side, but then they never say what their noise factor is, whether it's 10 to 1, 100 to 1, 1000 to 1. (00:22:52) They just could totally ignore that. (00:22:53) I don't have that in front in front of me, but if you go off the relative ratio for the others, it's definitely in the order of thousands. (00:22:59) So yeah, Guira is projecting 100 in 2026. (00:23:05) So 100 logical in 2026. (00:23:07) So then again, it's 30 this year. (00:23:09) So 3X. (00:23:11) So if you keep multiplying these numbers out again, the trend is linear. (00:23:14) So if we focus on the numbers today of 10 to 100 or 10 to 50 or 10, those kind of range of logical. (00:23:20) It doesn't sound that concerning, but the point is of the exponential growth. (00:23:24) And then OQC is saying they're going to have 5,000 logical in 2031. (00:23:30) So we're looking at like somewhere between 2028 (00:23:33) and 2031. (00:23:34) And we obviously don't need everyone to get there. (00:23:36) There don't need to be 1 firm there. (00:23:37) The other factor is that China is spending double the US on quantum. (00:23:43) And they're one of the latest super quantum machines that came out there was a million times more powerful than Google's. (00:23:48) And that was a few months ago. (00:23:49) So. (00:23:50) Do they publish everything that goes on in China? (00:23:52) We don't, you know, there's record-breaking capital being committed to this industry. (00:23:57) There's also 55 billion being committed to globally to quantum. (00:24:01) And some rumors that Trump's going to release an executive order on this, because obviously there's a critical urgency to be a quantum leader, to have quantum supremacy, because once you're ahead of the game in that, you obviously have a really significant power in terms of what we call Q day, which is unlocking secrets, potentially financial information and other hacking capabilities, of course. (00:24:23) So it's an informational warfare capability as well. (00:24:26) And that's why I think basically the allocation of money to this industry is only going to go through the roof. (00:24:31) And the other thing with these forecasts of qubits is that these leading companies have actually been beating their targets the last couple of years. (00:24:37) So they've been hitting their time frames early. (00:24:40) So they're not really, the firms I mentioned, they're not actually wishful thinking. (00:24:44) They've actually been beating that historical forecast. (00:24:47) So yeah, again, we don't know the exact number, but anywhere between the two to eight years with a really high probability in the four to five year mark. (00:24:54) And I think anyone who's kind of working in the industry will kind of confer that (00:24:59) That is the trajectory it's on and the tech improvements and tech advancements we're seeing every month and quarter are pretty breakthrough changes and capability and improvements. (00:25:09) So Charles, one of the things that I'm just looking at AI and AI specialty is being able to find patterns, right? (00:25:16) And when we look at one of the biggest issues, which we've talked about here is the noise factor, it seems like you could somehow apply AI to help dampen or try to figure out how to remedy a lot of the noise factors with respect to this, and which could accelerate some of these timelines in ways that we're not expecting today. (00:25:38) Is this something that you've read? (00:25:40) I mean, this is just an intuitive sense. (00:25:42) Is this something that you've read as being real or? (00:25:45) Yeah, I believe it was Rigetti a couple of months ago had an announcement, and this is I think the second biggest public quantum company in the US. (00:25:52) They basically said that they've been able to use AI to really fast track optimizations and how they're calibrating the quantum machines, right? (00:26:00) So where it would be a lot more manual and human driven, algorithm based. (00:26:04) but still slower, it can be the same significant speed improvements on that. (00:26:09) So AI helps speed up the development of quantum and then quantum ultimately will help speed up different processes for AI in the future. (00:26:17) So they really kind of interdependent and kind of grow off each other. (00:26:21) One of the things that you said earlier in the conversation that confused me a little bit, because when I was doing research on the entanglement piece of this, one of the things that became clear is you can't take (00:26:31) Let's say you could figure out how to do it with 1000 physical and it gives you, let's just say it's a 10 to 1 factor that gives you 100 logical qubits right there. (00:26:41) And then you kind of stitch those 1000 physical qubit processors together in order to build out a much larger quantum computer. (00:26:51) And what I read or what I think I understand is that's not how this works. (00:26:56) being able to kind of stitch together groups of 1000, 1000 physical here, 1000 physical there, doesn't get you over this curve. (00:27:04) They have to be completely entangled, all of the cubits in order to be able to solve these much bigger problems, call it like cracking the encryption on Bitcoin. (00:27:13) Is that true? (00:27:14) And if not, is there a way that you can partially do it or (00:27:20) Just help us kind of understand the mechanics of that. (00:27:21) Because I think for a lot of people, they'll start thinking in that direction because that's how normal day processors, you have dual core, you have quad core processors, and they're thinking that maybe they can apply that to quantum. (00:27:31) And I just don't suspect that it works that way. (00:27:34) Yeah, it is a bit different. (00:27:35) I'm probably not the right person to be getting into the technicals of the quantum engineering side before other businesses I'm focusing on. (00:27:43) But I suppose my high level comment would be that the announcements I've been seeing the last (00:27:48) from these firms is that they're seeing an improvement in error rates when they're adding qubits to the equation. (00:27:54) So it does have a scaling benefit. (00:27:56) And they're also seeing each year like reduction in error rates. (00:27:59) So it's very easy to focus and pick holes like in any problem and technology, right? (00:28:05) Same thing could be said for AI 5, six years ago. (00:28:07) Oh, it's not capable of this or it doesn't scale that way or the results are garbage, it's spitting out or it's got lots of downtime. (00:28:13) A lot of these things are parallels, I think with quantum. (00:28:16) And McKinsey, BCG, they're expecting multi-trillion economic value across industries within 10 years. (00:28:24) And as well, you've got QDA very highly likely within 10 years. (00:28:27) And I believe, as I said, based on those forecasts, it's sort of two to five year range. (00:28:31) And then if we have that, we have a bit of a hockey stick moment, a ChatGPT moment, if you will, in the sort of coming years, which it's very easy to focus on problems. (00:28:40) And humans are really good at generally solving problems. (00:28:42) And we're programmed to think pessimistically and then focus on problems. (00:28:46) But usually the innovation of these kind of things will win. (00:28:49) And as I said, it's really looking at that log chart where the progress is exponential and faster than Moore's law that I'm confident a lot of these things are just going to be continued to be solved on as they have been each year. (00:29:00) I'm going to pull up a chart. (00:29:02) We're going to transition a little bit more into Bitcoin and how this impacts Bitcoin. (00:29:06) And then I would be really curious going beyond Bitcoin, what you think some of the implications are. (00:29:10) But to frame this up for people, I've got a chart here that lays out the type of (00:29:16) that the public key, private key relationship that Bitcoin is built around for all the addresses and the output type that you have. (00:29:25) When Bitcoin was first founded and stood up, we were using P2PK and this is pay to public key. (00:29:32) And this is the primary set of keys that are the issue. (00:29:37) And with my research, and I'm curious if this is what you also have found as well, Charles, is it's about 25% of the Bitcoin (00:29:45) that currently exist are in this key type, which makes it vulnerable to Shor's algorithm if a quantum computer with the size that we talked about earlier existed. (00:29:56) So that's a significant portion. (00:29:58) Now, I think it's also important from 2010 to 2017 that they went to a pay to public key hash. (00:30:06) So you would take that public key, you would hash it so that it's not known what the public key is unless you actually sign a transaction. (00:30:14) And so anybody that has, and this is a majority of the Bitcoin, 75% of the Bitcoin are already in this P2PKH or higher configuration. (00:30:25) And so it would be protected in the interim as long as you didn't spend anything that would be protected. (00:30:33) Interim, very interim. (00:30:37) Giving you a little bit of assurance, I guess, is the way to frame that. (00:30:41) But I wanted to put this slide up so people can kind of see the timeline of when these different types of key outputs were, or the address outputs were used and what they've migrated to through the years. (00:30:53) And let's talk about, Charles, what the solution is, because people are looking at this, they're probably hearing this conversation and saying, oh my God, this sounds really scary. (00:31:04) But there's BIP 360. (00:31:06) Beast Hunter was the main author of this and it's out there for public purview to audit and look at and as a soft fork to Bitcoin, meaning nodes that are running the older software, there's no issue with running the older software if people would upgrade or migrate to this new version that he's proposing with the BIP 360. (00:31:27) But talk us through what that is and how that would work and kind of in application, what would that mean for people that currently hold Bitcoin and their own keys? (00:31:36) to migrate over to something like this. (00:31:38) Yeah, I think, so I agree with you, the 25% ballpark figure for the earliest key hashing process of the P2PK, I think it was here on the screen at the top. (00:31:48) So it's Toshi's coin and it's about 125 billion of those and then other wallets. (00:31:52) The key thing with that is that when they write the blockchain, it's exposing or showing their public address. (00:31:57) So everyone who is in Bitcoin has a public address and a private key and a public address (00:32:04) obviously is your wallet and then the private key allows you to access it and move funds. (00:32:08) If you know a public key, then a quantum machine can theoretically kind of back calculate what your private key is. (00:32:15) And technically computers today could do that or just take infinite amount of years and you'd never get that right in our lifetime. (00:32:21) So that's not a risk. (00:32:23) And that's how all encryption essentially works today. (00:32:25) But given what we talked about the quantum, it can configure multiple options at the same time. (00:32:29) It can close in on a solution to the private key (00:32:32) very quickly, again, once we get to that sort of 2,000, 3,000 qubit level. (00:32:36) So those first wallet address systems like the Stoshy coins are exposed, but it's also any public keys that are published. (00:32:45) So a lot of the exchanges, for example, have their wallets and public address is no one. (00:32:49) So again, all those can move across to a new system like Bit360 and the Quantum Bit. (00:32:57) This is again, the code improvement suggestions of a couple of Bitcoin developers. (00:33:01) So there's solutions to get the active addresses across, but there are still other public key exposed wallets which may not necessarily move across in time. (00:33:11) So yeah, as you kind of mentioned, pressing the solutions to this, especially for the wallets that are active and managed and can move across. (00:33:19) My point is that Stash's coins, largely everyone believes is not going to be moving those coins ever again because maybe not around anymore. (00:33:27) And a lot of the other early (00:33:28) coins are just lost, right? (00:33:29) People lost their wallets, they lost hard drives into landfills and all sorts of funny stories from back in the day. (00:33:35) So a lot of those coins will be unlocked no matter what we do by a quantum machine in that sort of two to eight-year range. (00:33:42) And that's sort of 20 to 30% of supply, we don't know the exact number, but in that region. (00:33:47) And that's again, as I mentioned, that's something we need to discuss in the community and how we're going to manage that. (00:33:51) For the quantum solutions that are out there, the bits, my kind of (00:33:55) take on it is I'm not here to say what's the right solution. (00:33:58) there's a few proposals out there. (00:34:00) I just want to get the community talking about this and closing in and zeroing in on a consensus because as you and I know, consensus in Bitcoin is a viable and takes years. (00:34:11) It's a mess. (00:34:12) You know, I basically want to initiate like block wars, but quantum, because I'm basically just concerned about the timelines at this point, right? (00:34:20) So technology solutions are there. (00:34:22) And I think if we all agree today on the solution, we could (00:34:25) I think we could agree and get it out in time. (00:34:27) But the problem is that if we did agree today, the lead time to get everyone across to this new wallet infrastructure or the soft fork or hard fork, whatever it is, going to take 6 to 12 months. (00:34:37) And that's limitations of transactions throughput. (00:34:40) So if you look at the flow through of Bitcoin in 30 days, and this is capped based on 10 minute block times, number of transactions the network can actually process. (00:34:49) If everyone with, say, over $100 in their wallet was to say, I'm going to move across to a new wallet, which is this quantum-proof encrypted wallet, that's going to take 30 days, assuming no other traffic. (00:34:59) If you want to do a test transaction, as we usually do, because you might have a significant sum of money on there and you don't want to lose it. (00:35:05) then double as 60 days, right? (00:35:07) Add in organic traffic, probably double it again. (00:35:09) You're basically at six months in a best case scenario of everyone like agreeing and moving at the same time. (00:35:15) So where I get concerned is that we know consensus takes time, probably best case a year, which is why I'm basically posting all the time. (00:35:22) I want to see a solution agreed in 2026. (00:35:25) If we get it solved in 2026 and agreed, then we might have a year to get to 2027 to roll it out. (00:35:31) And that's at the kind of leading edge (00:35:33) risk frontier, I suppose, for when a quantum machine could break Bitcoin, right? (00:35:39) Hopefully it's further out. (00:35:40) But if we have the kind of blase approach that it might be four years, it might be 10 years or 15 years, if we're one minute too late on upgrading this and getting everyone across, the whole trust system of Bitcoin is built on its trusting the code and its security, right? (00:35:55) Like it took us 16 years for Bitcoin to get to 2 trillion. (00:35:59) And it's hard to gain trust and easily lost. (00:36:01) So if we were to say 10, 20, 30, or whatever percent of supply unlocks all of a sudden over a 12 month period, whether that be in two years time or three years time or five years time, and we hadn't solved on this, I think the whole trust system network collapses. (00:36:15) So basically I'm just trying to sound the alarm on all of this because we need to get to consensus in my view next year. (00:36:21) to roll out and deploy everything within two years from now so that we're on the leading edge and we're not one minute late. (00:36:27) Let's take a quick break and hear from today's sponsors. (00:36:29) One part of being an investor that I don't think gets enough attention is how hard it can be to continue to improve as an investment researcher. (00:36:38) And for myself, I often find that when I finish a great conversation with some industry expert or fund manager, my head is full of ideas. (00:36:45) But by the time I sit down to write it all up, half of them are already gone. (00:36:49) That's why I've been using Plod Note Pro. (00:36:52) It's a small device that sticks to the back of my phone and captures the conversation and hands me back a clean, searchable recap. (00:37:00) And so the key points, the follow-ups, the things I usually want to act on, it has all of that. (00:37:04) And that allows me to stay present in the room instead of scribbling notes that I won't be able to read back later. (00:37:10) And I notoriously have very bad handwriting. (00:37:12) And so it's changed how I prep and how I follow up with investors. (00:37:17) It's also built for people who take conversations (00:37:19) Seriously, enterprise grade security. (00:37:21) So if you're recording calls with clients or industry contacts, that's covered too. (00:37:27) So if you live in meetings, calls and interviews, we'll give it a look. (00:37:30) Go to plod.ai slash WSB and use code WSB for 10% off. (00:37:36) That's plod.ai slash WSB, code WSB. (00:37:41) And always get consent before you record a conversation. (00:37:44) If they say every day your business is late to AI, you fall two days behind and the competition, they're only moving faster. (00:37:52) Fortunately, there's NetSuite Next. (00:37:55) You probably already know NetSuite, the AI-powered business suite that securely connects all your data, financials, inventory, commerce, HR, and CRM all in one source of truth, trusted by over 43,000 customers. (00:38:08) NetSuite Next is the next huge leap because now AI is built to do everything you do. (00:38:15) It surfaces custom insights throughout your day. (00:38:17) AI agents work alongside you on the routine stuff. (00:38:20) And anytime you've got a question about anything, you just ask, like you're talking to a colleague. (00:38:25) And I use it, and really I think you should too. (00:38:27) For the first time ever, you can try NetSuite Next for free. (00:38:31) If your revenue is at least in the seven figures, go to netsuite.ai/tip. (00:38:36) Built for every industry (00:38:39) ready for every boardroom, netsuite.ai/TIP. (00:38:43) Curious about online trading but haven't taken the first step yet? (00:38:48) You're not alone. (00:38:48) And Plus 500 Futures is a great place to start. (00:38:52) The futures markets are moving fast and with Plus 500 you can explore popular assets like oil, gold, S&P 500, Bitcoin, and more. (00:39:00) From crypto to commodities, (00:39:02) There's always something happening. (00:39:04) The platform is super easy to use so you can trade on the go right from your phone. (00:39:09) You can get started with just $100 and jump into the action. (00:39:12) See something interesting? (00:39:13) Once your account is open, you can trade it in just a couple of clicks. (00:39:17) And if you're not quite ready yet, you can practice with a free demo account. (00:39:21) No risk, no pressure. (00:39:22) With 20 years of experience, Plus500 makes trading more accessible than ever. (00:39:27) Check it out at plus500.com. (00:39:30) Trading and futures involves risks of loss and is not suitable for everyone. (00:39:34) Not all applicants will qualify. (00:39:36) Plus 500. (00:39:37) It's trading with a plus. (00:39:39) All right, back to the show. (00:39:41) So Charles, I think you're being really conservative with these numbers that you're saying as far as how long the migration would take. (00:39:49) Because I've run this math back when I made my video back in January. (00:39:54) And then I just, while you were talking, I ran it again because