Trump’s $500 Billion ‘Stargate’ Is ‘Most Important U.S. Investment’ — David Lin (Uncut)
Trump’s $500 Billion ‘Stargate’ Is ‘Most Important U.S. Investment’ Today | Arthur Herman
And suppose an attack were to happen and the development of fail-safes is not ready. What would this attack look like? Suppose you were a hacker, right, Dr. Herman, and you used his technology, what would you do? That’s what’s so interesting. The Trump administration is about to make one of the most important investments in modern American history, according to our next guest, Arthur Herman, Senior Fellow and Director of the Quantum Alliance Initiative at Hudson Institute.
We’re going to find out what that is and how that’s going to impact society and financial markets. We’ll also be talking about the intersection between quantum computing and AI and how these spaces will progress and influence cryptocurrencies, national security, and everybody’s lives. Dr. Herman, welcome to the show, it’s a pleasure to have you.
It’s a pleasure to be here. Let’s start with some recent news coming out of the U.S. President Trump has announced recently that he is initiating a $500 billion Stargate AI project. He said the country will be prospering like never before.
Take a look at this news development. President Trump announced on Tuesday a private sector investment of up to $500 billion to fund AI infrastructure aiming to outpace rival nations in the business of critical technology. He said the joint venture called Stargate will build data centers and create more than 100,000 jobs in the U.S. Chad Chibiti, creator of OpenAI SoftBank, and Oracle, along with other equity backers of Stargate, have committed to $100 billion for immediate deployment, with the remaining investment expected over the next four years.
What’s your initial reaction to this story, and then we can discuss the particulars. Well, I think it’s an amazing step forward in terms of where the U.S. government is going to be headed in terms of advancing the big technologies, and particularly AI. And what’s startling and interesting about this initiative is that the bulk of the capital, that $500 billion, it is going to be coming not from the federal government, but it’s going to be coming from private sector.
In other words, this is a form of industrial policy, in other words, in which the government helps to coordinate and bring together the investors, the technology, and the infrastructure to advance, in this case, artificial intelligence as a part of social and economic, and also, I think, without a doubt, national security. But at the same time, that the people who will be spending the money and watching how the money is spent is the private sector. And generally speaking, I think it’s a rule that people who have made a lot of money are usually pretty good at figuring out how that money is going to be spent and being careful about it, as opposed to simply opening up a vein of money from the federal government in order to support advanced technologies.
We did that recently with something called the CHIPS Act here in the US, which was, again, to advance technologies such as semiconductors production and AI. It was even money there for quantum technology. And really, it hasn’t worked out terribly well.
And I think one of the reasons is the key decision makers with the CHIPS Act were government officials and politicians, whereas if this Stargate enterprise goes the way it should, the key decision makers of how money is going to be spent and how much and where will be the driving engines of the private sector in that regard here. When it is reported that $100 billion will be deployed immediately on AI infrastructure, what does that mean, practically speaking? What is AI infrastructure besides just data centers? Well, I think part of it will be data centers, but I imagine also it’s going to have to be investment in energy. The demand, the heavy demand for energy that AI places on power grid is already beginning to make it cause pain in terms of the ability to produce enough power to drive all of this machine learning and artificial intelligence demands here.
We’ve seen it with companies like Google and Microsoft going out of their way to actually buy nuclear reactors and buy nuclear power plants as a way in which to try and sustain where they see the upward trajectory of artificial intelligence as a technology, as a part of the economy. So I would imagine a big part of this will also be addressing how to build a power grid that will not only sustain the growth of artificial intelligence, but actually advance it and drive it forward. But it’s an interesting and I think quite fascinating project.
And if it’s done right, it’s probably going to be the most important American investment in advanced technology since the moonshot. That’s if it’s done right. And I think the other thing which struck me, David, when I heard the announcement was that number, $500 billion.
And to what degree that was influenced by the fact that President Xi of China has announced a $250 billion initiative to make China the great AI leader. So maybe that number was just not snatched out of the air, but a way to suggest that the United States is going to do twice as much as China that goes with it. The other interesting thing about this Stargate project is that the name Stargate would suggest that we see the hand of Elon Musk in all of this.
But it looks like from the stories that are coming out and the sources are telling us that in fact Elon Musk has his doubts about aspects of this, whether these companies are really going to be able to raise the capital that’ll be necessary to build an initiative of this sort. I think it’s fairly well known that Musk and Sam Altman don’t necessarily see eye to eye on a lot of issues. Musk has had his questions about the direction of AI, particularly generative AI in the past.
So his expression of skepticism and doubts, while it may come as a surprise for everybody who thinks that the high-tech elite are all 100% in lockstep behind Trump and the Trump agenda, what it does suggest though is that the details on how Stargate is really going to work and how it’s really going to function still need to be worked out and need to be worked out in a very careful way. This is going to be not just a success in itself, but as a means by which to really preserve and extend American leadership in AI, but also as a paradigm for how and a model for how a new kind of industrial policy can be brought to be to revivify American manufacturing, to revivify, who knows, shipbuilding in America, the whole range of areas where we’re looking for new ways to think about how government and the private sector can work together to mutual benefit. You said that this could be the most important American investment in quite some time, Dr. Herman.
If done correctly, how would our lives change, Americans’ lives change over the next four to five years? Well, now we come to another interesting point, David, and that is, is that where do we see the emphasis with regard to AI and machine learning within this broad tent of AI infrastructure and the development of it? If we’re only talking about ways to advance generative AI, then I think there’s going to be something of a missed opportunity here. Now, why do I say that? I say that because I think where my view is that where, although generative AI is a hugely important and very significant advance, both in terms of social transformation and cultural transformation, but also as a driving engine for economic growth, the other part of AI are the uses that overlap with other parts of the economy. And here I’m talking about, for example, industrial AI, the use of AI as a means to re-engage and to revivify manufacturing, to make manufacturing sector more productive, to make it safer through the use of AI as a means, as a tool for increasing productivity and for economic output.
Its use in agriculture, its use in mining, the ways in which AI can make for a more productive, but also much safer and much cleaner and greener mining extraction processes and as an industry could be transformational there as well. So while CHAT-GPT has really drawn big attention on the part of American public, and I think the world, to just how important and what a big game changer AI can be, I think at the same time, there’s this whole other aspect of AI that in China, the government and industry understand very well of how it becomes a means by licking that up with robotics, for example. And you can create entire factories, which are fully automated and fully productive and completely safe for its human operators in ways that in the next decade, I think we’re going to be astonished at the transformations that could take place here.
So if Stargate is something that engages all aspects of AI as a force multiplier, as a game changer in our economic and national security, I’m all for it. But it’s got to be able to do more than just be able to replace human thinking when it comes to daily tasks or writing term papers or all the things we’ve come to expect with CHAT-GPT or even market forecast. Well, the theme of our conversation today is the intersection between quantum computing and AI.
So let’s bridge this conversation over to quantum computing now. It’s been reported that Google’s Willow chip is a massive game changer. This is according to Quartz magazine.
For example, they wrote, Google said Willow was able to complete a computation in less than five minutes that would take a classical computer from the beginning of the universe until now to complete. This is just to illustrate to laymen how powerful this new type of computer is. Dr. Herman, you’re a historian by trade.
Just per your studies, how significant is this development in the long history of technological development of mankind? Well, I would say this. I think that this is certainly a landmark, an important benchmark for development of quantum computing as a, not as a replacement for classical computing or conventional digital computing, but as an adjunct to and something that can extend and expand the ways in which the ways in which we calculate and analyze data and come to understand our world. And if you like the universe in more detail and in more clarity than ever before, remember that the quantum computer’s key advantage is not that it’s faster than supercomputers, but that it’s able to skip multiple steps in terms of the calculation of numbers and the quantification of data.
So, its ability to cut through all of the intermediate steps that a normal digital computer, which has to convert everything to ones and zeros, it’s able to dispense with that. The way I like to frame it, David, is that whereas instead of reading the entire Library of Congress book by book, we’re able to read the entire library all at once. That’s the kind of potential speed and the potential efficiency that a quantum computer brings.
But what we also have to understand is that the development that have been taking place and the other large-scale quantum computers, companies like Microsoft and Intel and others are engaged in the same race for development here, that the really big changes are going to come a lot faster and be accelerated when we find ways, as scientists and engineers are now doing and some companies are doing, to integrate quantum computing units with conventional computing units, including AI. And what you’ll have then is the best of both worlds, in which you’re able to analyze masses of data, huge amounts of data, which is what classical computers and AI machine learning do very, very well. But then it boils down to the set of answers that you need and require to understand a seemingly insoluble problem, to do that in a matter of seconds as opposed to taking years in which to solve, as is the case with supercomputers.
So the Willow experiment, we have to remember that they’re solving problems which are devised specifically for the existing quantum computer. In other words, we’re not yet solving real-life problems, we’re solving ones that are specifically designed to allow the quantum computer to answer faster than a supercomputer to do it. We’re still in the hypothetical range with regard to this.
So can you give us some applications, practical industrial applications for this type of computing power? I’m presuming it’s way too powerful and not really needed for the average retail consumer. It probably is not the kind of thing that each of us would require. But let me give you a good example of where quantum computers have an enormous advantage over classical computers.
And that’s what’s called optimization problems. The problem of figuring out how do I get to multiple points from a single point at the fastest and most economical way I can. The classic example is the newspaper route, newspaper boys route, right? You’ve got destinations for your deliveries all across the city, all across the county.
How is it that I can reach each of those destinations in the quickest possible time and the most efficient way possible? That’s a really difficult problem for an ordinary computer, even AI to figure out. But quantum computers are able to do this in almost in a matter of minutes. They can figure out the way in which to do these.
Now think about what would happen then with regard to issues such as supply chains. It’s become a very hot issue now for economists, for industrial undertakings, for politicians. Imagine if you could handle supply chain problems of taking a far-flung distribution or supply chain network and figuring out what’s the quickest and most efficient way for me to get the most important supplies that I need or to reach out to the distribution network that’ll give me the best return and the fastest possible distribution.
Being able to solve problems like that in a matter of minutes or even seconds, that’s the kind of calculating power, problem-solving power that quantum computers can break to bear. Their also key advantage that they have is model building. And they’ll be able to—and quantum computers, as they scale upwards, will find ways in which to do very precise, very accurate modeling for any number of phenomena all the way down to the subatomic level.
This gives you not just a breadth of analysis but a depth of analysis that right now classical computers, AI and machine learning are only able basically skimming on the surface compared to what quantum computers are going to be able to do and right now in fact are doing. In the case of the optimization model, I know companies, in fact one of them Canada-based, D-Wave Systems, which is now an American company but was founded and originated in Canada. And they’ve been doing optimization modeling, solving problems like traffic patterns for cities, including Beijing, using quantum technology in order to do this.
So I think the bottom line here, David, is for us to all understand that the quantum computers—quantum computing is not some far-off project that exists just beyond the horizon. When IBM or Google are finally able to scale up their large, you know, logic gate quantum computers so it’s able to handle thousands of qubits instead of just 100 to solve problems. That this is a revolution which is taking place right now with commercializable technologies that are underway right now.
And that the most dangerous aspect of the quantum computer revolution, the threat that it poses to public encryption systems, we won’t talk about that. Yes, yes. That that revolution is going to be coming a lot sooner than we think.
And the time to get ready for and to protect data and networks is getting shorter and shorter every year. We will talk about quantum computing and how this may affect cryptography and the crypto industry. I like to talk about AI and quantum computing.
People are talking about this as if it’s the perfect marriage. Presumably, if you were to remove the limitations of data size, computational speed, and the ability to solve problems at breakneck speed, we could, in theory, have AGI tomorrow. Correct? Yeah.
And also, too, you would have the ability to make quantum computing developments move faster as well and progress. For example, one of the big problems that a company like Google faces with its quantum computing and building its quantum computers is the fact that the qubits, the bits, the subatomic particles which are there, which become the bits with which you carry information, right, as part of the computing process of a computer, that these qubits are extremely unstable. They fly off in all kinds of directions in unpredictable ways.
The German physicist Werner Heisenberg described this as the uncertainty principle that even if you know where your qubit is, you don’t know where it’s going. And likewise, if you know where it’s going, you don’t know where it’s come from. This makes it very difficult to bring them into order enough for those nanoseconds necessary to carry out a calculation.
That instability, that decoherence, as the physicists call it, of qubits that fall off and sort of get lost into the haze, the computing haze, is what’s called noise. And right now, even the best quantum computers like Google’s, Google’s Willow, have a lot of noise, a lot of qubits which just be fly around without any kind of real purpose to them but which are distracting for the programmer and for the user. Now, artificial intelligence machine learning could be extremely helpful as a tool for helping to distinguish between noise and signals in that situation and to separate out the qubits which are simply flying off on their own as opposed to those that are staying disciplined and superpositioned long enough to carry out your calculations.
So, by adding AI and machine learning to the development of the quantum computer itself, we can begin to really shrink the timeline that’s necessary for the big breakthroughs in quantum computing we want to achieve. So, what I see is this kind of interesting synergy between the AI and machine learning community and the problems and the solutions that they bring to the world of computing and the world of digital technology and the quantum community which is very much dealing with and confronting the physics that underlies how digital technology is able to function and able to improve and grow by utilizing technologies such as quantum and quokka as a way to advance how we make calculations and how we understand and interpret data. This is an interesting development.
Let’s talk about AGI for just one minute, Dr. Herman. We have some confusion as to whether or not OpenAI has actually developed AGI. Last month, it was reported that maybe their newest update has reached AGI levels, artificial general intelligence.
New O3 and O3 mini models could be more powerful than the previously launched O1 models the company had previously announced, although now Sam Altman, founder, is saying that no, they have not yet developed AGI. AGI has been presented to me as somewhat of a marketing buzzword for a lot of companies. How would you define artificial general intelligence? Could you evaluate the state of the current situation and industry and whether or not we’re there yet? Yeah, I think AGI is a bit of a chimera.
I think it’s a, as you, the way I think you phrased it very nicely, it’s a good marketing tool to talk about it and it gives you a lot of buzz and it’ll draw you a lot of attention from the media, both tech media but also business media as well. I don’t know because of the, both the promise and also the peril involved in an AGI, in artificial general intelligence and the ways in which this will supposedly challenge even our own humanity by will we be inventing machines that are not only better than, and function better than human beings but will actually look at human beings and say, we’re doing a lot better than you are and we have no reason, what’s the reason for keeping you around when we could be running the show? All those kinds of science fiction aspects of the AGI future, I think, is part of what helps to sustain interest in this and to keep the issue alive but I think we are, if I may say, very far away from artificial general intelligence as an applicable law for understanding how AI and machine learning can function and improve and become a very powerful part of how the economy and society functions. Let’s just hypothesize here since we’re talking about science fiction.
You take Tesla’s Optimus robot, pair it with a quantum chip and install software that is equivalent to AGI. What happens then? Well, we’ve got three technological components, right? And when you mention a quantum chip, that’s where it begins to get sort of break down a little bit because I think we’re very far away from a quantum chip that does anything other than look for other quantum chips to join together and to find some way to develop an overall process. I mean, sure, if you think about where all of this technology could be headed in terms of developing machines, developing capabilities for machines that begin to approach and even mimic human intelligence and human motivated behavior in ways that makes it very difficult to distinguish between am I talking to a machine or am I talking to another human being? That’s the Turing test and a lot of it is now already past the Turing test.
Reaching out to the Turing test. And I think in the end, what we have to sort of say is that perhaps at a very superficial level, at certain moments where we’re talking on the phone and we can’t quite decide if you call in for help for a company and you’re speaking to somebody and for a few minutes you’re like, have I actually got somebody on the line here or am I talking to an AI tool? And those moments arise. But the key term here, I think, David, which we must get away from is mimic.
That in the end, what AGI technology and advances will be to develop more and more accurate simulation of how human beings act and behave and even think and in terms of the rational understanding and interactions with what takes place in the world. But that’s a very far cry from AGI either replacing human beings, let alone being superior to human beings. That the issue, and I’ve written about this in a review of Henry Kissinger’s book on the age of AI, for example, where the question came up in that book, the one that he did with Eric Schmidt from Google, the question that came out was, does AI pose that kind of threat to what it is to be human? And I felt that we’re really not on a trajectory where that question is going to be anywhere near consideration for us.
And I think the more we get distracted by those far off futuristic views of what AI could do and what could take place, the more it distracts us from really understanding just how powerful and useful and even essential AI and machine learning can be as technologies for economic growth, for national security questions, and for ways in which to make our world safer and a happier place in which to operate without worrying about whether we’re all going to be replaced by robots. Yes. Well, let’s talk about quantum computing and cryptos now.
So people are still wondering about what this means for cryptos. For example, this Reddit thread. Why people throw money at crypto if quantum computing is coming, as the title says.
I appreciate that it can take years, if not decades, to perfect quantum computing, but it’s going to happen. It’s just a matter of when more than if. This was a post from a year ago.
While encryption can be updated to be quantum safe, cryptos are really exposed. And as far as I know, there’s no crypto or blockchain that is really quantum ready. Why people keep throwing money at Bitcoin then? How would you go about answering that question, Dr. Herman? Well, I would say overall, the premise is probably accurate.
I think in the end that you will have quantum computers that will be able to factorize the large prime numbers that underlie the encryption for any public encryption system, but also also for blockchain and for other distributed ledger technologies that underlie cryptocurrencies. But I don’t think that’s the reason to give up on cryptocurrencies at all. I think far from it.
I think what I see is an enormous opportunity for cryptocurrency community to really lead and take the advance in building quantum safe and quantum ready networks that will protect against future quantum computer intrusion and hacking. That far from this being a matter for a matter for despair, that this is a matter of great hopefulness, that the cryptocurrency community, which has been, let’s face it, they’ve been on the edge of pioneering and innovation for a long time. The very fact, the very invention of cryptocurrency suggests someone who is not content with sort of the norms that are supplied in terms of monetary value and ways in which to calculate and store monetary value here.
It’s precisely that community which, on the one hand, has perhaps the most to lose if a quantum computer attack in the future were to come about and become a reality, but also may have the kind of creative, innovative thinking and paradigms of the ways in which to protect against it. You know, two years ago, we did a study at Hudson Institute, a very detailed quantitative study of what the costs would look like if you had a future quantum computer hack of Bitcoin, just Bitcoin alone. And the numbers that we came up with ran into the trillions of dollars for the damage that would be done to the US economy, not just to the value of cryptocurrencies, but also as a ripple effect throughout the financial markets and financial institutions, which have come more and more to rely on cryptocurrency as a store of value.
It’s no longer just a, you know, sort of fringe investment tool, as you know. It’s become part of people’s portfolios, part of companies and financial institutions’ investment portfolios. And so an attack that could bring down or devalue cryptocurrency like Bitcoin or Ethereum or any of the others would have serious, deleterious effects on economic growth, on financial stability, and a range of other things.
So from our standpoint, from an analytics standpoint, the danger is real. It’s just a question of how soon the timeline for developing the kind of quantum computer or quantum computer and conventional computer hybrid that would enable you to carry out that kind of encryption and what would take place with it. So what we’re seeing is we’re seeing a real threat.
Yeah. The real question is, how does cryptocurrency community respond? Do they respond by pretending like it’s not there and say, well, it’s decades away, we don’t have to worry about it? Or can they say, we have ways in which we can adopt quantum safe encryption that will protect not just us, the future of blockchain and the future of cryptocurrencies, but can be a model for how other financial institutions and other financial tools need to protect themselves from that growing threat. And the speculation on quantum attacks on Bitcoin, can we just guess, take a guess as to when a quantum attack on Bitcoin, just specifically Bitcoin, could happen? How long would it take for a quantum computer? I think the short answer to that is, I think that the timeline is steadily shrinking.
And I think we’re looking at a possibility, if you think about it in terms of quantum computing plus a plus conventional hybrid system, not waiting until you get those large scale quantum computers with the thousands of qubits in which to carry out decryption operations, but doing it using quantum plus conventional computing. And Chinese are already experimenting with doing this and have already claimed that they can hack into RSA encryption using those hybrid systems. We may be looking at something in which the threat becomes real, I think, in less than a decade, maybe as soon as five years.
So it’s not just a question of the timeline required before the threat arrives, and when it arrives it’s too late, but it’s also the timeline to get ready and how much time and effort is going to be required in order to layer into legacy encryption systems and cybersecurity systems the kinds of quantum safe cryptography, quantum safe, quantum resistant algorithms, whatever kind of technology you’re talking about. The time it’s going to take in order to put that into place. And suppose an attack were to happen and the development of fail-safes is not ready, what would this attack look like? Suppose you were a hacker, right, Dr. Herman, and you used his technology, what would you do? That’s what’s so interesting.
What would it look like? Well, let’s think about this for a minute, because a quantum computer hack is going to be very different from a conventional hack of the kind that we’re used to being carried out by hackers today and all the time and what gets underway here. Because what happens with a quantum computer attack is you’re not just breaking into the network or breaking into one particular user in order to have access to the other users or to the data or to be able to use the network. What you’re really doing is you’re factorizing the prime numbers that underlie the entire encryption system itself.
So from the point of view of a hack of, let’s say, Bitcoin, is that it’s not going to appear as everybody says, oh boy, someone’s trying to get into the Bitcoin and try to hack into and steal value from a system. The hacker is going to appear as a user of Bitcoin, as an investor. And so they’ll have access to everything that operates within the network, within the chain, within the blockchain.
And that means that they’ll be able to manipulate and control in ways that none of the other users will be aware of until all the value is gone or until things reach a level of instability that finally someone says, what’s been going on here? What’s really been happening here as well? So it’s a stealth and persistent threat. And that’s what makes it so different and I think qualitatively different from a conventional hack of the kind that we’ve become used to. So it’s not simply just breaking the encryption of Bitcoin and then stealing everybody’s private keys and bringing the price down effectively to zero.
I mean, that’s one possibility. But it’s a lot more nuanced than that. It’s a lot more nuanced than that.
It’s being able to manipulate and control Bitcoin as a whole and its interaction with everybody else. Well, I mean, that threat could be applied to any financial market, could it not? Of course it can. Yeah, of course.
The other study that we did, one of the other studies we did at the Quantum Alliance Initiative was what would happen with a large quantum computer hack on the FedWire system, which underlies how interbank loans take place with the Federal Reserve. And there you have the same problem. You have a ripple effect costing trillions of dollars across the economy.
But again, one in which every move made by the hacker appears as authentic and as a deliberate act of the users within the network. So in other words, you’ll be able to declare interest rate cuts or interest rate increases by the Federal Reserve. And it will appear across the markets as being genuine and authentic, when in fact, of course, it’s completely bogus, completely set up in order to do this.
And on banks, how does it impact? And there’s no footprint. In other words, there’s nothing for cybersecurity to go back and look and find the back door at which this took place. Because you are controlling, you’re able to manipulate the encryption system itself.
That’s the underlying danger. That’s the dark side of quantum computing technology in the future. And how does it impact banks, for example? Well, in that situation, what you would have is banks that are simply going to have to shut down any kinds of transactions because there will be no way of knowing which are authentic and which are bogus.
So everything grinds to a halt. Again, it’s not a question of emptying out the value of the bank vaults. That would be, that’s the low hanging fruit for a computer hack, including a quantum computer hack.
The real value is being able to disrupt and render meaningless every financial transaction that takes place. And if you do that within the U.S. financial markets and financial infrastructure, then you’re going to be able to do this globally as well and bring everybody to a screeching halt. So what’s the defense for this ultimately, especially in regards to national security? Well, the defense comes in two kinds.
The first kind is the one that the U.S. government has been most focused on, which is the development of quantum-resistant algorithms, what are called post-quantum cryptographic algorithms, which can be inserted into existing networks and can be inserted into and on top of existing cybersecurity measures by putting in encryption where the underlying prime numbers are too large and so complex that even a quantum computer won’t be able to penetrate. That’s why they’re called quantum-resistant. Now, the problem is that there’s no quantum computer of which to test.
So in other words, we’re assuming, and probably justifiably so, that these large, complex algorithms that are being installed are ones that will foil a future quantum computer attack 10 years, 20 years out. That’s the assumption in which they’re operating, and that’s the assumption in which they perform. Now, that’s a very different situation than you have with the second approach to quantum security, and that is to actually use quantum-enabled technology in order to protect against hacks.
That’s what quantum key distribution networks do, for example. That’s what using a quantum random number generator technology does, for example, is you create a link between users that automatically, when someone tries to intercept or hack, including a quantum computer, it immediately severs the connection, and both sides know that something is going wrong, and they break off. That unlike today’s cyber security in which you now know, there’s no way to know whether a quantum computer has hacked in or not, this way you know automatically that it has, and the communication ceases at once.
We’re talking about hack-proof networks. This is a way in which we talk about what’s called quantum cryptography as distinct from post-polar cryptography. There are companies, there are commercial companies now that are doing this, using this quantum cryptographic approach, using quantum-enabled technology in order to do this.
There’s, I can think of one in Canada right now, Quantum eMotion, for example, which is based out of Quebec, which is doing this, precisely this kind of using random, using a hybrid of both quantum random generating numbers to give you the equivalence of a one-time pad for encryption, and also with quantum-resistant algorithms at the same time. But there are companies in Australia, there are companies in the United States that are doing very much the same kind of a thing here as well. So that technology already exists, it’s already being used.
And in certain circumstances, it may be more appropriate and be more useful than installing these big quantum-resistant algorithms that post-quantum cryptography prescribes as the solution to future computer hacking. So ultimately then, what would you recommend or suggest to blockchain developers to do in order to prepare for this? I would recommend, I recommend an all-of-the-above approach. Okay.
All right. I think by and large, I think that a quantum cryptography approach is probably going to be the most effective, simply because so much of what happens in blockchain technology is point-to-point communication within the network. And so having ways in which to protect that encryption from quantum computer hacking in ways that don’t involve installing big, large, clumsy algorithms into each state within the ledger could take place here.
But there’s any number of solutions that are coming, and the companies that are working on this now are finding easier and easier ways in which to do it. When I first, David, when I first got involved with this and thinking about cryptocurrencies and their future and the risks involved with quantum computer hacking, when I first got involved with this three years ago, four years ago, it looked like the only solution was to start from scratch. In other words, you’d have to build an entirely new distributed ledger based on quantum-safe standards as a way in which to go forward.
Enormous, expensive, time-consuming undertaking. Now what we’re seeing is more and more what I’ll call plug-and-play solutions for quantum security, including for blockchain and a host of other uses as well. And so I think what you’re going to see is that quantum security as a useful tool for protecting against not just future quantum, future hacking, but also present-day hacking as well.
They’re just as effective for that. That you’re going to see enormous advances and strides that take place there even faster than the advances that take place in quantum computing itself. Excellent.
Dr. Herman, I really appreciate your insights. Where can we learn more from you and your work? Well, one thing you could do is to go to the Hudson Institute website and check out the Quantum Alliance Initiative. You could download our reports that are there that will, I think, help to explain not just how quantum computing works as a security threat, but also how quantum and AI and quantum and conventional computing are going to work together as hybrid systems in the future.
And our big landmark study on quantum computer threat to Bitcoin and to block cryptocurrencies and also to the Federal Reserve, you could find the links on that website page as well. I think that will all be ways in which to really help to both educate people on just what the quantum computers can and can’t do. But also, I think the most important thing is to make people feel that this is not, on the one hand, it’s not a science fiction threat that lies out far way out on the horizon.
On the other hand, it’s no reason to despair, certainly. There is some kind of inevitable sort of doom which is going to fall upon cryptocurrencies or financial markets and so on. We have the tools in which to protect against future quantum computer threats.
It’s just a question of the will, the time that it takes to deploy them before that threat becomes real. Very good. Thank you very much for the links down below.
Appreciate you, Dr. Herman. Speak next time. Thanks, David.
Look forward to talking to you again. Thank you for watching. Don’t forget to like and subscribe.