EP19: Quantum Computing Unveiled: AI, Cryptography, and Future Technologies with Dr. Thomas Wong

Speaker 1:
0:00
I'm not a physicist and I certainly don't play one on television, but from my understanding is that, you know, qubits can be linked together in a special way that really can let them share information instantly, right?

Speaker 2:
0:09
It's still probably faster to kick it than it is to throw it or to run with it, and so, again, this is the idea you're changing the rules of the game. In some cases, certain things are faster.

Speaker 3:
0:23
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Speaker 1:
0:51
Hi, fellow travelers, to another exciting episode of Tech Travels. In today's episode we're going to venture down the road of talking about the wonderful world of quantum computing, and quantum computing promises to revolutionize how we solve complex problems and how it enables possibilities that are just simply not possible with classical computers. And today we're thrilled to have Dr Thomas Wong, a leading physicist in the field, to join us on this discussion and discuss these groundbreaking achievements. Dr Wong is a professor at Crichton University specializing in quantum computing, and he's renowned for his research on quantum information search methods and innovative contributions to quantum computer design. He holds a PhD from UC San Diego and serves on the editorial board of the Journal of Quantum Information Processing. Tom, welcome to Tech Travels. We're so honored to have you on the show today. Thank you, Steve.

Speaker 2:
1:43
So wonderful to have you, so Tom, with to Tech Travels we're so honored to have you on the show today.

Speaker 1:
1:45
Thank you, steve, so wonderful to have you. So, tom, with your extensive background in both physics and computer science, can you help us understand kind of just from the start of explaining the fundamental principles of quantum computing and how they differ from classical computing?

Speaker 2:
2:04
Yeah, so a traditional computer uses bits. So your zeros and ones, and that's it. You just have two options. Your bit is either zero or one, and that's it.

Speaker 2:
2:10
But a quantum bit acts differently. In some sense it can be like a combination of zero or one, and there's actually this great geometric way of picturing what these quantum bits, or qubits, look like. And so if you imagine a sphere like the Earth, you know a ball, and imagine that the North Pole is your zero and the South Pole is your one. So with a traditional computer bit you can only be at the North Pole or the South Pole. You're either zero or one. But with a quantum bit you can actually be anywhere on this sphere. So you could be halfway on the E equator. You could be in halfway on the equator. You could be in the northern hemisphere, you could be in the southern hemisphere, even at a particular latitude. You can go around the earth and have a different longitude.

Speaker 2:
2:57
And so you know, if you imagine now you know if you're somewhere on the surface of the earth, say on the equator, well, that's neither zero nor one.

Speaker 2:
3:06
In some sense that's like half zero and half one, because you're halfway between the North Pole and the South Pole.

Speaker 2:
3:11
If you're in the northern hemisphere, you're now more zero than you are one because you're closer to the North Pole and so forth, and so a quantum computer actually acts like this.

Speaker 2:
3:23
So with these bits you're no longer constrained to being zero or one, you're actually some combination. But one of the interesting things is that when you actually measure your quantum bit to see what the result is, then you force it in a sense to take a stand, so you force it to be zero or one at that point. So if your quantum bit was on the equator, then with a 50-50 chance you'd get the North Pole or the South Pole. If you're in the Northern Hemisphere, you're more likely to get zero. If you're in the Southern Hemisphere, you're more likely to get one. And so there's these probabilities that are involved with a quantum bit, and the idea is that you want to tune your quantum algorithm so that the probability of getting the right answer becomes high, and so essentially, a quantum bit just has a very different unit of information, and because it acts differently, you're able to do different things and in some cases solve problems faster.

Speaker 1:
4:14
Yeah, and again it's like so qubits, they can be linked together. And again, I'm not a physicist and I certainly don't play one on television, but from my understanding is that qubits can be linked together in a special way that really can let them share information instantly, Right?

Speaker 2:
4:31
Yeah, so I think what you're talking about is quantum entanglement. So quantum entanglement is this unique property that quantum bits have, where you can have quantum bits where, even if you separate them by long distances, when you measure one qubit, that directly affects what the other qubit could be. And so one of the interesting things about this is that, even though the measurement of one qubit can in some sense instantaneously affect the other qubit, you actually can't use that to transmit information faster than the speed of light. And so you know, unfortunately for science fiction movies and novels, you can't use quantum mechanics to do an instantaneous information transfer or, to you know, talk to people across galaxies instantly. Yeah, but this idea of quantum entanglement, this is actually a property that is utilized in a lot of quantum algorithms and quantum protocols, and so it allows you to do things like to solve problems faster than you could with a traditional computer.

Speaker 1:
5:34
Right. So you mentioned algorithms and understanding a little bit more about the algorithms. I think there's quantum algorithms where you kind of use the different types of algorithm versus traditional right, or are they the same? Can you walk me through a little bit about understanding what quantum algorithms might be?

Speaker 2:
5:52
Yeah. So I guess, to start off, you can think of quantum computing as being like a superset of traditional computing. So with a quantum computer you can do everything that a traditional computer can do, but the idea is that it can do more. So with a traditional computer, typically, when you do operations on these bits, you use what are called logic gates. So, for example, if you have an AND gate, what that would do is, if you have, if both of your bits that are going to this AND gate are one, then the output would be 1. So it's like both bits are 1, then the output will be 1., and if either bit is 0, then the output will be 0. So, basically, you get bits that come in and then a bit or bits that come out, but a quantum gate acts differently because, again, these quantum bits can be in a superposition or a combination of zero and one, like anywhere on this sphere, and so because of this, the way that these quantum gates act is very different, and it acts in such a way to ensure that your probabilities make sense, essentially. And so I think, maybe to take like a step back, I think one way of understanding quantum computing is that we're changing the rules of the computer and just like if you change the rules of anything, say a sport like soccer, if you change the rules, then the sport can look really different and certain plays on the field might also come out very differently.

Speaker 2:
7:22
So, for example, in soccer generally you're not allowed to use your hands. That's why it's called football in most other languages. But if you change your rules and say every player can now use their hands, well, that's going to look really different. In some cases it'll be faster to just like swat the ball out of the air, to catch it, to run with it. But not everything is faster. If you want to get the field down the, if you want to get the ball down the field as quickly as possible, it's still probably faster to kick it than it is to throw it or to run with it. And so again, this is the idea You're changing the rules of the game. In some cases certain things are faster and so with a quantum computer we're changing the rules of the computer.

Speaker 1:
8:02
And in some cases certain things are faster. What about real-world applications that are leveraging things like quantum today? How are they really different? So I'm curious to kind of explore when is so putting it into the tangible of what do we see in the real world? What problems does quantum solve for us?

Speaker 2:
8:16
Yeah. So this is really interesting because, you know, quantum computing is certainly a newer field than our regular computers. We've been studying regular computers, how to build them, what they're useful for, for a much longer time than quantum computers, and because of that we're still sorting out exactly what problems they might be useful for. And so there's problems where we know for sure and there's problems where we kind of have some reasonable expectation or some guesses but we're not entirely sure yet, because doing the math to try to figure out what happens is very challenging and you can't just test the algorithms yet because we don't have big enough good enough quantum computers. Right, with a traditional computer, even things like with AI, like a lot of areas of AI, don't actually have math proofs to prove definitively that this AI system works. The reason we know that it works is because people tried programming it. You know they tried training their models and it worked. And so you know quantum computers are at the stage where we haven't built good enough quantum computers yet to test a lot of these potential applications, and so in some cases we don't know.

Speaker 2:
9:20
To give you a famous example of something that we do know is something called Shor's algorithm for factoring numbers, and so it turns out that traditional computers have a lot of difficulty factoring numbers. So factoring means, like you factor the number 15, that's writing it as three times five. So 15 is a very easy number to factor, right? 21 is easy to factor it's three times seven, right? People know that we have a really, really big number.

Speaker 2:
9:45
It's actually very hard in general for a computer to factor that, and that's actually the basis for all of our currently used public key cryptography systems, which is basically how we securely send information on the internet. So anytime you buy something from Amazon, you send your credit card information over the internet. You're using public key cryptography in order to ensure that your credit card information remains safe, so that only Amazon can view it when you send it to them. But quantum computers can actually factor quickly, which means that it would break public key cryptography. But don't worry, there's actually a replacement algorithms that are in the works that are going to roll out any day now, and so this is a very concrete problem that factoring numbers is something that quantum computer can do quickly, whereas it seems like classical computers cannot.

Speaker 1:
10:32
Right. So you mentioned Shor's algorithm. So I think for most listeners out there is, you know, if they're using something like AES-256, I think it's probably what with using classical computers. It will probably take a billion years to try to crunch that number, because it's what is it? 256 is something to the 256 power, what is it? Again, it's a crazy number, right. But with quantum is that they're saying? Is that you know, the more people I speak to in security, you know they're always talking about quantum computing, breaking AES-256. But then also they're also talking about Shor's algorithm, where you know it's leveraging the time to be able to break that within what? Eight to 10 years. But then even some people are speculating that it could possibly be a year or two, depending upon the technology advancement.

Speaker 2:
11:17
Yeah, I think so, if you look at what the US government has been doing to plan for this. Because, you know, shor's algorithm was invented in the mid nineties, so it's been 30 years now, right? So this is no surprise that quantum computers would be able to do this, and so you know, part of the reason why the National Institute of Standards and Technology, nist, has been working on standardizations for the next generation of cryptography algorithms to replace AES is because you know, like because we have known that this is coming right. And so the idea is that you know you don't need your information to be safe forever, right? Like I don't need my credit card number to be safe for 30 years because I get a new credit card number every I don't know handful of years, right? Or my credit card expires, I get a new one with a new number, and so you know a lot of the information that we send on the internet.

Speaker 2:
12:08
There's some time value to it, you value to it. After 30 years, all this information is out of date. If someone sees it, it doesn't really matter in terms of financial records. And so the idea is that we are starting to transition our cryptography systems now so that when quantum computers are available. Whenever they say 30 years, I don't know exactly. No one knows. The idea is that in 30 years time, if we decrypt the information now, that's okay.

Speaker 1:
12:35
That then then, like that, information is no longer valuable so the life of the data is basically almost kind of like end of life at that point, like it's almost irrelevant, right? Credit card numbers change, you know your address might change, um, your phone number might change. So most of that data is probably kind of uh data that you could, you could safely say we could probably do with that, because it might be kind of old or stale data. But you mentioned, you know, a very interesting topic around. You know how quantum computing is impacting fields like cryptography. How do we see it impacting the realm around artificial intelligence and kind of the emergence of, you know, ai and large language models.

Speaker 2:
13:12
Yeah, so this is where I mentioned that you know there's kind of two types of algorithms the ones that we know work better on a quantum computer and those where we don't know. And AI applications for quantum computing would be in that second camp of where we just don't know right. There's some people who kind of think, like intuitively, that quantum computers, because they can be in these combinations or superpositions of zero and one, maybe they can somehow do computation on large amounts of data better. But ultimately we don't know. And you know there are lots of scientists who are working on the math to try to figure out what would happen. We're trying to do simulations on like supercomputers or on prototype small quantum computers. But it's also possible that we may not know until we have a big enough computer to actually try it. And, like I mentioned, even with normal AI on a normal computer, in many cases we don't know if it's going to work until we actually try it.

Speaker 1:
14:10
So what's being? That's very interesting, is it? I wonder, kind of what's hindering that or what would be the leap forward to be able to get more of the AI and the algorithms into using something like quantum computing? Is it just the understanding of the quantum computing type, of different computing powers with the algorithm, or is it just we just don't have enough quantum computing to test all the algorithms with AI?

Speaker 2:
14:37
Yeah, so I think the biggest challenge that our quantum computers are not good enough yet and so all computers suffer from errors. So in a classical computer that would be one of your bits, like a zero accidentally becoming a one right, maybe there's some voltage issue or something, or like a cosmic ray can actually come and hit your storage device and can flip a bit from a zero to a one or one to a zero. And so there's all sorts of ways that traditional computers will correct for these errors. Or for example I don't know how old your listeners are, but remember CDs, whatever you use for music or for data. One of the issues is that it's like if your CD gets scratched right, then it might mess up your music. But actually in a lot of cases if you get a scratch on your CD it's actually still okay, like it still plays all right, and that's because there's different encodings that are used for the music. So that way if, even if some of your bits get flipped or damaged, it can still infer from the other bits what that error was and how to fix it.

Speaker 2:
15:37
And so with quantum computers, they also suffer from errors, and the challenge is that they are a lot more sensitive, and so if you go back to this sphere or this ball analogy, for a classical error you have to go from the North Pole, your zero, all the way to the South Pole, 201, or vice versa, in order to constitute an error. But since a quantum bit can be anywhere on the sphere, if you just move a little bit on that sphere, that's an error, and so it's much more vulnerable now, because any kind of movement on that sphere constitutes a different qubit versus a giant leap from the North Pole and the South Pole, and so quantum computers are a lot more vulnerable to errors, and unfortunately, there are methods to try to encode this information in such a way that if you have an error you can find it and fix it. But your hardware needs to be good enough in order to implement those strategies, and the hardware is not good enough yet.

Speaker 1:
16:38
Interesting. I mean it's interesting. I mean it seems like they're a little bit more fragile, more delicate than classical computers. Right, it seems like the technology is so advanced, but you mentioned this they're not good enough, which is interesting because you would think that you would have all of the best hardware to be able to make the quantum computer work right, as I mean I know that NVIDIA, google, amazon, they've all kind of got some elements of quantum computing. Are there different elements of quantum computing across different providers like Amazon, Google, or are they all pretty much all playing from the same field of same hardware, same type of operating system? Is it different or is it the same?

Speaker 2:
17:19
It is different, and this is one of the interesting things about quantum computing, which is that it's not necessarily the same type of hardware that we're using for traditional computers, although it could be. Essentially, to build a quantum computer, to have a quantum bit, you need to take any physical system that inherently behaves according to the laws of quantum mechanics. So just to maybe throw out some examples that people might have heard of before. So, for example, with light, people might have heard of a photon. So a photon is commonly called like a particle of light, and so light has a property which is called a polarization. So you may have sunglasses that are polarized, that will help cut out glare and things like that. And so an individual photon, this single particle of light, also has polarization, but because it's a single particle, it behaves according to the laws of quantum mechanics, and so instead of having a polarization that is solely vertical or solely horizontal, it can be in a superposition or a combination of vertical and horizontal, and when you measure it, you force it into being vertical or horizontal, and so you can think of these two polarizations, vertical and horizontal, as being your zero and your one, and so there are some scientists and companies that are pursuing quantum computing, using photons, for example. There are others that are using superconducting circuits, where you have current in this, in this circuit, and if you get it very, very cold, like at a millikelvin, so you know just fractions of a degree above absolute zero, it turns out that this starts to act in a quantum mechanical way and you can actually use that as your quantum bit.

Speaker 2:
19:02
There are people that are using individual atoms as their quantum bit and different like energy levels of the atom. You're looking, people are looking at trapped ions, so those are charged atoms. There are approaches using the spin of an electron, so this is like the Ingram momentum of an electron, which again is something that behaves according to the laws of quantum mechanics. And so there are so many different approaches and more than I've mentioned here, because not one of these approaches has won yet has demonstrated that that is the approach to go and this kind of mimics the evolution of our traditional computers.

Speaker 2:
19:44
Right, like before transistors, there are all sorts of different approaches and people had to discover, like, what are better ways to build computers? You can start with vacuum tubes and relays and things like that and eventually, once the transistor was developed and then further matured over the course of decades. Now we have our transistor based CPUs, right that that are amazing or small. You know fast and everything. And so you know in some sense we haven't reached a point of having like the quantum version of a of a transistor. And even when we do, you know it may still take decades to mature it to the point that you know we have our amazing computing devices in our pockets, in our cell phones.

Speaker 1:
20:25
It's interesting. What do you, what are you seeing from the student perspective of students that you're teaching at the university? What are some of the things that they need to understand getting into a program where they're understanding quantum computing? And what are some of the things that they need to understand getting into a program where they're understanding quantum computing, and what are some of the things that they're learning as they're going through the journey of understanding it? From the university perspective, I'd be interested to know kind of what happens kind of in the classroom.

Speaker 2:
20:49
Yeah, I would say that students can have a place in quantum computing from a very wide range of backgrounds, just like with traditional computing. Computing from a very wide range of backgrounds, just like with traditional computing. Like, there's no one who really is a master of every single part of a computer. Right, you have software people, you have hardware people. Even within those two designations, there's so much level of expertise right when, and then even beyond that like technical side, there's the people who work in the business side, right, in the marketing and sales. You know everything. Right, there's this whole ecosystem. Then there's all the additional technologies that support, uh, computers, um, and so you know, I want to just, you know, emphasize that with quantum computing it's going to be similar. Right, there's people who are going to work on the software side. There's going to people who work up in the hardware side. Even on the software side, you have people who are maybe working more on the math and the theory of things. You have people who are going to work on the software side. There's going to be people who work on the hardware side. Even on the software side, you have people who are maybe working more on the math and the theory of things. You have people who are working more on coding and programming challenges on the hardware side.

Speaker 2:
21:47
Another thing with quantum computers is that quantum computers don't exist in a vacuum. It's not like you just have a quantum computer To build a quantum computer. You also use classical computers to be adjusting all of the knobs and voltages and lasers and things like that that are going into controlling these quantum mechanical systems. And so, just like traditional computing is very diverse in the backgrounds that people have, whether it's engineering or physics or math, computer science, chemistry, business all these various fields Quantum computing is going to be similar and so, yeah. So in the field I see students that come from a traditional physics background who are doing the research, but there's also a lot of people who come from, say, math or engineering or computer science or people who are on the business side, who are interested in how emerging technologies might affect business.

Speaker 1:
22:38
Interesting. So it seems like it's kind of like you know, like you mentioned, in today's world is that you have a lot of people from different disciplines, different spaces of expertise all kind of coming together to be able to kind of work on maybe a common problem, where they all work together as a team to solve problems. And I see this a lot across the different industries, with encompassing artificial intelligence. You have a lot of people from different backgrounds and different technical and non-technical disciplines doing some very interesting things. What are you and kind of shifting a little bit what are you seeing kind of from the future perspective of what would you like to see happen in the quantum computing space? From the technologist perspective and some of the folks in my space are technologists what are you looking for from the technologist in terms of innovation or something that might be new, that you would see advance quantum computing?

Speaker 2:
23:28
I would say that approaching quantum computing from the perspective that there is still a lot of basic science and research to be done, I think you know, sometimes people like to hype up emerging technologies which is true of any emerging technology, not just quantum, but certainly quantum is guilty as well, where people might say things like you know, quantum is going to cure cancer next year.

Speaker 2:
23:51
You know it's going to solve climate change next year, right?

Speaker 2:
23:54
These are some of the claims that that sometimes come out, and you know I would say that you know, between the like, the like, the two applications, the ones that we know quantum computers can do, and those where people are kind of like, speculating or maybe have a guess, I would say those are very much more on the the guess or the speculating side, right, sometimes people can be very optimistic, and so, like I mentioned earlier, even once the transistor was invented, it still took many decades to reach the point where we had CPUs that are built using transistors, and so you know there's still a lot of work to be done.

Speaker 2:
24:28
I think there's a famous quote I can't remember verbatim, but to paraphrase, it's basically something along the lines that we tend to overestimate the near-term consequences of new technologies but underestimate their ramifications long-term. And so you know, I think, long-term, yes, quantum computers will have a huge impact on our society, just like traditional computers basically touch every aspect of life now. But you know, and I think you know, it's very hard for us to just to understand just how big that impact could potentially be, just like the early creators of computers, you know, didn't understand that we would have this conversation now, you know, over the internet, using our computers. But you know, in the near term, I think, we tend to overestimate how much work still needs to be done. And so, yeah, so in terms of you know, what can technologists bring, I think, just having an understanding that there is still a lot of basic work to be done.

Speaker 1:
25:32
but there is also a place for people to start thinking about you know what is your perspective on kind of what you're seeing in the landscape in the next three to five years, your predictions.

Speaker 2:
25:43
So I think there's going to be a lot of continued growth from various sectors in quantum computing.

Speaker 2:
25:48
Certainly, in the past handful of years, the rise of like industry involvement in quantum computing has been huge right computing has been huge right.

Speaker 2:
26:00
Historically, quantum computing has been mostly in the academic setting that people have been thinking about and doing the basic research on what might quantum computers do and how one might begin to build them. But now that we're getting closer to quantum computers being useful, the investment from companies, both in the hardware and the software, has grown a lot, and so I'm expecting to see a lot more work on that. But, like I mentioned earlier, like we still don't know which approach is the best, and so I think there's still going to be a lot of you know, announcements from these different camps and different approaches saying like you know, we've reached this new breakthrough, we've reached that new breakthrough, but you know I breakthrough, but we're not going to know really which one is going to win out, and I think there's still going to be quite a bit of work and it might be that there's going to be some completely new approach that people haven't tried yet Interesting.

Speaker 1:
26:49
It's going to be interesting to see what happens in the next three to five years. I think that there's a lot of hype going on, especially with artificial intelligence. We're kind of in that hype cycle right now A lot of excitement's a lot of hype going on, especially with artificial intelligence. That you know we're kind of in that hype cycle right now A lot of excitement, a lot of enthusiasm and, to your point, kind of around quantum is that there's also a lot of excitement. Probably a lot of you know over over excitement where there's there's not a lot of. There's not a lot there there just yet, but it how the landscape plays out. Tom, I really can't thank you again for coming on the show. Your insights has been very invaluable to our listeners and thank you for enlightening us on this topic and we really gained a lot of insight from your experience on this topic. Any final thoughts on where we can follow you? Keep up to date with your latest journeys and papers and things that you publish.

Speaker 2:
27:35
Yeah, if you want to see more about my work, you can go to my website at thomaswongnet. So it's just my name, thomaswongnet.

Speaker 1:
27:41
And you also have an X account, right, I do.

Speaker 2:
27:43
Yes, and you can find my handle on my website.

Speaker 1:
27:51
Wonderful. Thanks again, tom, for your wonderful thoughts on this topic and thank you to all of our listeners. Thank you for tuning in and, as always, fellow travelers, stay curious, stay informed. Most of all, happy travels, thanks.