


24 Aug 2026 · 38m · 16 chapters

The episode (Merrin Talks Money) explains what quantum computing is likely to change, how close “quantum computing actually works” is, and what businesses/investors should do now; it also includes a Bloomberg Tech Minute on SpaceX hiring culture.
Daniel Don Steinberg, co-founder and partner at EdenBase, an investment firm focused on frontier deep tech; EdenBase also builds technology-adoption ecosystems.
Quantum computers use qubits (probabilistic “quantum bits”) to do optimization and simulation better than binary machines. The crucial distinction is physical vs logical qubits: companies may claim many qubits but only logical, error-corrected qubits are truly powerful. As logical qubits scale (1→10→~50), useful machines emerge; “Q-Day” (encryption breaking) is discussed as potentially years away. Quantum is expected to be supply-restricted and initially valuable for business optimization/discovery, creating first-mover advantages and potential winner-takes-all dynamics.
Table-planning combinations; drug/material discovery and ammonia energy savings; banks’ quantum teams (watching IBM, testing algorithms, renting limited access); JP Morgan investing in Quantinuum.
Written by AI. May contain mistakes.
Discussion about the hiring practices and culture at SpaceX.
“it's the space exploration dream that draws people to the company, and Musk invokes that dream regularly to remind workers why they're there.”
Discussion on quantum computing and its implications.
“This week, I'm speaking with Daniel Don Steinberg, co-founder and partner at EdenBase, an investment firm that invests in frontier deep tech.”
A conversation about AI, LLMs, and their impact on various industries.
“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?”
Examining small language models and their advantages.
“computers are able to comprehend, like a code for a computer, rather than what humans are going to be able to understand.”
Deep dive into the principles and future of quantum computing.
“And a segue into quantum, for instance, is a quantum computer is not a binary system.”
Explore the complexity of optimization problems and their significance in quantum computing.
“that binary compute is very bad at the first is optimization so imagine a good example might be a table plan.”
Learn how quantum computing can simulate natural models and chemical reactions.
“And simulation is where we have the ability to simulate natural models.”
Distinguish between physical and logical qubits and their implications in quantum computing.
“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.”
Discuss the significance of achieving higher counts of logical qubits for breakthroughs in drug and material discovery.
“And that is the only reason to understand it.”
Understand the potential threats quantum computing poses to encryption and cryptocurrencies like Bitcoin.
“If you can only hold 50 variables, it's limited what the model can do.”
Explore how quantum computing could lead to monopolies and competitive advantages in various industries.
“And so most businesses are not considering the quantum threat.”
Discuss the preparations industries are making to leverage quantum computing and its potential impact.
“So does that lead us into a new age of monopolies?”
Learn about the current state of quantum computing and its accessibility.
“So they're doing a lot of that work now in readiness for when that happens.”
Explore how AI, quantum computing, and other technologies interact.
“You've got underneath that, you've got probably quantum.”
Discover how to invest in quantum computing and related technologies.
“investable at the moment as if you wanted to invest in space.”
Discuss the philosophical questions raised by advancements in quantum computing.
“But it's going to require so much money into the system to start pushing it up to those numbers again.”

Get the gist, explore an idea or ask about something said.
On Merryn Talks Money, what are the key points of this episode?
Automatic transcript. May contain errors.
0:01This is the Bloomberg Tech Minute brought to you by ChachiPT. I'm Carol Masser. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Businessweek's Lauren Grush. She reports that the company culture is defined by Musk and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs, and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw, innate intelligence.
0:39A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices, but according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company, and Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, must be willing to work extended hours and weekends as needed. One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time.
1:16That's the Bloomberg Tech Minute brought to you by ChachiPT. Get started at ChachiPT.com. For big business, AI opened up a world of promise, but that world of promise turned into a world of pain. Cost spiraling, data trapped, security and governance risks multiplying, and ROI out of reach. That's why enterprises turned to Boomi to connect data, apps, and AI, helping them operate securely, efficiently, and at scale. Boomi turns a world of AI pain into a world of AI gain. As Boomi says, we got you. Head to Boomi.com. That's B-O-O-M-I dot com. Bloomberg Audio Studios. Podcasts. Radio. News.
2:14Welcome to Maren Talks Money, the podcast in which people who know the markets explain the markets. I'm Meryn Somerset-Webb. This week, I'm speaking with Daniel Don Steinberg, co-founder and partner at EdenBase, an investment firm 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.
2:52Spoiler alert, read some philosophy. Daniel, welcome to Merrin Talks Money. Pleasure. Thank you for having me. Will you tell me a little bit about what Edenbase does and then we'll take it from there. Well, Edenbase's 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 Tech Nation for David Cameron in Level 39, which is the fintech ecosystem.
3:33And when I really explored what he'd done, I realized that ecosystems solved a few of the challenges I saw with what was about to happen. And so Edenbase 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 enough, three years ago. It's not sustainability, it's a future we can be proud of. Okay. 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 today, and the thing I invited you to talk about was quantum computing.
4:10But before we get on to 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 LLM's large language models, and anyone listening who isn't entirely sure how LLMs 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?
4:44So we're using the wrong phrase in the beginning. I think we used the wrong phrase because that's how we referred to technologies such as these, which are we are building artificial intelligence. And the history of compute, certainly for the last 20, 30 years, has been exponential. And LLMs 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.
5:27This happens to be even more so. And its 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. I was having a conversation with one of my nieces the other day about how you can tell what is AI writing and what isn't AI writing.
6:14And I was explaining to her that, of course, the way that AI writes, the way that an LLM writes is actually just the way that old people write because they're using our writing. This 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 50s? Well, a good question. It has access to a lot of information. And one advantage I have when 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.
6:51However, I do find the style we wrote the first book in is not the style we're 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. 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, LLMs will fully replace lawyers in no time at all. How do you see it playing out?
7:33Well, I think that's a very plausible scenario. Going back to my book that I wrote in 2020 and 21, we use the legal profession as something that LLMs are about to wreak havoc in, 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 186 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 llms 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 and we say if that happens then in 15 20 years there are no junior lawyers the second thing is As we become more LLM focused, the only thing that can unpick what LLMs are writing eventually becomes another LLM.
8:44And 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 very likely. The other thing that we find, and I've been enforcing this at Edenbase 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.
9:24So what it meant is a legal bid is probably 5 % of what it used to be. And that is also a problem for the legal industry. As long as you are fully confident in your LLM. 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. It wasn't worth sending to a lawyer, but I put it through an LLM and it took the Spanish contract. And this is two and a half years ago, so they weren't as good as they are today. And it gave me a plausible scenario. It might not have been all right. And I was able to write rather than just signing it and saying, well, I don't care.
10:01I 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. So what are the limits to the LLM 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 app from Stanford University, and someone at Pamya Liberium 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.
10:55The LMs are, 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 then crucial, then you can just have an SLM on your laptop. You don't need an LLM, which rather suggests that in some parts we might be going down the wrong path with full focus on LLMs, massive data centers, et cetera. Well, I haven't read that report, so I can't comment particularly on that now.
11:33What 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 built derivative trade technology in the early 90s, we worked on mainframes. And the only people that had desktops were the people that wrote letters. And within five to 10 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. I said, why do people need the cloud? You know, we can do it all locally.
12:08And 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 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 LLM 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 a segue into quantum, for instance, is a quantum computer is not a binary system.
12:53Daniel, explain quantum computing to me. Adam Quantum computing is a break from the past. That's the first thing. The most comprehensive way to describe it is, a 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. They were able to write beautiful mathematics that described how subatomic particles worked. In 1970s, Richard Feynman, the physicist, suggested that we could actually control them. And then in the 80s, IBM started trying to control them. And what that meant is they were able to, instead of operate binary bits, i.e.
13:40ones 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 compute is very bad at the first is optimization so imagine a good example might be a table plan. If you have five people sitting around a table, you have 125 combinations. If you have 10, you have 3 million. If you have 25 people, you have one with 25 zeros on the end of it, a combination.
14:24This is why it's so hard to make table plans. Exactly. It's impossible because 25 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 it. Gives you a new respect for wedding 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 models. 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 zeros.
15:09A 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 understood the next levels down and the next levels down. at 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 7 % of the world's energy creating ammonia for fertilizer. 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.
16:03And the reason it's so important is optimization and simulation are two of the areas that we are very bad at 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'd say they actually have machines that work now. 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 a great it's not a black and white so there is something called a qubit and a qubit is the equivalent of a bit in computing to run a quantum computer you need qubits and you need to connect qubits together and what confuses the picture more and i think people have to understand this when people use qubit, you have to ask, is it a physical qubit or a logical qubit?
16:54And they don't say which is which, and the difference is enormous. So a physical qubit is a working qubit. A logical qubit is one that you can control and use effectively. And there is an enormous difference, maybe a thousand to one. So certain companies will say they've got a hundred or a thousand qubit machine, but that's not a logical qubit machine and therefore it's to a degree not that powerful and other companies like quantinium will claim they've got a 52 qubit machine but it's a logical qubit machine which means it's very very powerful i don't understand the difference between these two qubits do i need to understand the difference between these two qubits 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.
17:48So if I open the paper and it says company A has a thousand cubits and company B has 10 cubits, which is what they do in the press, those 10 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. Okay, so the logical qubits are the much more powerful ones? They're the ones that are error corrected and work reliably. Okay. That's what you need to know. The point is, up until 2024, no company had announced a logical qubit. In 2024, someone announced one.
18:32And then in early 2025, they announced 10. Continuum, who are the half British, half American company announced 50 at the end of last year. 50 is starting to become meaningful. The 100 started to become useful. And so if you look at that progression of 1 to 10 to 50 over an 18-month span, you're looking at 100 within the next year or so. And then you have a machine that is useful. Useful for what initially? So we've got 100 logical qubits. See, I know, I know what these things are now. We've got 100 logical qubits. We've got a machine and it's useful. But what will it do for us initially? What will it change?
19:18What will we understand that we didn't understand before? 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 300, 400, 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.
20:03Okay, and this is partly down to sheer speed. It's not the speed, it's the number of variables that you can hold. So each qubit can hold a variable. If you can only hold 50 variables, it's limited what the model can do. If you can hold a thousand variables, it's quite powerful because it's factorial. So every qubit doubles the model, in effect, like that 5, 10, 25 that I was talking about. It's a factorial number. So adding qubit, it sounds like it's linear. It's not. It's non-linear. The numbers that people bandy about, and let's put it as bandy about, somewhere in the early thousands, you will be able to reach Q-Day, which is breaking encryption.
20:50So those numbers are maybe six, seven years away at current. Q day is the day when everyone's Bitcoin becomes useless, right? Worthless. Because, well, the encryption is broken. 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 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 a satoshi wallet of a million that cannot that 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 a bitcoin firstly who is going to sell it to me 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 wanted to short a market which is the only way you make money on it it's shorting so so bitcoin is probably in the top thousand of things you would go for, but you know.
22:15Too 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. Okay. So we get to the point out maybe 10 years, whenever it is, when we get to this Q day.
22:54And the first thing that can happen is we get to the point where that level of encryption becomes pointless, but companies such as Google, etc. are already protected against that. So what next? What's the next thing that we see happening that quantum computing will change around us? I think Q-Day will be scary. I think what necks 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.
23:34One, 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 1 % 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.
24:25It's the first person that discovers it. So if I'm a pharmaceutical company and I have access to the biggest 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 drug company has a 400 or 1000 logical qubit machine, will you build me one?
25:07They won't be able to. So does that lead us into a new age of monopolies? 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.
25:42I 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 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 will be for a different reason the amount of money that starts going into the industry will start to be huge.
26:40And the chat GPT moment will be the realization of big banks or of big pharma companies or big logistics companies 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 banks are 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 qubits. But when you say a bank will have a quantum team, a bank is not developing the machine.
27:27So a bank's quantum team is doing what? Just watching IBM all the time. Building systems that can use the quantum machine at a later date. 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 Quantinua, the leading quantum company, because they want access to it. The second thing they are doing is they are building algorithms that they can test 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 into amazon bracket you can rent a quantum computer it doesn't do very much but they are starting to test quantum algorithms on qubits because they know like everybody that a machine is made available the day two you're not using it It'll probably take you two or three years before you're up to speed.
28:28So they're doing a lot of that work now in readiness for when that happens.
28:40This is the Bloomberg Tech Minute brought to you by ChatGPT. I'm Carol Masser. Getting hired at SpaceX requires exceptional ability and may include having Elon Musk review a candidate's resume. So writes Bloomberg Businessweek's Lauren Grush. She reports that the company culture is defined by Musk, and job candidates must understand that a commitment to SpaceX means adhering to this culture and exhibiting loyalty to Elon Musk. To get hired, candidates must demonstrate their achievements from past jobs, and hands-on experience matters more to recruiters than advanced degrees, with the company looking for people with raw, innate intelligence.
29:18A spokesperson for SpaceX didn't respond to a request for comment on its recruiting and hiring practices. But according to recruiters, advisors, and those who've interviewed for jobs there, it's the space exploration dream that draws people to the company. And Musk invokes that dream regularly to remind workers why they're there. Prospective hires are told that the job will require stamina, including in job ads that candidates, quote, must be willing to work extended hours and weekends as needed. One major perk for all that hard work? Employees' access to equity, either the right to buy shares or payment in the form of restricted stock units that vest over time.
29:56That's the Bloomberg Tech Minute brought to you by ChachiPT. Get started at ChachiPT.com.
30:08really that the great power of the next phase of the technological revolution is the interaction between quantum and what we're calling ai look ai is an umbrella ai is an 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.
30:48But the AI, what we call AI, is the control layer, the orchestration layer that sits on top of all of it. 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, etc. Who's good at quantum? Who's going to win here? It sort of breaks down as 25 to 28 % of the US that we've looked at, 25 % UK, 25 % Europe as a whole, and 25 % rest of the world. China is probably most of that 25%. 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.
31:34And we've been looking at quantum for a very long time. And that's why Quantinium, which is part owned by Cambridge Quantum, it was a merger between Cambridge Quantum and Honeywell Quantum, is still located in the UK. And a lot of their brains are still in the UK. And they are likely, because we don't know what everybody is doing, certainly in China, they're likely to be the most advanced quantum company in the world. 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 easy for the non-scientists among us, how can we be quantum ready, both not as an investor, but also as an investor?
32:16Well, as an investor, one of the 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 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 definitely have very powerful quantum. Honeywell is part owner of Quantinium, which is, as I said, considered the leader.
33:02And 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 qubit. They're the people 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, etc., the ways of generating.
33:54but you've got to connect them together it's no point just having a generation station in the middle of nowhere 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 that area to me is the most investable at the moment as if you wanted to invest in space. And there are a variety of ETFs already, both in Europe and in the US, that list themselves as quantum ETFs.
34:36Was that a reasonable way for an ordinary investor to get a little exposure to the space, or is that just filled with junk? When I looked at them last, six months ago, there were very few quantum companies in there. Now, that would have changed a little bit. As 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 10 15 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 in floating listing quantum companies so that will that will be in the space so that that would be my preference that's what i do some companies get acquired by the bigger companies ionq for instance is acquiring lots of companies because they have something in there that they really need.
35:26So even the ones that are less sophisticated in the number of qubits 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. What could go wrong with all this? It all sounds absolutely marvellous.
36:02You make me very excited about the future. What could go wrong here? 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 technologies. 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 50 to 200. They go from 50 to 2 ,000 or 5 ,000. And suddenly the regulators say these systems are not going to be available to people. 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.
36:55They have to give us their software and it grows slowly because of that. Isn't that where 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? That's true. But I suspect if China developed 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 useful. If I've developed a nuclear bomb, I could sell it to lots of people, but I'm not going to. Okay, brilliant. Right. Okay, my brain's about to explode.
37:31Daniel, what haven't we covered in this area that we should 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 TCP IP works, no one says that. They say, how does it change what I'm doing? I think quantum is actually very approachable. There was a quote I heard in 2022 from the deputy head of IT for the US Air Force who said, Q-Day is almost closer than it will take us the time to fix the problems that we have.
38:16and that is really how you need to look at it which is there's an opportunity and 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 brilliant daniel i'm going to ask you i haven't asked for a while because it got a bit boring felt a little old-fashioned but i think we might be in the correct zone here, which is that given the choice over a 10-year period, Bitcoin or gold? Wow. I would probably say gold now. The Bitcoin industry has been built on hype. It went up to 125 ,000. It's now sitting around 60.
38:57I'm still a holder of Bitcoin. I sold most of my holdings in 2022. 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 a fraction of what I own. We'll come back to you in a year or so and see if that's changed, shall we? Indeed. Final question. What are you reading at the moment? Actually, what I want to read is a lot more philosophy because of what I think quantum is going to do. Sorry, and 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?
39:35Are we going to have one great existential crisis, all of us in Awana from what we find out? This is such a great question. It's quantum unlocks because of the way it operates. It 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 word, but without question, suddenly get challenged. for instance what is reality how does the universe operate something that i heard demis hasabas 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 what that means.
40:37I'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. Daniel, thank you so much for joining us today.
41:00Thanks for listening to this week's Merrin Talks Money. If you like our show, rate, review and subscribe wherever you listen to podcasts. Also keep sending questions or comments to merrinmoney at bloomberg.net. You can also follow me and John on Twitter or X. I'm at merrinsw and John is John underscore steppik. This episode was hosted by me, Merrin Somerset Webb. It was produced by Sam Asadi, Moses Andam and Jennifer Seeley. Sound design by Blake Mabelt. Special thanks, of course, to Daniel Don Steinberg.
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Merryn Somerset Webb talks to Daniel Doll-Steinberg, Co-Founder & Partner at EdenBase, an investment firm that invests in quantum computing, about why the next great technological leap may arrive sooner than investors expect. They explore how quantum could transform drug discovery, finance and encryption. They also look at how investors can get meaningful exposure to the quantum boom, what “Q-Day” really means for Bitcoin, and why understanding philosophy goes hand-in-hand with understanding quantum.
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