The Quantum Threat to Encryption Is Already Here | Dr. Shohini Ghose

Vit Lyoshin (00:01.794)
Dr. Shakini Goose, welcome to the podcast. Thank you for your time today.

Shohini (00:07.234)
Course, glad to be here. Thanks for inviting me.

Vit Lyoshin (00:09.346)
Yeah, this is an exciting topic for me. This is the first time I'm going to be talking about this. So let's see how it goes. So first I wanted to ask because I read some news and I check out about the quantum computing industry and I see some companies investing a lot of money in this. I checked IBM is going to be investing about 10 billion in like next five years or so.

US government is investing heavily. Why do you think companies invest in this technology?

Shohini (00:45.686)
well, I think that they all are, you know, realizing that we are at a point where this is b quickly becoming a global race to build that large scale quantum computer. And in fact it's not just the computing piece, and I'm sure we'll get into this in our conversation, but essentially quantum technologies because you know, engineering and all of the pieces needed to make this work, they're s they're getting developed pretty fast.

So this is a point where investing in it and having a long term strategic plan will eventually determine who gets there and and what it will be able to unlock in terms of advantage. So yeah, it's the start of a race. So this is what we're seeing now is everybody basically laying down their dollars and, you know, betting on the race.

Vit Lyoshin (01:15.384)
Mm-hmm.

Vit Lyoshin (01:38.06)
Yeah, okay. And do you think that quantum computing is like the next major computer revolution or something like that?

Shohini (01:48.108)
Well, I think that's the expectation and part of the the problem with I'm trying to answer that question is we can't quite predict the future. I think a lot of people are really, of course, investing and counting on something coming out of all of these investments that will help transform some technologies, if not all. So it's going to be a matter of where the innovation really can, you know, really

Vit Lyoshin (01:51.15)
Hmm.

Vit Lyoshin (01:58.392)
Sure.

Vit Lyoshin (02:11.67)
Mm-hmm.

Shohini (02:17.515)
Be unlocked in ways that will be both scalable as well as commercially viable, right? So there's two pieces. On one hand, you have all the science and the technology. And a lot of that has already been, you know, proved in principle, meaning in the lab and with experiments. It's not this the science is solid, but going from the science to the engineering to the scalability, that's the process that is still a little bit unpredictable. So that's why I have to answer, yeah.

Vit Lyoshin (02:32.716)
Mm-hmm.

Vit Lyoshin (02:36.235)
Mm-hmm.

Vit Lyoshin (02:43.261)
I see, okay. Yeah, okay, I see. Yeah, no, I think everything with emerging technologies is kind of goes the same thing, right? First, you do a lot of research and development, lab work, proof of concept, and then commercial company start.

Shohini (02:52.043)
Yeah, exactly.

Vit Lyoshin (02:59.725)
messing with it and doing something in the real world and figure out how it works because right now I think a lot of people are just waiting to see what happens here. Just like with AI it happens, same thing. Nobody really knew what it is and then this huge wave came in and everybody now kind of absorbing. Yeah.

Shohini (03:10.273)
Tulsa.

Shohini (03:17.119)
Yeah. Yeah, that's a really good point that it this is not new. This happens with almost every such technology except all of that R and D piece usually is done in the background where it doesn't hit the media and the headlines. But once it gets to that point where it's actually applied, now it's we it looks like it's sudden because now it is mainstream.

Vit Lyoshin (03:31.509)
Mm-hmm.

Shohini (03:39.628)
But it's actually not sudden. Even AI, of course, there was decades of research and development happening. So there's never really a sudden change. It's always a slow process. The sudden piece is only the part that we see right at the end. So it's sometimes a little different because now it feels like even the R and D part is be getting a lot of attention more broadly. So usually that part is more hidden and it's been going on for a long time, but people are starting to

Vit Lyoshin (03:40.086)
Yeah.

Vit Lyoshin (03:45.494)
Mm-hmm.

Vit Lyoshin (03:54.123)
Alright.

Vit Lyoshin (04:00.257)
Hmm.

Vit Lyoshin (04:07.629)
Yeah.

Shohini (04:08.725)
you know, see it more just because of the h huge amount of investment going into.

Vit Lyoshin (04:12.851)
Mm-hmm. I see. So why don't we get into this and just define what is quantum computing?

Shohini (04:22.841)
well, that's going to be hard to do in you know in in a a few sentences, but I think most importantly, we need to step back and think about what is computing itself and then maybe go from there, just as a more of a familiar place to start. I think most people are aware that our computers work based on a very, very simple logic system of true and false, which is converted into zeros and ones. So binary logic is what.

This has all been based on. And that is a really convenient thing because essentially every calculation and every such logical operation we need to do can be just broken down into, you know, almost like the most basic Lego pieces, if you like, that we can build all computation from, right? No matter how complicated. So binary sort of computing based on the binary digit, which is the bit, is how our current computers work.

Vit Lyoshin (05:10.155)
Mm-hmm.

Shohini (05:18.857)
Now, quantum computing is a completely different, meaning we have to literally go back and change that fundamental Lego piece of the binary digit or the bit and think about a quantum Lego piece, which is a quantum bit or a qubit. And so quantum computing is essentially a different way of computing where we don't start with zeros and ones, but we start with this idea called superpositions of zeros and ones, which is essentially like saying you have a bit that

Vit Lyoshin (05:18.965)
Mm-hmm.

Vit Lyoshin (05:33.172)
Mm-hmm.

Shohini (05:47.404)
Has a probability of being a zero or a probability of being a one. So it's like a knob rather than a switch, if you like. And starting from that, you have to rethink what do you mean by adding and subtracting, for example, zeros and ones? Well, how else can you combine these probabilistic superpositions? So you literally have to build up a whole framework of operations of logic. We still want to do the same thing, which is we want to do complicated calculations, let's say, or we want to send information securely.

Vit Lyoshin (05:51.351)
Hmm.

Mm-hmm.

Vit Lyoshin (06:14.497)
Mm-hmm.

Shohini (06:17.205)
So the goals are the same, but how we do it is actually going to change. We're not relying anymore on just bits, but on these quantum bits, which are more generalized kinds of ways of encoding and manipulating information. And turns out it can be very, very powerful for certain types of tasks. And so that's why quantum computing offers a lot more potential. Our regular computers are like a subset of that much larger.

Vit Lyoshin (06:32.182)
Mm-hmm.

Shohini (06:45.727)
potential of quantum computing. So that's broadly what we're trying to do is use this new way of thinking about computing itself. And then therefore we instead of going with these switches, which is what our current hardware is, we have to build new hardware can that can use this knob of probabilities. That's why you need to change the software and the hardware. And that's what everybody's trying to work on in this space.

Vit Lyoshin (06:47.925)
Mm-hmm.

Vit Lyoshin (06:54.059)
Mm-hmm.

Vit Lyoshin (07:03.37)
Right.

Vit Lyoshin (07:06.999)
Yeah.

Vit Lyoshin (07:10.709)
Yeah, that's a whole big new problem to solve. Do you have any sort of good analogy for somebody who's new to this quantum computing, how to think about these probabilities of being 1 and 0 or like a spectrum or some sort of so people can visualize it a little bit in their heads?

Shohini (07:31.28)
unfortunately, there's no such thing as an accurate analogy for quantum because it's outside of our everyday experience. So, one thing that you know a lot of people have used for the visual is you know, with regular zero and one probabilities, you can think of a coin, right? Having heads or tails. That's like a probability, probabilistic kind of model. So 50% chance of getting heads, 50% chance of getting tails. But in fact, that is

Vit Lyoshin (07:37.655)
Yeah.

Vit Lyoshin (07:47.778)
Mm-hmm.

Vit Lyoshin (07:51.17)
Right.

Shohini (07:58.582)
That's not enough to visualize a quantum bit. It's not just a coin flip. It's essentially like having a quantum coin is like having a s situation where when you're flipping the coin, it's not like one side is heads and the other side is tails and you don't know which is which. It's like both sides kind of have heads and tails, right? And until it Yeah. So until it literally lands and you look, you don't have any information. So it's like having a

Vit Lyoshin (08:18.295)
So it's like sideways.

Shohini (08:27.837)
Heads and tails on both sides of the coin. And even that's not really an analogy because, of course, there's no such thing as heads and tails. How do you even visualize it? So, one of the biggest challenges of quantum is that yes, we cannot imagine these kinds of possibilities all coexisting, but at the quantum level of, let's say, an electron or a photon, this you know, very microscopic subatomic level, for example, there are you can actually observe the the sort of

Vit Lyoshin (08:35.435)
Yeah, yeah.

Shohini (08:57.985)
Consequences of this kind of very fluid, you know, identity, if you like, where where you don't know even if there is a one particular reality. The reality itself is more fluid at that level, which is so hard for us to experience because we have one fixed, you know, way of thinking of heads and tails and coins. But

Vit Lyoshin (09:11.189)
Mm-hmm. Yeah.

Vit Lyoshin (09:19.362)
Yeah.

Shohini (09:19.935)
That's the closest we can get to an example. If we could have a perfect way of visualizing quantum, it wouldn't be quantum because then that means it's just part of what we already know, which is what we call classical. So this is the real frustrating part of trying to talk quantum because we don't even have any experiences that we can literally hold on to and say, Yep, this I've experienced quantum. We can't experience quantum. We can experience gravity, but we don't really experience quantum, unfortunately.

Vit Lyoshin (09:29.261)
Sure.

Yeah.

Vit Lyoshin (09:49.228)
Yeah, I think that's why quantum physics is so hard and not so many people study it because you have to have a special brain, I think, a way of thinking to think in those terms.

Shohini (10:00.736)
Yes, outside of like it's literally like having yeah, you need that imagination because it's not something you can see and feel and touch. Yeah.

Vit Lyoshin (10:05.759)
Yes.

Yeah, yeah, yeah. Okay. And then why scientists started working in this field and trying to come up with a new way of computation? What the problem was or like why? Why they start this?

Shohini (10:22.284)
That's a great question. So, quantum science itself is actually quite old in the sense that it was developed back in the early 1900s. And back then it was developed because, you know, scientists at the time they had made some observations of certain ways of, you know, certain objects had particular properties of radiating energy, or there were some experiments that they couldn't quite understand what they were seeing in terms of current flow in particular circuits.

Vit Lyoshin (10:27.713)
Mm-hmm.

Mm-hmm.

Shohini (10:51.362)
So, because those things didn't fit the existing theories, which is what we call old classical mechanics, electromagnetic radiation, and so on, they had to develop a new theory. And that theory eventually is what we call quantum mechanics. And it was it's a really powerful theory because it ex it it essentially describes precisely the behavior of all particles in the universe, right? So that's quite a quite a powerful kind of way to.

Vit Lyoshin (10:51.446)
Mm-hmm.

Vit Lyoshin (11:17.665)
Mm-hmm.

Shohini (11:21.068)
Think about the universe as one description. And so whether it's electrons or atoms or photons or everything, that's all part of quantum mechanics. So that's been developed over the last century. And this is why we understand the periodic table and we understand different types of elements, including silicon, which led us to building our current computers because we know how to control electronics, you know, based on the properties of silicon, for example.

Vit Lyoshin (11:25.697)
Mm-hmm.

Vit Lyoshin (11:42.966)
Mm-hmm.

Vit Lyoshin (11:46.667)
Yeah.

Shohini (11:50.039)
But at some point, even our current computers, as you know, they get keep getting smaller and smaller and more powerful. And now we have computing power even in our phones and so on. So inside these devices, these chips or these you know circuits that are that are actually doing all of these calculations, they're getting smaller and smaller and smaller. And at some point, they get to that atomic level. And at that level, you can't really just rely on, as I said, the switching behavior of zeros and ones.

Vit Lyoshin (12:10.294)
Mm-hmm.

Mmm.

Shohini (12:19.788)
Getting into that more fluid probabilistic zone. So at that point, you have to think, okay, now I need to switch to not switch, but I need to think about including this quantum probabilistic behavior. So that's part of why scientists started thinking more carefully about building out hardware and devices at that scale. It requires a little more, you know, sort of.

Vit Lyoshin (12:23.969)
Mm-hmm.

Shohini (12:47.906)
change in the way that we can control these circuits. And on top of that, from the computing part, there's always, you know, problems in, you know, in computing in different sectors where even with superconductors, supercomputers, they can be very, very difficult to calculate. So things like modeling, you know, certain types of materials, if you want to know how to build out you know, better materials for, I don't know, solar cells.

Vit Lyoshin (13:06.156)
Mm-hmm.

Shohini (13:17.204)
Or if you want to figure out better pharmaceuticals and you want to do some simulations, it's actually the kind of problem that becomes very, very challenging, even with supercomputing. So if you can keep increasing your computing power, you can do better in all of these ways. So this is another reason why scientists were saying, well, on one hand, we're going to hit this scale, this tiny scale, where quantum

Vit Lyoshin (13:17.601)
Mm-hmm.

Vit Lyoshin (13:28.201)
Mm-hmm, yeah.

Vit Lyoshin (13:41.751)
Mm-hmm.

Shohini (13:43.651)
Things like superposition become important. And on the other hand, we also know that there are problems that we cannot solve solve with our current supercomputers. So we need better computing. So the two kind of intersected. And that's why scientists started thinking more deeply about how do we unlock the power of that quantum scale to do computing even better.

Vit Lyoshin (13:51.425)
Mm-hmm.

Vit Lyoshin (14:03.149)
Yeah, that's interesting because potentially we could have like a really really small computers that can go like even like inside the body or out in the space somewhere and it's easy to launch them far away and they still gonna be pretty powerful in terms of doing some tasks and stuff. Yeah, that's very interesting. Okay. So you mentioned something about superposition.

the concept of it. And I know there is also another one is called entanglement. So can you talk a little bit about both and what they mean and how it works?

Shohini (14:43.008)
Yeah. So I'd say superposition and entanglement are sort of the key building blocks of this new type of computing called quantum computing. So superposition, as I was saying, is a way of it's really describing the fact that these qubits are not just specifically precisely zero or one, right? They are in this superposition is essentially a mathematical way of combining these probabilities of zeros and ones, right? So there's technical details there, but essentially it's

Vit Lyoshin (14:52.193)
Mm-hmm.

Shohini (15:12.3)
Probabilistic description of zero and one. And entanglement is essentially like a you know describe using superposition to describe more than one qubit. For example, you know, one of the qubits is a superposition of zero and one. What if you have another second qubit? So each of them could of course individually be in the superposition, not quite zero, not quite one, maybe sixty percent, forty percent kind of superposition.

Vit Lyoshin (15:15.511)
Mm-hmm.

Vit Lyoshin (15:38.956)
Mm-hmm.

Shohini (15:39.821)
But what if they start talking to each other? Turns out that quantum particles like you know atoms and electrons and photons, they can of course interact with each other and then they get locked together. So they become very, very connected. So that if one of them is a zero, the other one is also a zero, no matter where they are in the universe, and also vice versa. But individually they actually are not exactly zero or one because they're in a superposition.

Vit Lyoshin (15:51.724)
Mm-hmm.

Vit Lyoshin (16:03.137)
Mm-hmm.

Shohini (16:07.308)
So entanglement is this bizarre connection, which is like a balance of you know probabilities of you know in in the superposition model, but also this connection where individually they don't really have a particular value, but if one of them is zero, the other one's definitely zero. So it's both knowing and not knowing them, right? Jointly there is perfect information connection, correlation, but individually.

Vit Lyoshin (16:33.805)
Interesting.

Shohini (16:35.106)
They have, they still maintain their very fluid identity. So that kind of a balance turns out to be a very powerful knob for computing. It sounds like it wouldn't be because, you know, what does that even mean? But when you write down the math, it gives you those extra sort of things that you can control a little bit more, you know, through this kind of almost like a remote control between the two qubits. So this turns out to be.

Vit Lyoshin (16:44.439)
Mm-hmm.

Vit Lyoshin (16:59.063)
Yeah.

Shohini (17:02.676)
A powerful thing if you are clever about how you use it. Because you want to get the correct answer, the precise task that you're trying to do has to be, you have to achieve it, but you have to somehow also not get sort of stuck in the world of probabilities where you don't know exactly something, right? Because in the end you want an exact answer. So you have to control the probabilities and force them to give you the right answer with high probability and the wrong answer with low probability.

Vit Lyoshin (17:06.966)
Yeah.

Vit Lyoshin (17:24.461)
Mm-hmm.

Shohini (17:32.15)
So you have to it's almost like a game where you you try to flow through this interesting landscape and get there. So superposition and entanglement together are the are the two knobs that we try to use to solve our tasks. Yeah.

Vit Lyoshin (17:34.623)
Yeah.

Vit Lyoshin (17:46.305)
Mm-hmm.

Yeah, I guess, yeah, well, it's a really more complicated math that has to be incorporated here. That's, guess, an advantage here in the computation. And also it's a very specific use cases, right? You're not going to just do simple like two plus two calculations with that. You're going to have to do something a little bit more complicated than that. Yeah.

Shohini (17:57.719)
Yeah, exactly.

Exactly.

Shohini (18:13.718)
For sure. Exactly. It's like having a few more operations, not just your addition and subtraction. What if you could do other things, right? You could perhaps dream up new math. So it's kind of like that. Yeah.

Vit Lyoshin (18:20.095)
Yeah. Yeah.

Yeah, okay. So just to wrap up this part of the conversation, are there anything that you hear from people that they maybe don't understand about quantum computing, some misconceptions, some hype or something like that that you can mention and kind of like maybe, you know, clear the clouds in terms of this? Yeah.

Shohini (18:39.896)
Yeah.

Shohini (18:48.428)
For sure. I mean, I'm sure there's lots of you know confusion around it just because it's such a strange way to think about computing. But one that comes up a lot around entanglement. You know, people talk about, there's instant connection between these particles, and they can be on others on opposite sides of the planet, and the particles are connected. So that means instant communication. That's unfortunately not true. We can't actually send instant messages across the universe, even though.

Vit Lyoshin (18:59.211)
Mm-hmm

Shohini (19:17.034)
Entanglement is a real thing. You can test it in the lab. And the com the particles are definitely connected in this instant way, where if one of them is a zero, the other one is also a zero. But remember, I also said that it's probabilistic, meaning sometimes it's a zero, sometimes it's a one. So when you when you actually look at the particles. So if I want to send a pr precise message, I can't because of that randomness as well. So

Vit Lyoshin (19:21.185)
Mm-hmm.

Vit Lyoshin (19:41.895)
Mmm, okay.

Shohini (19:43.765)
So, this idea of instant communication, unfortunately, it breaks this barrier. You know, you can't send anything faster than light, like not messages. So entanglement seems to be an instant connection, but we can't use that instant connection to communicate a message faster than the speed of light, unfortunately. We can do some things, but we can't do that. So that's a misconception that people may have about this instant connection.

Vit Lyoshin (19:51.713)
Mm-hmm.

Vit Lyoshin (20:05.013)
Mm-hmm.

Shohini (20:11.936)
Instant communication is still not possible, sadly. Yeah.

Vit Lyoshin (20:15.177)
Okay, okay, I understand. So the next question I have is, so we have the normal computing, we used for many different things and it worked great. Now we have quantum computing. Are we trying to use quantum computing for the same type problems or is it going to be like a different set of problems that we need quantum computing for to do better job basically?

Shohini (20:42.584)
So that's actually a really important question. Why are we even trying so hard? Obviously, for things like email and things like this, our computers are just fine. But so there are particular areas where we know that, as I said, there are bottlenecks where things become really, really hard to do even with our regular computers. Those are the areas where we would like to apply quantum computing. So some of the examples I gave are I think the ones that a lot of

Vit Lyoshin (20:52.46)
Mm-hmm.

Vit Lyoshin (21:02.028)
Mm-hmm.

Shohini (21:11.756)
folks around the world are looking at. So being able to t you know try to understand the behavior of things like molecules, right? So that may sound like, that's not necessarily that interesting. But of course, if you can understand how certain molecules behave, you can see how they interact with, let's say, our tissues and our body. So then you would be able to develop better treatments, you know, for example, better drugs. So pharmaceutical inter industry is interested in that.

Vit Lyoshin (21:36.449)
Mm-hmm.

Shohini (21:40.483)
But molecules, of course, are you know really important to understand if you want to create, develop, I don't know, chemicals for the agriculture industry, or materials, as I said, for you know, solar cells andor better ways to build batteries. All of this has to be understood at the molecular level. So even though it sounds like a boring math problem, it has a lot of potential applications. So th those are the kinds of areas where I think.

Vit Lyoshin (21:58.188)
Mm-hmm.

Shohini (22:07.768)
Quantum could have potential application. and we may not even notice it in our everyday lives. Kind of like how we don't really think about exactly where our, you know, whatever medication that we use for perhaps some illness. We don't when we go and get it from the doctor, we don't really think about all the different pieces needed to make that medication. So we again, it's not part of our everyday lives, but of course it changes us, right? We

Vit Lyoshin (22:33.439)
Yeah.

Shohini (22:37.442)
We all are benefiting from the healthcare industry. So, in a way, it's a going to be an indirect impact on many such industries.

Vit Lyoshin (22:37.794)
Mm-hmm.

Vit Lyoshin (22:47.147)
Yeah, yeah, I think it's like with the normal computers, right? First we had big mainframes, only certain industries used that for calculations. And then some people converted it to personal computers, and now we all have it. So eventually, quantum computing could become the same. Now only certain labs or...

Shohini (22:55.988)
Exactly. Yeah.

Shohini (23:01.184)
Yeah. Yeah.

Vit Lyoshin (23:11.169)
companies will use it and then eventually people everywhere may need something to calculate really quick that complicated. I don't know. I'm just guessing and wondering here.

Shohini (23:18.136)
Yeah.

Yeah, if you want

That's I mean, I would say that it's unlikely that we will need it, but you know, let's say tomorrow there's some huge breakthrough where we can build quantum computers very cheaply and easily, right? In that case, you could do things like designer, I don't know, drug development for your put personal body or your personal healthcare needs, and you just plug it into your private quantum computer and it calculates something for you. Maybe. But I don't think this is the first step by far. We're talking about

Vit Lyoshin (23:36.683)
Mm-hmm.

Vit Lyoshin (23:48.769)
Right.

Shohini (23:54.381)
Possibly that never happening because mostly we don't really operate that way, right? We don't have that kind of specific needs. so will we get to the point where each of us will have access to quantum computing? Not in the first case. You're right. It's gonna be more like if you think of it like mainframe computing that will be probably built in parallel with, you know, how they're building data centers for doing AI?

Vit Lyoshin (23:59.288)
Yeah.

Vit Lyoshin (24:20.011)
Mm-hmm.

Shohini (24:20.408)
And we'll all be logging in, and we already log in online to use AI, right? We don't we don't actually download Chat GPT, for example, onto our machine. We're just using it through the cloud. So I think if we do have needs of quantum, it'll probably be first set up that way, cloud based. Because why give everybody devices if you don't need to, right? They'll be more like portals where we will perhaps be able to access it if we need it. But I think it'll be very specific, yeah.

Vit Lyoshin (24:25.184)
Right, yep.

Vit Lyoshin (24:32.459)
Mm-hmm.

Vit Lyoshin (24:37.279)
Mm-hmm

Vit Lyoshin (24:42.539)
Sure.

Vit Lyoshin (24:47.061)
Yeah, yeah, just as a service. okay. Understand. So I guess another thing I know people saying like, will they replace normal computers? I guess the answer is no, not anytime soon. Like keep using your phones and personal computers for everything. Yeah.

Shohini (25:06.41)
Yeah, I think our our the platforms will look the same. The back end will always be changing and im evolving and improving. And we may not even know. Some perhaps at some point we will be, you know, running some calculation and we just submit a job to the whatever service provider, and that provider will decide whether to access quantum or AI or some mix of the two. In fact, that kind of service is already being developed and offered by companies like.

Amazon, if you go to AWS, Amazon Web Services, it has that option where if you have a problem, you can submit it and it will, you know, they will help you to figure out how, you know, how to access whether you need the quantum or the you know, other like AI and or some combination. So I think that's the model, and we are right. We perhaps may not see much the everyday user is not gonna really see that change like right away. It'll be on the back. Yeah.

Vit Lyoshin (25:39.724)
Mm-hmm.

Vit Lyoshin (25:53.387)
Mm-hmm.

Vit Lyoshin (26:03.379)
Right away, yeah. Yeah, okay. Yeah, you kind of mentioned this already, but I had a question about like real world applications today that maybe you know of, like you mentioned Amazon right now, but maybe you know some other places, like something that's being done in pharmacy, like you mentioned, or maybe space tech or mining or whatever, maybe you can mention.

Shohini (26:10.904)
Mm.

Shohini (26:26.88)
Yeah. Yeah. So I think currently we have to keep in mind that we're talking very, very early days. It's early stage in terms of the technology develop development itself. So it's yes, there are companies out there who are offering commercial level quantum hardware and technologies, but honestly they are

Vit Lyoshin (26:39.873)
Mm-hmm.

Shohini (26:50.25)
You know, it's kind of like going back to the 50s when the of course there were computers also available, but they couldn't really do much and most people couldn't access them. So right now, also you can go, for example, you can go on IBM and create an account and you know buy time on their quantum computer or on D-Wave, you can do that, or Amazon. So you can certainly subscribe and get access to a quantum computer, but what would you calculate? Turns out that these machines are not yet.

Vit Lyoshin (26:58.604)
Yeah.

Shohini (27:16.802)
powerful enough to do very, very large-scale computing. Some areas and examples where they have been used for commercial style applications have been in what we call logistics and optimization. Turns out that there are certain tasks that current computers can do for things like, you know, scheduling, things like, you know, if you're delivering, if you have to, you know, maybe you're FedEx and you have to deliver

Vit Lyoshin (27:20.269)
Hmm.

Shohini (27:45.505)
Services and goods to people, right? So, how do you optimize your delivery routes? turns out that there are quantum approaches that may help you, depending very much very specifically on your problem. So that's an area where you can actually access quantum tools to solve those kinds of problems. But mostly you want to use it in combination with existing computing power because of course we already have quite a lot of powerful computing, right?

Vit Lyoshin (27:48.897)
Mm-hmm.

Vit Lyoshin (27:56.716)
Hmm

Shohini (28:12.468)
So most companies currently that are test are are trying these quantum approaches are testing and benchmarking compared to their existing computing. And in many sectors, you're right, in the space technologies, they are certainly trying to use quantum to do better things like sensing, right? You you you you want to be able to do better imaging, for example, or and and honestly imaging is very important even for things like I don't know, finding new resources and minerals or imaging.

you know, below the oceans and things like this. So that's another area, like this whole area called quantum sensing technologies is actually a growing area. and turns out entanglement can h help you get better high precision imaging, which is quite fun to actually think about as a scientist, but also for various sectors. So those are areas quantum communication, telecom sector, you know, better being able to s you know

Vit Lyoshin (28:46.625)
Mm-hmm.

Vit Lyoshin (28:53.921)
Mm-hmm.

Shohini (29:12.492)
build out better communications networks is of course another big area where quantum could be helpful. So yeah, there are some areas, but I would say currently there's not really an example of real quantum advantage at the scale that you might want. That makes it, you know, sort of reasonable just to move over entirely to quantum because keep in mind this is very expensive. The technology is quite limited.

Vit Lyoshin (29:21.996)
Mm-hmm.

Shohini (29:41.535)
And so you need a lot of resource and a lot of changing over of your hardware and your infrastructure. So you have to make calculation, is it worth it, is it not? Currently, most part, it's not really worth it unless you're looking at critical problems. Like if you really think you can, I don't know, help to perhaps improve our chances of developing a cure for cancer. Even if it's a small step, you would take it, right? Even if it costs a lot.

Vit Lyoshin (29:48.758)
Mm-hmm.

Yeah.

Vit Lyoshin (30:08.641)
Mm-hmm.

Shohini (30:10.37)
So that's why I'm saying it's a very much d dependent on your particular problem and what are the stakes. Right. So yeah, that's how you have to think about it. Yeah.

Vit Lyoshin (30:16.489)
I see. Yeah. Okay. I also find out from my research and online browsing in cybersecurity and some people saying quantum computer help us like crack any sort of code over there or encryption and things like that. Can you tell us a little bit about that? Like what's the, what are the like promises for the cybersecurity to help protect things or

crack things and stuff like that.

Shohini (30:49.238)
Yeah, so I'm really glad you brought that up because it's not all h happy, happy good news about quantum. In fact, the biggest application that which actually did also kickstart this whole quantum race is because we know that there exists a quantum approach that can hack into all of our current encryption, right? So we use some very standard global encryption protocols just because everything, you know, is constantly being communicated around the world.

Vit Lyoshin (31:03.009)
Mm-hmm.

Shohini (31:17.228)
So we have global encryption standards, and they have been in place for you know decades. But now we know that the particular global encryption standard, which is called RSA, is vulnerable to a quantum algorithm that was developed by this scientist named Peter Shore. So Shore's algorithm can actually crack our current encryption. So now it's just a matter of somebody building a large-scale quantum computer that is powerful enough to actually

Vit Lyoshin (31:17.516)
Mm-hmm.

Vit Lyoshin (31:35.627)
Mm-hmm.

Vit Lyoshin (31:40.183)
Hmm.

Shohini (31:47.363)
Go through and implement Schor's algorithm. So we know that the algorithm works. It's just that the technology, the hardware has to catch up. So we just have to be able to control the qubits. Once the hardware is there, there is no doubt that it it will work because the algorithm is already existed. So because of that, this is a huge problem for us, meaning this is a global issue because everybody uses that standard.

Vit Lyoshin (31:54.622)
Hmm, I see.

Vit Lyoshin (32:04.523)
Yeah, it's proven.

Shohini (32:12.896)
So now, for example, the US you know National Institutes of Standards and Technologies that does all of the testing and rollout of standards and certification, they've already announced that there are these new potential standards that we should be all moving to because of the quantum threat. So this is well understood and acknowledged. Will the new standards be, you know, f fully secure? We don't know because honestly, standards take a lot of testing, right? Maybe some very smart

Vit Lyoshin (32:13.057)
Mm-hmm.

Vit Lyoshin (32:30.593)
Mm-hmm.

Shohini (32:42.068)
I don't know, teenagers somewhere in the world will come and hack the new s new standards, who knows? So that's a huge problem. And so lots, I mean, governments all around the world are absolutely concerned. And, you know, the the current approach is to definitely think about moving at least to the new standards. Even if they are not in the future they might not be secure anymore.

Vit Lyoshin (32:49.397)
Yeah.

Shohini (33:07.436)
But for now, we already know that our current standard is not secure. So you should move to this other standard. And going even further, we want to create an encryption protocol that can never be hacked even if somebody has a quantum computer, right? That would be great. Turns out there is a way. The only way to block a quantum attack is by using a quantum encryption, actually. So there are actually existing known protocols.

Vit Lyoshin (33:13.641)
Mm-hmm.

Vit Lyoshin (33:24.301)
Yeah.

Vit Lyoshin (33:30.871)
You

Shohini (33:35.681)
That you use quantum to block quantum. But to actually build that new quantum encryption, again, it's going to be about changing all of our hardware and our networks and every single person, individual, company, anybody who's on a network would have to be part of that quantum encryption. Because even if one window is open in your house, you know, anybody can get in. Similarly with the quantum global internet.

Vit Lyoshin (33:39.201)
Hmm.

Vit Lyoshin (33:55.947)
Mm-hmm.

Vit Lyoshin (34:00.27)
Yeah.

Shohini (34:04.246)
If you have even one small vulnerability, it doesn't really work. So it's a huge problem and it'll take a while. But but there are definitely lots of people worried about it and working on it.

Vit Lyoshin (34:11.157)
Yeah. Yeah.

Vit Lyoshin (34:16.501)
Yeah, well, I'm glad they're working on it already because if somebody tomorrow announces that they built a computer, that's it. We all basically lose all our stuff. And that's gonna be disaster. Yeah.

Shohini (34:26.262)
Absolutely. It's a major, it's yeah, major, major issue. In fact, it's it's called Q Day, this this idea that, one day, one day this will happen. But for me, actually, I often think of in a way, Q Day is almost like we're thinking about it wrong because Q Day is not one day. Q Day is the day that we found out about Shore's algorithm that it's possible that this will happen in the future because

Vit Lyoshin (34:33.677)
Q day.

Shohini (34:52.596)
All of the data that we have today, if somebody just downloads it, even though they can't crack it now, right? They'll just download the encrypted file, let's say our, I don't know, our health records or I don't know, our you know, codes for launching weapons or whatever. If they just download it and wait when the quantum computer is built, then they run that computer and decrypt all the existing data. And so, in a way, all of that is already lost if somebody's collected the encrypted data.

Vit Lyoshin (35:06.945)
Mm-hmm.

Vit Lyoshin (35:15.18)
Mm-hmm.

Vit Lyoshin (35:20.883)
It's already... Yeah, we don't know if somebody's got it already or not. Yeah, that's a...

Shohini (35:23.742)
Exactly. So it's not in the future, Q Day. Q Day is happening every day that we are using our current standards, which is very scary, I know. But I feel like we should be more worried about our data and you know, really start mobilizing to move away from current encryption as soon as possible.

Vit Lyoshin (35:32.208)
Yeah.

Yeah.

Vit Lyoshin (35:42.325)
Yeah, yeah, people, nobody talks about this, but I think this, but this is like a breaking news or something because it's a,

Shohini (35:44.991)
Alright?

Shohini (35:49.717)
It's coming. It's definitely a problem and we need to really think about it. It's it's uncomfortable. To me, it's a lot like, you know, when we talk about climate and global warming, we all know it's coming and then we kind of ignore it. So this is the same way. Like we know this is coming, but we're not talking about it as much as we should.

Vit Lyoshin (36:03.255)
Yeah.

Vit Lyoshin (36:08.309)
Yeah, it's not yet popular enough, unfortunately. Yeah, okay. Well, I'm glad people working on it. Yeah, yeah, yeah. I also wanted to talk about like a sort of connection with AI and quantum computing. If anything is happening right now, like people saying if we're gonna train more AI, should we use quantum to train it faster, better?

Shohini (36:10.764)
Yes. So I'm I'm glad you're talking about it. Yes. You're doing your part.

Shohini (36:23.629)
Mm.

Vit Lyoshin (36:34.561)
or whatever, more efficient from energy standpoint, what's your take on it? What do you think is happening there?

Shohini (36:41.302)
Yeah, there's definitely work by many research teams around the world and also at man various companies like you know, all the big groups like Google and IBM and everybody is exploring this field called quantum machine learning, where on one hand, yeah, one approach is to try to think, well, can we create better, cleaner data sets using quantum and then use those better data sets, high quality data, to train AI.

Vit Lyoshin (37:04.215)
Mm-hmm

Shohini (37:10.104)
Right. So that's one thing that people are definitely looking into. And then there's the reverse might also help where AI is used, you know, machine learning to try to improve quantum algorithms. Right. Maybe, you know, and then this is something it's kind of like using AI to do some kind of scientific research, maybe find new algorithms, look at patterns and structures of you know quantum entanglement networks and things like this.

Vit Lyoshin (37:28.172)
Mm-hmm

Shohini (37:35.586)
So I think it works both ways where quantum can perhaps help enhance AI, but AI can help to enhance quantum too. So I think the future will be about developing both approaches together because they're really about improving computing. So why choose one or the other when you can do both? I think that's the the way people are starting to think about.

Vit Lyoshin (37:50.838)
Mm-hmm.

Vit Lyoshin (37:57.708)
Yeah, I see. And then there is also like, I found a term called quantum AI. Can you talk a little bit about that and like, is it? And maybe people misunderstand it or it doesn't like, what does it mean really?

Shohini (38:15.037)
Sorry, you found what I c it cut out a bit.

Vit Lyoshin (38:17.454)
Quantum AI?

Shohini (38:19.978)
Okay. So that is kind of what I was talking about where are you talking more about AI in the sense of L LMs, like language models, or is that what you're asking about?

Vit Lyoshin (38:29.325)
No, that's what I don't know because I found this term and I thought maybe it's something special about it or is it just like a short term of using quantum to help with AI training or finding better algorithms. So it's all the same thing.

Shohini (38:42.826)
Yeah, yeah, yeah. That's I'm thinking broadly. I don't think there's a very specific meaning to it right now. It's basically all all the various research and development of AI and machine learning, and then there's all the quantum and it's about how can we, you know, bridge that together. So quantum can power AI and machine learning, and AI and machine learning can power quantum as well. So yeah, that's broadly what it.

Vit Lyoshin (39:01.986)
Mm-hmm.

Vit Lyoshin (39:08.873)
Yeah, okay. So do you sense that both of these technologies kind of going to go and help each other in the future? Since now everything is, not everything, but many companies invest heavily with AI and hopefully those manufacturers of hardware and algorithms for quantum can use it. Do you think they will kind of work together with each other? Is that a possibility?

Shohini (39:35.085)
Yeah, so like for example, I think Nvidia already has a quantum team working in this area. So I'm assuming that they they certainly believe that it's not going to be AI AI or quantum. There's gonna be some way to sort of use both in some optimal fashion, but I think it'll depend on this particular problem you're trying to address or the architecture you need to build.

Vit Lyoshin (39:40.353)
Yeah.

Vit Lyoshin (39:53.58)
Mm-hmm.

Shohini (40:02.188)
the very very much specific to your sector, your problem, your resources, your constraints. And then you sort of put all that in and hopefully you find the ideal combination of quantum and AI that could help. Currently it's all AI because as I said, quantum is in very, very early stage. It's not at a point where it's really going to help out in any big way right now.

Vit Lyoshin (40:17.387)
Yeah.

Vit Lyoshin (40:21.846)
Yeah.

Vit Lyoshin (40:25.961)
Yeah, okay. So if we look in the future, since we're in the early stage right now with Quantum, what is like a next major milestone we're expecting with Quantum? Is it going to be like a hardware breakthrough or something on the software side?

Shohini (40:44.364)
That's actually a very good question. I wish I could give you all of these if if I had all these answers, we would be doing them all, right? That's what it means to be in early technology. If I knew exactly what to do next, somebody else would have done it. So the milestones that we do look for, obviously the first thing, and this happens often, you'll see Google will make an announcement saying, we've unlocked quantum supremacy, quantum advantage, right? So the way that these companies do these benchmarking is that they try to

Vit Lyoshin (40:50.625)
Yeah

Okay.

Shohini (41:12.492)
Take their existing quantum device, which they all have their prototypes, and then they run some hard problem on it. And it has to be a standard hard problem that the scientific community has said, yes, this is a hard problem for computer science in general. So if you can solve this problem, we can look at how fast you were able to do it compared to our existing supercomputers. And if you did it much better, then that's like a milestone. Say, you have that benchmark.

Vit Lyoshin (41:17.761)
Mm-hmm.

Shohini (41:40.429)
So there are these kinds of test problems that these companies have been running. And they've been able to announce some, you know, advantages where they run these. Basically these are made up almost like math problems kind of, that they are not actually useful, meaning they're not like specifically applied to, I don't know, as I said, curing cancer or a particular molecule. These are very, very sort of theoretical problems.

Vit Lyoshin (41:40.898)
Mm-hmm.

Vit Lyoshin (41:53.665)
Hmm.

Vit Lyoshin (42:01.937)
Mm-hmm

Shohini (42:05.686)
So then I would say a real milestone would be if somebody said, okay, here's an actual useful thing. Like I wanted to calculate the properties of such and such molecule, and I can't do it on any existing supercomputer, but look, I did it with a quantum computer. That would be like an useful applied implementation milestone. So I think that would be a big one. And that would be on the hardware side, because I think it's really the hardware that needs to catch up to be able to do that.

Vit Lyoshin (42:06.059)
Okay.

Vit Lyoshin (42:24.428)
Mm-hmm.

Shohini (42:33.954)
However, even on the software side, in principle, yeah, we know that let's say you can have Schore's algorithm. That would be a big milestone to be able to run Schor's algorithm on a on a large enough device that could break some real encryption. But I think that's further down the road. there in the meantime, we could take algorithms that exist today like Shores and see can we improve them? And so there's definitely software level kinds of approaches where we are where we might be able to.

Vit Lyoshin (42:34.367)
Okay.

Vit Lyoshin (42:47.788)
Mm-hmm.

Shohini (43:02.676)
squeeze more power just by optimizing the algorithms themselves and making tailoring them for the particular hardware architecture you're using. So there's a lot of that kind of work and those will be milestones. The other piece that I think for the on the hardware side is really, really going to be important is that as you put more and more qubits together to make larger and larger quantum computers, you run into this problem of errors. And honestly, even our current computers, you know, they they have overheating problems. I mean

Every machine has errors. There's no such thing as a perfect machine, right? So quantum computers also are not perfect. There are many errors, but errors in the quantum world are much worse because these machines are very fragile, right? Controlling individual quantum particles is very, very difficult. So there will definitely be errors, which means we have to correct the errors as we go on. So for the technol what that means is that the hardware itself has to be built in such a way that as you run your code,

Vit Lyoshin (43:32.032)
Yeah.

Mm-hmm.

Vit Lyoshin (43:52.557)
you

Shohini (43:59.405)
There will also be error correction happening. And that puts even more challenges on technology. So I think the next few milestones that I would like to see is, you know, essentially it looks it's very technical, meaning it's not something that perhaps seems very interesting, but from a technical side, I would like to see more advances in error correction in this in a way that is scalable and you know robust. Because

Vit Lyoshin (44:02.253)
Hmm.

Vit Lyoshin (44:25.1)
Yeah.

Shohini (44:25.962)
It doesn't matter if you put millions of qubits together, if they're all just going to be garbage in, garbage out. We don't care. So I want to see you know, those la even if it's just a hundred qubits with good error correction, that is a real milestone. I don't need the because then I know I can put these modules of hundred qubits together and eventually get to a million qubits and there won't be an error problem. So it's this modular development that I think are milestones we'll have to look for.

Vit Lyoshin (44:32.85)
Right? Yeah. Yeah.

Vit Lyoshin (44:42.967)
Hmm.

Vit Lyoshin (44:49.804)
Yeah.

Vit Lyoshin (44:54.561)
Yeah. So from what I understand, it's like getting our basics now on hardware and software and, and big companies who have resources to invest, they're kind of trying to run through certain algorithms to prove the concepts and make sure it all works correctly and it's efficient and so forth. and then once that's done, it's going to take us to the next level. This may be bigger problems or more problem problems that actually to everyday.

People matter, right? Not some theoretical, scientific tasks. Yeah, I think AI kind of started in the same way. They were playing chess and go, like, who cares, honestly, right? But they proved the concept, they proved that this technology is actually, can do this. And then now let's take it to the next level. Yeah, okay. I think history repeats itself every single time. Yeah, okay.

Shohini (45:25.484)
Yeah, exactly. That's right.

Shohini (45:32.29)
For sure.

Shohini (45:37.676)
I agree.

Shohini (45:42.932)
Yeah. Yeah.

Shohini (45:48.352)
Right? All the time. We just don't remember it that way.

Vit Lyoshin (45:53.632)
Yeah, right, we don't. Yeah, we forget about it. We move on to the new stuff. That's exciting. Personal question for you. What excites you the most about quantum computing? Maybe today, in the future or what not.

Shohini (45:57.398)
Yeah. Yeah.

Shohini (46:10.136)
So I'm going to answer this like a very nerdy theoretical physicist because that's what I am. I'm I'm a I'm a theory person. The reason I like quantum, and in fact, I started my graduate work, you know, when I s was looking at research and so on. When I started, there was not even a quantum computing research program, meaning it didn't really exist, right? It's it's as I said, it's a early stage kind of technology.

Vit Lyoshin (46:15.53)
You

Vit Lyoshin (46:31.629)
Hmm

Shohini (46:36.854)
But I love the idea the theory itself. Quantum theory, of course, has existed, as I said, for about a hundred years. And I wanted to, you know, learn this amazing theory because it explains everything in the universe or it describes everything in the universe. And I wanted to understand it better. So for me, it's more about fundamental science as an understanding the laws of nature and w how and why do particles behave in these weird quantum ways. So it turns out if we can build quantum computers, that process itself.

Vit Lyoshin (46:37.152)
Yeah.

Shohini (47:06.21)
Will is teaching us a lot about the structure of the quantum world itself. And we can actually use quantum computers to solve the equations of quantum science itself, perhaps, and understand things like the structure of space and time and how things interact and so on. So these are very foundational, you know, as I said, nerdy science questions that to me are very exciting. I don't expect that it'll be something interesting to everybody, but to me,

Vit Lyoshin (47:19.03)
Mmm.

Shohini (47:35.106)
Quantum computing is a way to really push our knowledge about the laws of nature itself. So that that's the most exciting part to me. It's like being an explorer, right? Going and essentially looking out at these new landscapes. They look very strange, full of superposition and entanglement, and trying to make sense of it and understand this new world.

Vit Lyoshin (47:42.349)
Yeah.

Vit Lyoshin (47:56.75)
Yeah, maybe it can do calculations on itself and tell us in like plain human language what's going on in the world. like if you look in space, basically every decade they come up with some breakthrough discoveries like what's black matter, dark matter and all that stuff and nobody knows what it is.

Shohini (48:17.077)
Exactly.

Vit Lyoshin (48:20.685)
I sometimes watch scientists from astrophysics and stuff and they're like, well, we don't know. We know it is, math shows that's what it is, but we don't know why. I'm like, how is it even possible? But yeah, it is.

Shohini (48:27.5)
Okay.

Shohini (48:31.392)
Yep. I know. Exactly. So for scientists like me, it's actually very exciting when we run into something we don't know because it means we have something to study more. So I hope quantum quantum computers and this whole field as it grows, it'll just throw up even more things that we don't know that we can try to explore more.

Vit Lyoshin (48:41.837)
Mmm.

Vit Lyoshin (48:46.913)
Yeah.

Vit Lyoshin (48:52.299)
Yeah, okay, interesting. So do you have any sort of advice for people maybe who study or in product in like founders of companies if they want to understand more the space? Do you have any sort of advice to them where to start, where to look for and things like that?

Shohini (48:54.264)
Yeah.

Shohini (49:14.24)
Yeah, so I think one way to approach it, I know it feels very sort of sci-fi and strange to most people who have who'd feel like they don't understand quantum. That's okay. I don't think everybody has to understand every part of superposition entanglement. But think about it as like a computing problem, meaning there's certain areas where quantum may help, right? So it's you in in solving some complicated computing. So think in your own sector, in your own company, are there computing bottlenecks?

Identify those, or maybe you need better, as I said, imaging. So are there sensing needs, computing needs, or security communications needs? These are the areas that quantum could help. So on your end, you just have to identify what you need. And then ask yourself: is there a quantum way to approach it? And of course, if you're not a quantum expert, it doesn't mean that you would solve the problem. You go and ask the experts. So start making connections in your local area or you know, do some

you know, assign somebody in your group or your team to start think looking around to see who are the experts in that field looking at those kinds of computing bottlenecks or so on in quantum and reach out to them, start, you know, having that conversation and see if there is an approach to, you know, addressing the problem. So if in that way you start with what you know and ask yourself what is your need, and then look for the expertise that can come and help you solve your need.

Vit Lyoshin (50:32.637)
Mm-hmm.

Shohini (50:41.26)
That way you don't become an expert. You know, it's like, you know, whenever let's say if I need some legal help, I don't go and become a lawyer myself. I go and hire a lawyer. But I need to first identify what's the problem I need to solve. So that would be my advice: that don't try to become a quantum expert, but ask yourself what are your computing needs, what are your security needs, cybersecurity needs, and what are your sensing needs. Maybe you work in, I don't know, ocean imaging or something, right?

Vit Lyoshin (50:53.119)
Yeah, yeah.

Vit Lyoshin (51:06.677)
Mm-hmm.

Shohini (51:10.658)
So that's the way to really look at this problem and then go from there.

Vit Lyoshin (51:10.688)
Yeah.

Vit Lyoshin (51:15.693)
Yeah, I think that's a good advice for product people, for companies, because sometimes I see them jumping into technology like a couple years ago, three years ago, whenever AI started, everybody said, oh, we need to build it. We don't know what it is, but let's just build it because we need to sell this and stuff like that. And many product people I see online and I meet in person and they sometimes get confused. Like my boss is asking me for this.

Shohini (51:32.771)
No.

Vit Lyoshin (51:45.6)
but I don't even know where I can plug it in. It's weird. Now people start to get more understanding and I guess same thing here. Like if you really have a problem that applies to quantum, then go for it. Otherwise you don't have to. Yeah. Okay.

Shohini (51:57.761)
Yeah. Exactly. Yeah. Yeah. Make a list of problems. That's always the first step. Do you actually have a problem that needs to be solved? Or maybe you you're already solving some problem or you're offering some service in computing or maybe creating, I don't know, doing analysis of I don't know, insurance services as an example. But maybe you want to do it better. Right? So it's not that you don't have a solution, have a solution. And you ask what is it possible to do this particular thing?

Vit Lyoshin (52:06.252)
Yeah.

Vit Lyoshin (52:19.221)
Mm-hmm. Yeah.

Shohini (52:27.626)
insurance analysis better. And then you're like, okay, now that I have a very concrete question. Here's the insurance analysis. Here's what I want to do better. Then go and talk to a quantum expert and say, do you know of ways to do this better? And step by step. Yeah.

Vit Lyoshin (52:30.285)
Yeah.

Vit Lyoshin (52:37.313)
Mm-hmm.

Vit Lyoshin (52:42.604)
Yeah.

Okay, great. Well, thank you very much for your time today. It's been a pleasure. A lot of interesting information. But at the end, I also have three questions, my three innovation questions for every guest. So I'm curious to know your answers. And the first question is, can you define innovation in a few words?

Shohini (52:59.736)
Okay.

Shohini (53:05.096)
that sounds easy, but not so easy. So again, I will answer it as a scientist. To me, my mo the most exciting innovations that I think of are when you take an take an existing question and you think of it in a new way, right? So you switch it completely. And then that unlocks new area or approaches to solve the problem.

Vit Lyoshin (53:09.323)
Hahaha

Shohini (53:32.088)
So to me that's what innovation is. Take existing questions and rethink your approach to them. So innovation is an i is an approach to me.

Vit Lyoshin (53:32.14)
Mm-hmm.

Vit Lyoshin (53:39.661)
Okay. Yeah, okay. That's great. Second one is which innovation throughout the human history you think changed the world the most?

Shohini (53:52.311)
Wow. I think a lot of people, and I've you know, heard this a lot before too. A lot of people would say something like, I don't know, the printing press, for example, or as a way to, you know, but for me, I think I'm gonna go with the radio because or or just radio waves and the development or understanding of things like what we call today we call it the electromagnetic spectrum.

Part of that is radio waves, microwaves, X-rays, they're all part of the spectrum. So I'll go with the radio for two reasons. One is obviously because it's it was our way, our first way of really, you know, expanding how who you can communicate with and how to spread information. Of course, before that we had books, but those were not like instant ways to.

Vit Lyoshin (54:24.258)
Yeah.

Vit Lyoshin (54:40.961)
Yeah.

Shohini (54:41.676)
communicate. So I for me that's why. And the other reason is very personal because the person who actually came up with the first demonstration of radio wave signals, people th think of Marconi as the person who created and made commercialized radio waves. That's true. But the first person was a scientist from India and from Bengal. I'm Bengali. And the scientist named Jagadesh Bose was the first who demonstrated these. And actually Marconi used those

Vit Lyoshin (55:03.956)
Okay.

Shohini (55:09.836)
techniques himself and that's when it became large scale. But this this scientist Bose was not interested in, you know, companies and commercialization, but he actually did the science. So for me, that's what makes it special.

Vit Lyoshin (55:11.765)
Mmm.

Vit Lyoshin (55:18.155)
Yeah.

Vit Lyoshin (55:22.989)
Okay, I understand. And the last question is which technology or software or tool that we use today we will be laughing at 10 years from now.

Shohini (55:24.769)
Hell.

Shohini (55:34.328)
Wow. I think we always get these kinds of things wrong when we try to predict. So I'll I won't say I in fact I know this will not be the case, but what I hope that we laugh at or try to leave behind going forward is, you know, things like all of our gas, gas use vehicles. I hope we all are laughing at using gas and we're all using really cool electric ve vehicles and you know, living in a world where we are much much.

better about our energy use. So exactly. Yeah. Yeah. That would be so nice. Yeah.

Vit Lyoshin (56:05.932)
Yeah, and quieter, right? Yeah. Yeah. Okay, great. All right, that was it. Thank you very much for your time. I hope we can stay in touch and talk more in the future about quantum on the next big milestone. Yeah. All right. Thank you.

Shohini (56:23.35)
For sure. That would be great. Great idea. Thank you so much.