What Happens When Quantum Computing Actually Works?

0:02Speaker 1:Bloomberg Audio Studios, Podcasts, Radio News.

0:18Speaker 2:Welcome to Marion Talk's Money, the podcasts in which people who know the markets explain the markets. I'm Maren Sumset Web. This week I was begining with Daniel don Steinberg, co founder and partner at eden Base, an investment firms that invests in frontier deep tech. I invited Daniel on the show because I had a really interesting conversation with him about quantum computing and just how close it might be. During our conversation, we talk about ai future of and what it really is. We also talk obviously about quantum computing and what it might mean for our futures, and we also cover exactly how one might deal with the future that quantum might bring. Spoiler alert read some philosophy. Daniel, Welcome to marind Money Pleasure.

1:01Speaker 1:Thank you for having me.

1:02Speaker 2:Will you tell me a little bit about what Edenbased does and then we'll take you from there.

1:07Speaker 1:Well, in Bases, three partners got together, all with very different backgrounds, but sharing a common theme, which we were all entrepreneurs and we wanted to invest our own money but also create a platform for two things. One to allow us to hire a bigger team to make decisions in a world that we thought was becoming incredibly complicated. And secondly, one of my partners created Technician for David Cameron level thirty nine, which is the fintech ecosystem. And when I really explored what he had done, I realized that ecosystems solved a few of the challenges I saw with what was about to happen. And so Edenbase is a is an investment vehicle and also an ecosystem where we help with adoption of new technologies. We call it investing in a future we can be proud of, which actually came out of AI weirdly in our three years go.

2:00Speaker 1:It's not sustainability, it's a future we can be proud of. Okay.

2:04Speaker 2:I like that. That's better than sustainability. Is so vague, isn't it? Okay? So the thing I really wanted to talk to you about it and I think I invited you want to talk about, was quantum computing. But before we get onto that, I wanted to talk to you a little bit about AI because when we were chatting the other day, right you and I and we were talking about various things, and I said to you, is AI the correct name at all for what we think of as AI, because what we're using at the moment is lllm's Large language models. And anyone listening who isn't entirely sure how LMS work, please go back and listen to some of our previous podcasts if you've had lengthy conversations about all these things. So when we talk about AI, we're talking about these large language models, and they're not artificial, they're man made, and they're also not really intelligent, are they.

2:47Speaker 2:So we we're using the wrong phrase in the beginning.

2:51Speaker 1:I think we use the wrong phrase because that's how we referred to technologies such as these, which are we building artificial intelligence And the history of compute, certainly for the last twenty thirty years, has been exponential, and m's are a continuation of that exponential and therefore they fit into the bucket of artificial intelligence. But you're right, the word artificial is not correct and the word intelligence is not correct for what we have built. We have built incredibly powerful technology. I mean, all the technologies we've built have been incredibly powerful at the time. This happens to be even more so, and it's an opportunity and threat for what we have as our society and the way we work is enormous. But yes, you're right, they don't fit what we would classify as intelligence, which is a biological characteristic. These are programmed characteristics. The way they mimic intelligence is they have access to an enormous amount of data, most of which was generated by humans, and therefore the ability to write cogent arguments based on human intelligence is what they do.

4:11Speaker 2:I have thee conversation with one of my nieces the other day about how you can tell what is Ai writing and what isn't Ai writing? And I was explaining to her that, of course, the way that Ai writes, the way that an LM write is actually just the way that old people write because they're using our writing. There used to be a hallmark of my writing style was, you know, short sentences and dashes, This is how I write. So is it Ai writing or is it someone in their fifties?

4:38Speaker 1:Well, a good question. You know, it has access to a lot of information, and one advantage I have I'm writing a second book at the moment is the fact that I've written a first book. It knows my first book, and so when I ask it to write in my and my co author's style, it can copy that. However, I do find the style we wrote the first book in is not the what style we writing the second book in, but it can mimic lots of styles. Whilst it is certainly based on the data that we have, it is able to create new things, and so if you explain exactly what you want from it, it will do pretty much exactly what you do, as long as that's within a framework that it can understand.

5:22Speaker 2:When you look at where we are at the moment with llms, and we think about, say, for example, the legal profession, and that's the place where everyone says, well, lllms will fully replace lawyers in no time at all. How do you see it playing out?

5:37Speaker 1:Well, I think that's a very plausible scenario. Going back to my book that are in twenty twenty and twenty one, we use the legal profession as something that llms are about to wreak, havocate, as they are in accounting, as they are in management consultancy and a lot of those rule based roles. The reason that will happen is, I think for two reasons. The first is that even though you may argue or not whether it is better than the best lawyer. It certainly has access to more information than the best lawyer, because however much I read, I've got one hundred and eighty six hours a week, I can't read everything. The second thing, and we talk about this, which is, firstly, if you're a legal firm today, why would you hire junior lawyers to do things that lllms can do? And if you do, it's almost like you're doing it for the future of the industry rather than your personal success, because you might as well replace it.

6:32Speaker 1:And we say, if that happens, then in fifteen twenty years there are no junior lawyers. The second thing is, as we become more LLLM focused, the only thing that can unpick what lllms are writing eventually becomes another LLM, and therefore you migrate to that. So if the court system, for instance, decides to replace certain parts of it with AI, then people will be writing AI to deal with the AI, and eventually we will have a different legal system which will be based on what computers are able to comprehend, like a code for a computer, rather than what humans are going to be able to understand. I see that as as very likely the other thing that we find, and I've been enforcing this at even Base for a long time, is we do not send contracts to lawyers if we can do it ourselves. I used to do that with my first startup many years ago. So what it meant is our legal bin is probably five percent of what it used to be. And that is also a problem for the legal industry.

7:35Speaker 2:As long as you are fully confident in your LLM.

7:39Speaker 1:It depends on the risk factor. So an example is I invested in a Spanish company two and a half years ago and I was putting a small investment in. It wasn't worth sending to a lawyer, but I put it through an LM and it took the Spanish contract. And this is two and a half years ago, so they weren't as good as they out there, and it gave me a plausible scenario not have been all right, and I was able to rather just signing it and saying, well, I don't care. I was able to write to them with a few questions and they answered those, so it was better than doing nothing. And as they get better, your risk appetite becomes greater. Secondly, the risk appetite changes as you are able to deal with things yourself, and I think that's really powerful.

8:25Speaker 2:So what are the limits to the LM model. And one of the things that we've been looking at, and we've done a few podcasts on this is the idea that you can use an SLM, a small language model instead of an LLM, and a couple of years ago that didn't work so well. But the new study at from Stanford University and someone at pameel Iberium has been through it, pointing out that these small language models that you can run on your laptop, you can even run it on your phone, and you compare the performance of those with an LLM. The LMS, of course what we need the massive data centers for you compare these and in fact the results are pretty much as good, pretty much as good. So if you want a fairly straightforward AI model, and you want it to be private and contained in your own laptop or computer, and you want to use less energy, which is also than crucial, then you can just have an SLM on your laptop. You don't need an LLLM, which rather suggests that in some parts we might be going down the wrong path with full focus on LM's massive data centers, etc.

9:31Speaker 1:Well, I haven't read that report, so I can't send it to you comment particularly on that. Now, what I can say is two things. One is straight lines are rare. So when I was starting to code many many years ago in the derivative trading industry, I've built derivative trade technology, and the early aunties we worked on mainframes and the only people that had desktops and the people that wrote letters. And within five to ten years as I finished my career, before I started my first startup, everybody had a desktop and you were doing everything locally. And when cloud came along, Actually I'm not bad at reading the future, I was surprised.

10:08Speaker 1:I said, why do people need the cloud? You know we can do it all locally. And then what I failed to recognize was the onset of mobile phones, and mobile phones had limited power, and therefore the cloud was very useful. And so there are phases in which SLMs will be very, very useful. But I don't see that necessarily meaning that cloud huge cloud data centers aren't valuable. The other thing, of course, is as we build new technologies, and SLMs are based on the current LLLM technology, which is based on binary compute, and it is based on GPUs and it is based on existing storage. A mobile phone could do that. And the segue into quantum for instance, is a quantum computer is not a binary system. Daniel explain quantum computing to me, quantum computing is a break from the past. That's the first thing, and the sort of the most comprehensive way to describe it is. One hundred years ago mathematicians created quantum mechanics and quantum physics, and it described the way the universe operated extremely well, better than they had before, and they were able to write beautiful mathematics and described how subatomic particles worked. In

11:25Speaker 1:nineteen seventies, Richard Feynman the physicists suggested that we could actually control them, and then in the eighties IBM started trying to control them. And what that meant is they were able to instead of operate binary bits i e. Ones and zeros, they were able to operate in effect probabilistic bits, so they were all combinations of ones and zeros. And what that meant was we were able to do two types of compute or in theory, because no one's built one that is big enough to do anything really meaningful, or until very recently, they haven't. It does two types of things that binary computer is very bad at. The vers is optimization. So imagine a good example might be a table plan. If you have five people sitting around a table, you have one hundred and twenty five combinations.

12:19Speaker 1:If you have ten, you have three million. If you have twenty five people, you have one with twenty five zeros on the end of it a combination.

12:28Speaker 2:This is why it's so hard to make table plans.

12:30Speaker 1:Exactly, it's impossible because twenty five people is more combinations than the biggest computer in the world could compute in the history of the universe. If we'd started it in the beginning, it still wouldn't have come up with.

12:43Speaker 2:It gives you a new respect for wedding.

12:45Speaker 1:Planners, doesn't it exactly? Exactly? That's optimization. The second thing it's good for is simulation. And simulation is where we have the ability to simulate natural mods. So, for instance, the way that a chemical reaction happens, the way that a material actually behaves at the moment. With our data, we can approximate it because it's ones and zero's a bit like a CD and a vinyl A cd is ones and zeros a. Vinyl is the true wave. Quantum is operating at the vinyl level, and it is able to model the way that a new drug will interact with your body. I would use the word perfectly, but we don't know because we haven't We haven't understood the next levels down and the next ovesalguma and a much better resolution than you could with a binary compute. So for things like material discovery, drug discovery, how chemical reactions happen, like the nitrogen bond to make ammonia, we use in seven percent of the world's energy creating ammonia for fertilizer.

13:55Speaker 1:If we could understand actually how that bond was structured and how you could break it, potentially you could find out how it works and use a fraction of that energy. And the reason it's so important is optimization and simulation are two of the areas that we are very bad dealing with as humans because we don't have the tools. And we're about to create systems that can do that for the first time. So if you ask the quantum companies, they say they actually have machines that work. Now.

14:25Speaker 2:Okay, So when I was about to ask you what you meant by about but you say that, the companies would say, this is here already usable stable, it's.

14:34Speaker 1:A great it's not a black and white. So there is something called a cubit, and a cubit is the equivalent of a bit in computing. To run a quantum computer, you need cubits and you need to connect cubits together. And what confuses the picture more and I think people have to understand this. When people use cubit, you have to ask is it a physical cubit or a logical cubit, and they don't say which is which. The difference is enormous. So a physical cubit is a working cubit. A logical cubit is one that you can control and use effectively.

15:11Speaker 1:And there is enormous difference, maybe one thousand to one. So certain companies will say they've got a one hundred or one thousand cubit machine, but that's not a logical cubit machine, and therefore it's to a degree not that powerful. And other companies like Quantinium will claim they've got a fifty two cubit machine, but it's a logical cubit machine, which means it's very very powerful.

15:36Speaker 2:I don't understand the difference between these two cubits. Do I need to understand the difference between these two cubits.

15:42Speaker 1:You only need to understand it if you're investing in the space, because if you're matching two things that are not equal, then you need to know that there is a difference between them. So if I open the paper and it says company A has a thousand cubits and Company B has ten cubits, which is what they do in the press, those ten cubits may be logical cubits, and the thousand cubit machine is physical cubits, and they have zero logical cubits, And that is the only reason to understand it. You don't really need to understand what that means.

16:15Speaker 2:Okay, So the logical cubits are the much more powerful ones.

16:19Speaker 1:They're the ones that are error corrected and work reliably. Okay, that's what you need to know. The point is, up until twenty twenty four, no company had announced a logical cubit. In twenty twenty four, someone announced one, and then in early twenty twenty five they announced ten. Continuum, who are the half British half American company announced fifty at the end of last year, fifty is starting to become meaningful. The one hundred started to become useful. And so if you look at that progression of one to ten to fifty over an eighteen month span, you're looking at one hundred within the next year or so. And then you have a machine that is useful.

17:07Speaker 2:Useful for what initially? So we've got a hundred logical cubits. See I know or I know what these things are. Now we've got one hundred logical cubits. We've got a machine and it's useful. But what will it do for us initially? What will it change? What will we understand that we didn't understand before.

17:25Speaker 1:I don't think we will particularly be able to crack anything new because traditional compute, especially traditional compute with AI, is phenomenally powerful. And therefore, even though these things are meaningful, can they do anything more significant in a wide range than where we are with AI today? Probably not. As we start moving up to the hundreds, you know, the three hundred, four hundred, that is the point where we will be able to potentially discover new drugs or discover new materials. Those are the sort of numbers at which it becomes very interesting.

18:07Speaker 2:Okay, and this is partly down to sheer speed.

18:09Speaker 1:It's not the speed, it's the number of variables that you can hold. So each cubit can hold a variable. If you can only hold fifty variables, it's limited what the model can do. If you can hold one thousand variables, it's quite powerful because it's factoral, So every cubit doubles the model in effect, like that five, ten, twenty five that I was talking about. It's a factoral number. So adding cubit it sounds like it's linear. It's not. It's nonlinear.

18:41Speaker 1:The numbers that people bandy about, and let's put it in a bandieback, somewhere in the early thousands you will be able to reach q day, which is breaking encryption. So those numbers are maybe six seven years away at current.

19:00Speaker 2:The day when everyone's bitcoin becomes useless, right, worthless, because while the encryption is broken.

19:06Speaker 1:It's very complicated with bitcoin. Actually it's not such an obvious thing. The underlying technology is not necessarily impacted. What is impacted is the wallets. You could potentially break the wallets if you hadn't upgraded them, So it's complex. So the people that have access to their wallets, could upgrade them. The problem with bitcoin is you've got millions and millions of bitcoin out there. For instance, it's a Toshi wallet of a million that cannot, as far as we know, cannot be accessed, so those are vulnerable. The thing I always say to the bitcoin community. What I say to them is if I have a quantum computer that can break bitcoin, Firstly, who is going to sell it to me?

19:49Speaker 1:Because whoever develops it will be under enormous regulations won't be able to just buy one. And secondly, if I wanted to cause serious damage, I would not be going after bitcoin because it's too small an industry. I would be going after taking down some regional banks and bring it. If you want it to shorter market, which is the only way you make money on it, it's shorting. So so bitcoin is probably in the top thousands of things you would go for, but you will be small to care, too small to care. The bitcoin community cares because all their wealth is tied up in a single asset. They tend to be very hyper focused on that asset, and they're aware of the danger. The problem with most people is they are not aware of the danger because they're not technical, and so most businesses are not considering the quantum threat. Now, my argument would be they probably don't need to because most of them operate on Microsoft or Google or whatever, and they're very aware of the quantum threat, and so most of their technology will be upgraded automatically.

20:52Speaker 2:Okay, So we get to the point out maybe ten years whenever it is when we get to this QDA, and the first thing that it can have then is we get to the point where that level of encryption becomes pointless. But companies such as Google et cetera already protected against that. So what next? What's the next thing that we see happening that quantum computing will change around us?

21:15Speaker 1:I think QDA will be scary. I think what next with quantum is it's a very different animal to AI. We have to look at what it does. It's not likely to be a consumer application for the foreseeable future for two reasons. First, it's very complicated to use, and secondly, it's going to be supply restricted for two reasons. One, they're very difficult to build, and secondly, the regulators are looking at quantum already and they're not going to allow you to buy or access a quantum computer. I think what changes is different. What changes is assuming they are supply restricted, and assuming they do what we've discussed, which is optimization and discovery. Both of those are fundamental to business optimization in terms of one percent saving in logistics or in farming, or in weather prediction or any of these things is a huge competitive advantage. The second thing is, in the world that we live where intellectual property is protectable, the second person that discovers something has no value. It's the first person that discovers it. So if I'm a pharmaceutical company and how I have access to the biggest

22:35Speaker 1:and best quantum computer and no other pharmaceutical company does, my competitive advantage is enormous because I'm out there discovering drugs on a daily basis or an hour however long it takes to run the thing, or an hourly basis, and none of my competitors do. And if they're two years behind, then I've got a two year free run. And because these systems are so difficult to build, you can't just go and find another competitor and say, okay, well, this drugged company has a four hundred or one thousand logical cubit machine. Will you build me one? They won't be able to.

23:12Speaker 2:So does that lead us into a new age of monopolies?

23:15Speaker 1:I suspect again the regulators will be on it. But it leads you into a winner takes all scenario. It turns a lot of companies into, in effect, the tech companies. I mean tech companies are renowned for winner takes all. The biggest search engine, the biggest social media way before that, the biggest word processing software, the biggest spreadsheet. They always trend towards standardization, and standardization initially creates monopoly or standards and monopolies, and eventually doesn't because everybody can hook into them.

23:46Speaker 1:I remember the early days of word it's the person you send it to who didn't have word. It was impossible. But now you send a word document to anybody and they can open it in anything they like. So there is going to be this change, and I think that's what makes quantum so valuable because what will likely have happen is people will realize over the next two three years that these machines are either available or on the cusp of being available, and if you are not building today to be ready for them, it will take you so long. Therefore, you need to be investing incredibly heavily to make sure that you are not the Kodak of the world and that you are the digital camera of the world. I mean, it's not a perfect analogy, but it makes sense. And so what we foresee happening very much with quantum. It will be the same cycle as the Internet and blockchain and AI, but it will be for a different reason. The amount of money that starts going into the industry will start to be huge, and the chatterpt moment will be the realization of big banks, or of big farmer companies, or of big logistics companies

24:52Speaker 1:or big farming companies that they are not going to be the winner and they have to start investing in this now. And you look at the banks. Actually, the bank's very interesting. Most banks, big banks have a quantum department and quantum team. And yet I would argue that finance, whilst probably the most valuable industry that quantum can go for in terms of raw cash day one, is a long way from having quantum supremacy because you need so many cubits.

25:26Speaker 2:But when you say a bank will have a quantum team, a bank is not developing the machine. So a bank's quantum team is doing what just watching IBM all the time, building building systems that can use the quantum machine at a later date.

25:43Speaker 1:They're doing three things on the whole. The first is they are investing in quantum companies, so JP Morgan is a big investor in Continue, the leading quantum company, because they want access to it. The second thing they are doing is they are building algorithms that they can tell on traditional compute that will be ready for when quantum comes along. And the third thing is they are getting access to basic quantum computing. And if you go onto an Amazon bracket, you can rent a quantum computer. It doesn't do very much, but they are starting to test quantum algorithms on cubits because they know, like everybody, that a machine is made available day two, you're not using it.

26:28Speaker 1:It'll probably take you two or three years before you're up to speed. So they're doing a lot of that work now in readiness for when that happens.

26:48Speaker 2:Really, the great power of the next phase of the technological revolution is the interaction between quantum and what we're calling AI.

26:57Speaker 1:Look. AI is an umbrella umbrella over all the other technologies. One of the things that I strongly believe is the convergence of technologies is far greater than adding them together. AI sits on top. You've got underneath that, you've got probably quantum, You've got the data protocols. I used to be a believer in blockchain, not so much anymore. But how do we handle data? How do we handle better data? Different data? And then under that you have three other things.

27:27Speaker 1:But the AI, what we call AI, is the control layer, the orchestration layer that's just on top of all of it.

27:33Speaker 2:Okay, Now, who's good at this? Because one of the things that we've seen over the last decade is we've seen who's good at AI in terms of countries, right, so America, China, Israel, etcetera. Who's good at quantum? Who's going to win here?

27:48Speaker 1:It sort of breaks down as twenty five to twenty eight percent of the US that we've looked at, twenty five percent UK, twenty five percent Europe as a whole, and twenty five percent to the world. China is probably most of that twenty five percent. So if you look at that, the UK is in a very very strong position. And the reason is we tend to have very good quantum expertise here and very good material science expertise. And we've been looking at quantum for a very long time.

28:17Speaker 1:And that's why Quantinuum, which is part owned by Cambridge Quantum, it was emergent between Cambridge Quantum and Honeywell Quantum is still located in the UK and a lot of their brains are still still in the UK, and they are likely because we don't know what everybody is doing, certainly in China, they are likely to be the most advanced quantum company in the world.

28:40Speaker 2:So how does someone who's stayed with us so far thank you listeners for staying with us. I know this stuff is not immediately easier than non titans among us. How can we be quantum ready, both not as an investor, but also as an investor well as an investor.

28:56Speaker 1:The one of things about quantum is there are quantum companies listing and secondly, most of the big tech players are starting to explore significantly quantum. So if you look at Microsoft, Google, Amazon, they have big quantum teams. If you look at some of the other companies like Cisco and in Nvidia, they are investing significantly in quantum already. So if you want exposure on that, there are those You've got companies like IBM and Honeywell who actually have significant quantum machines already. IBM had definitely have very powerful quantum Honeywell is part owner of Quantinuum, which is, as I said, considered the leader. And then we have seen over the last four or five years a number of pure play quantum companies listing, particularly on Nasdaq. And so if you want to invest in the base layer, which is how you build the actual quantum compute, there are probably five or six other companies you can invest in as a retail investor, But the more interesting area is clearly the private markets, because the private markets are in the layer above the actual quantum cubit. They're the people

30:18Speaker 1:that are building the connectivity, the networking. And if you consider quantum a little like electricity, the people building the machines are building the generation, the wind, the solar, the gas, the oil, et cetera, the ways of generating. But you've got to connect them together. It's no point just having a generation station in the middle of thewer So what we're going to see is as those companies start building powerful quantum computers. We're going to need to put them into cloud data centers. We're going to need to network them together. We're going to need to network them to the existing infrastructure we're going to need to store quantum data, and we can already see those starting to be built.

31:00Speaker 1:That area, to me is the most investible at the moment, as as if you wanted to invest in space.

31:08Speaker 2:And there are a variety of ETFs already, both in Europe and in the US that list themselves as quantum ETFs. Was that a reasonable way for an ordinary investor to get a little exposure to this space or is that just filled with junk?

31:22Speaker 1:When I looked at them last six months ago, there were very few quantum companies in there. Now that will have changed a little bit because a portfolio approach, I think investing in the big tech companies and the companies that are pure play quantum companies as a portfolio approach is not a bad approach. You can probably build up ten fifteen positions. If there was one or two, I would say not. And I think you will see over the next year there will be much more interest in floating listing quantum companies, so that will be in the space, so that would be my preference. That's what I do.

31:56Speaker 1:Some companies get acquired by the bigger companies. Ion Q, for instance, is acquiring lots of companies because they have something in there that they really need. So even the ones that are less sophisticated in the number of cubits or their customer base in the photonic space, for instance, some of those are going to be incredibly valuable because of their networking capabilities that these bigger companies are going to need, and because it's going to be this asymmetric advantage, a small time lead is incredibly valuable. So these companies, many of them will have enormous value and many of them won't. But it's quite difficult to determine analytically which ones those are going to be.

32:38Speaker 2:What could go wrong with all this? It all says absolutely marvelous. You make me very excited about the future. What could go wrong here?

32:45Speaker 1:The big challenge will be that there are scientific problems that come up that we cannot scale as fast as we want to, and therefore we have a massive delay in delivering these technology. I don't see that happening, but it's not unlikely. The second thing weirdly is that these companies become too big too quickly. I e. They don't go from fifty to two hundred, they go from fifty to two thousand or five thousand, and suddenly the regulators say, these systems are not going to be available to people.

33:21Speaker 1:They're going to be military machines, and companies that really need access to them for specific things like material discovery or pharmaceutical discovery have to go through a firewall. They have to give us their software, and it grows slowly because of that.

33:39Speaker 2:Isn't that why you might run into geopolitical differences in that you might have a regulatory system like that, for example, in the US, but you might not have one in China.

33:49Speaker 1:That's true, but I suspect if China develop quantum computers of that scale, they're not going to release them in the commercial market anyway. It's not a great example, but it's an example that I find usefulness. If I've developed a nuclear bomb, I could sell it to lots of people, but I'm not going to.

34:06Speaker 2:Okay, brilliant, right, Okay, my brain's about to explode.

34:10Speaker 1:Daniel.

34:11Speaker 2:What haven't we covered in this area that we should.

34:13Speaker 1:Have anyone that has heard about quantum and doesn't look into how it impacts their operations or what they do, is doing themselves an injustice. And I think if you demystify quantum by saying it doesn't matter how my iPhone works, it doesn't matter how TCPIP works. No one says that. They say, how does it change what I'm doing? I think quantum's actually very approachable. There was a quote I heard in twenty twenty two from the deputy head of it for the US Air Force who said QDA is almost closer than it will take us the time to fix the problems that we have. And that is really how you need to look at it, which is there's an opportunity in a threat, the time to get ready for the opportunity and deal with the threat is significant, and therefore you need to look at it now and how it's going to impact you.

35:14Speaker 2:Brilliant Daniel, I'm going to ask you Krito that I haven't after for a while. That's got a bit boring further the old fashioned, But I think we might be in the correct zone here, which is that given the choice over a ten year period, bitcoin or gold.

35:28Speaker 1:Wow, I would probably say gold. Now the bitcoin industry has been built on hype. It went up to one hundred and twenty five thousand, it's now sitting around sixty. I'm still a holder of bitcoin. I sold most of my holdings in twenty twenty two, but it's going to require so much money into the system to start pushing it up to those numbers again. However, to be honest, I don't own any gold, and I do own bitcoin still, but it's it's a fraction of what I owned.

35:57Speaker 2:We'll come back to any year or cera and see if that's changed, shall I Indeed? Final question, what are you reading at the moment?

36:04Speaker 1:Actually, what I want to read is a lot more philosophy because of what I think quantum is going to do.

36:09Speaker 2:Sorry now I was about to finish, but I can't leave on that. What is quantum going to do? That means we need to read more philosophy. Are we going to have one great existential crisis all of us in a honer from what we find out?

36:20Speaker 1:This is such a great question. It's quantum unlocks because of the way operate unlocks in effect a new data set and a new understanding, which is quantum physics. As we do that some of the assumptions that we hold very dear, that's probably the one we're but without question suddenly get challenged. For instance, what is reality? How does the universe operate? Something that I heard Demis Hassebis talking about in December. I was surprised I heard it from him is maybe energy and matter are not the foundation of the universe. Maybe information is. These are the type of things that this technology is going to start allowing us to explore. Many of those are philosophical questions, and so I want to be much more knowledgeable about about what that means. I'm absolutely fascinated by the understanding that we may be unlocking again another layer of what it means to be human and what it means to be sitting in this universe.

37:30Speaker 2:Daniel, thank you so much for joining us today. Thanks for listening to this week's Marin Talks Money. If you like us show, rate, review, and subscribe wherever you listen to podcasts. Also gives any questions or comments to Marry Money at Bloomberg dot net. It's an also following me and John on Twitter or exam at marys w and John is John underscorss depic. This episode was hosted by me Marren undset Web. It was produced by Some Society, Moses and Im and Jennifer ciliun by Mabel's and special thanks of course to Daniel don Steinberg m HM