Speaker 1: Brought to you by Toyota. Let's go places. Welcome to
Speaker 1: Forward Thinking. Hey there, everyone, and welcome to Forward Thinking,
Speaker 1: the podcast that look at the future and says I'm
Speaker 1: making a note here huge success. I'm Jonathan Stricklandon, I'm
Speaker 1: Lauren Bock Obama, and I'm Joe McCormick. And guys, you know,
Speaker 1: I have this problem. I was using my computer the
Speaker 1: other day to work on a non trivial math problem,
Speaker 1: and it gave me an estimated time of completing that
Speaker 1: particular task as four hundred and seventy eight years, and
Speaker 1: I've got plans that day. I'm actually washing my hair.
Speaker 1: So I was hoping that maybe we could talk about
Speaker 1: classical computers, how they process information, and maybe why you're
Speaker 1: still washing your hair and your cyborg body and years
Speaker 1: years his cyborg body has hair. Yeah, it actually it
Speaker 1: takes to wash only my body has hair. But yes,
Speaker 1: it's uh, it's you know, let's not I don't want
Speaker 1: to go too far into my personal details here, so
Speaker 1: we all understand classical computers are reading machine language, binary language,
Speaker 1: zeros and ones. Technically there's actually something electronic going on there,
Speaker 1: but we're specifically saying that you know, it interprets information
Speaker 1: in sequences of zeros and ones that represent other things. Yeah,
Speaker 1: any piece of software running on your computer is actually
Speaker 1: a really long, I'm generally really long sequence of on
Speaker 1: and off switches of ones and zeros, right, and it's
Speaker 1: following specific rules. Yeah, and so there are two options
Speaker 1: as to work with. It has on and off their
Speaker 1: own one or one and zero whatever. On and off
Speaker 1: would be one in zero um. And everything that it
Speaker 1: does has to be translated down to that level before
Speaker 1: the hardware can make use of it, right, because the
Speaker 1: hardware doesn't understand things like run Assassin's Creed four. It
Speaker 1: actually has to break it down into understands one zero
Speaker 1: one one. Right. But if you tell it that run
Speaker 1: equals one zero zero zero one one one, right, Yeah,
Speaker 1: if you establish what the rules are, then it can
Speaker 1: it can interpret it through multiple levels of translating from
Speaker 1: whatever language you're using into machine language that that binary system.
Speaker 1: So these sort of this sort of approach is really
Speaker 1: good for certain types of operations. For example, if you
Speaker 1: want something just really simple, like you want to multiply
Speaker 1: one number by another number, and you input then too
Speaker 1: the computer and it understands what the operation is understands
Speaker 1: how to multiply then, and by understand I mean it
Speaker 1: has the instructions to do so, not that it actually comprehends. Yeah,
Speaker 1: you can listen to our artificial intelligence episode and hear
Speaker 1: that whole argument again. But the the idea of being
Speaker 1: that it does that very well. It can do that
Speaker 1: operation quickly, you get it. You know, if you use
Speaker 1: a calculator, you're going to get that information very quickly.
Speaker 1: That's first computer, more quickly than a human being, certainly
Speaker 1: than most most human beings. Yes. Yeah, your classic computer
Speaker 1: is very good at math, and it's very good at
Speaker 1: doing lots and lots of math problems way faster than
Speaker 1: you can. But if it needs to do a whole
Speaker 1: series of those in order to get the one results
Speaker 1: you want, because the question you're asking is actually going
Speaker 1: to require many, many, many operations before you can get
Speaker 1: an answer, that's where the classical computers start to slow down.
Speaker 1: Even when we're talking about modern classical computers, which often
Speaker 1: have multi cores, right, you know, you'll hear about these
Speaker 1: multi core processors. They can break down certain types of
Speaker 1: problems into parallel chunks, and each core of the processor
Speaker 1: can work on a chunk of that problem, which cuts
Speaker 1: down on the amount of time it takes to solve
Speaker 1: the overall question that you've asked. But even then it's
Speaker 1: you know, you're talking like like maybe sixteen cores. That's
Speaker 1: still nothing if you're talking about a truly difficult problem.
Speaker 1: And that's that's traditionally where we run into a barrier
Speaker 1: with classical computers. There are certain types of non trivial
Speaker 1: problems that classical computers have trouble solving. And here's an
Speaker 1: example we've talked about before, the traveling salesman problem. You know,
Speaker 1: the idea that you've got a traveling salesman who needs
Speaker 1: to visit let's say ten cities, and your job is
Speaker 1: to try and find the most efficient route for that
Speaker 1: traveling salesman to go through to spend the least amount
Speaker 1: of energy on this trip. And there are a lot
Speaker 1: of different potential wants to choose from, you know, choosing
Speaker 1: city A first and then going to city D and
Speaker 1: then going back to CITYB, or going straight through, and
Speaker 1: really you don't know what the right answer is until
Speaker 1: you've compared all those options. And as you add cities
Speaker 1: to this this question, it becomes more and more difficult
Speaker 1: to answer, and a classical computer essentially what it has
Speaker 1: to do is go through and run every single possibility
Speaker 1: and then at the end of running all of them,
Speaker 1: compare all the results to other to come up with
Speaker 1: your answer, which can take a long time. So that
Speaker 1: means that we need to look at maybe an alternative
Speaker 1: to classical computing if we want to be able to
Speaker 1: solve those types of problems in a more efficient, faster manner.
Speaker 1: But how do we get more efficient than than a bit?
Speaker 1: I mean, on or off seems like a pretty pretty
Speaker 1: simplified What if you could be both on and off
Speaker 1: at the same time? That's crazy talk. It is crazy talk, Jonathan. Yes,
Speaker 1: I have never seen a light switch that was both
Speaker 1: off and on at the same time. No wonder you
Speaker 1: haven't seen it. If you had observed it, it it would
Speaker 1: either be off or on. Yeah, can't. You can't see
Speaker 1: it and see it that it's both off and on
Speaker 1: at the same time, then you've observed it. Well. The
Speaker 1: problem is because the light switch is actually a really
Speaker 1: huge thing. Yeah, it's a macro level thing. It's on
Speaker 1: our scales, um, so it's position tends to be pretty stable, right, Yeah,
Speaker 1: But if we're looking at things on say a quantum
Speaker 1: ski ill that's sub atomic, tiny world where things just
Speaker 1: don't make sense an electronic Yeah, we're talking like tiny
Speaker 1: little particles. They exhibit behaviors that if if that same
Speaker 1: behavior were to suddenly exhibit itself on the on the
Speaker 1: on the macro scale, on our scale, we would all
Speaker 1: just think that we had been sucked into some sort
Speaker 1: of David Lynch weird al. Yeah, would make sense. No,
Speaker 1: nothing would make sense, because the quantum world and the
Speaker 1: classical world are are very different in the way they behave. Well, yeah,
Speaker 1: our our intuitions are evolved to deal with you know,
Speaker 1: like trees and rocks and animals, nothings, superpositions and in
Speaker 1: further more, trees and rocks and animals that don't suddenly
Speaker 1: shift three miles to the right for no apparent reason. Okay,
Speaker 1: so what what are we talking about? How can something
Speaker 1: be in two positions at once? It is called superposition,
Speaker 1: And asking me how is the wrong way to go
Speaker 1: about a joe, because I certainly could not tell you
Speaker 1: how I can tell you what's going on here. So
Speaker 1: super position is a concept within the field of quantum engineering,
Speaker 1: quantum mechanics, where a sub atomic particle is able to
Speaker 1: coexist in multiple states at the same time. And they
Speaker 1: don't mean states like the United States. I'm talking about
Speaker 1: actual states of being. So, for example, with electron, we
Speaker 1: often talk about spin, Like let's say that it could
Speaker 1: either have a spin that's up or spin that's down,
Speaker 1: and that's going to determine its magnetic field as well. Right,
Speaker 1: the direction of its magnetic field is that will be
Speaker 1: determined by this electron spin. Now, on the quantum level, technically,
Speaker 1: an electron can be in superposition, meaning that can inhabit
Speaker 1: both an upspin and a downspin at the same time.
Speaker 1: It has a probability of being in either one or
Speaker 1: the other at any given moment, were you to observe
Speaker 1: that electron and therefore lock it into that one one
Speaker 1: state or the exactly, So, if you were to observe
Speaker 1: the electron, the electron would then suddenly in have but
Speaker 1: just one of those two states, and that would be
Speaker 1: determined by the probability of which state it was most
Speaker 1: likely to be in. Sometimes it's going to be in
Speaker 1: the less likely state. That's why they're probabilities. Right, it
Speaker 1: might be a chance that will be a spin down
Speaker 1: and a six chance of spin up and you observe
Speaker 1: it and it's spin down. That can still happen because
Speaker 1: as long as the probability exists, that's how things can
Speaker 1: sometimes shake out. Now, if you were to do that
Speaker 1: same sort of experiment over a really long run, then
Speaker 1: the probabilities would start to manifest themselves, assuming that everything
Speaker 1: else was identical, which would never happen. But anyway, superposition
Speaker 1: is that crazy idea that a sub atomic particle can
Speaker 1: exist in both of these states at the same time,
Speaker 1: at least until you observe them, at which point, once
Speaker 1: you observe them, you would say that the system decoheres.
Speaker 1: That's it's an idea where a quantum system is a
Speaker 1: very delicate thing and if you interfere with it in
Speaker 1: any way, if you try to interact with it in
Speaker 1: various ways, it will decohere and become a classical system
Speaker 1: where things behave more the way we would expect them
Speaker 1: to based upon our own experiences. In terms of thought experiments.
Speaker 1: This is kind of going back to if you've heard
Speaker 1: about it Stronger's cat, It's it's it's you know, poking
Speaker 1: the system and seeing, you know, trying to identify what
Speaker 1: a particle is doing is going to make the cat either. Yeah.
Speaker 1: So the basic Strodinger's cat thought experiment is that you've
Speaker 1: got a box with uh, some sort of castor in
Speaker 1: it that is going to that could release a poisonous
Speaker 1: gas anytime after thirty minutes have passed. So you've got
Speaker 1: a cat inside this box with the cast of poisonous gas,
Speaker 1: and you wait for thirty one minutes to pass. And
Speaker 1: at that at thirty one minutes, there's a fifty percent
Speaker 1: chance that the castors released the gas and a fifty
Speaker 1: percent chance that it hasn't, which means at that moment,
Speaker 1: before you open up the box and observe it technically
Speaker 1: from a quantum level, the cat is fifty percent alive
Speaker 1: and fifty dead. And then once you observe it it
Speaker 1: those those uh that quantum state deco here's and it
Speaker 1: forms a classical state. Right. Of course, the idea of
Speaker 1: Schrodinger's cat was first introduced a sort of like a
Speaker 1: reductio out of serdum. The idea was like, this is
Speaker 1: so ridiculous, exactly, yeah, but it turns out like works.
Speaker 1: Quantum physicists were like, well that's tough, you know, Yeah,
Speaker 1: on the On the macro scale, of course, it's ridiculous.
Speaker 1: You know, you would never say that the cat is
Speaker 1: both alive and dead at the same time. It's either
Speaker 1: one or the other. And because you open up the
Speaker 1: box doesn't change that at all. But on the quantum
Speaker 1: scale it certainly does matter. Okay, But so if if
Speaker 1: this is how does this relate to quantum computing? Are
Speaker 1: we giving the cat a bunch of buttons to push?
Speaker 1: The cats and quantum computing? Lauren, I don't know where
Speaker 1: you got your notes, but let's just without cats. I
Speaker 1: think is a really sad. I think computers are made
Speaker 1: entirely of cats. Internet is made of cats, not computers.
Speaker 1: Uh no, no, no, we're going to We're going to
Speaker 1: back off the cats and the Internet and the quantum
Speaker 1: computing for just a second. There's one other there's one
Speaker 1: other concept of quantum that we have to cover, which
Speaker 1: is entanglement. Yeah. This is the idea of where you
Speaker 1: have multiple sub atomic particles that are entangled in some
Speaker 1: quantum way. So remember when I was talking about the
Speaker 1: spin of the electron being either up or down. If
Speaker 1: you have two entangled electrons, those electrons are going to
Speaker 1: be kind of opposite but mirror images of one another,
Speaker 1: and that if you know the behavior of one, you
Speaker 1: know what the behavior of the other one was at
Speaker 1: that moment when you observed the first one. Knowing that
Speaker 1: from that moment forward, you can't really predict anything, but
Speaker 1: being that if if two electrons are entangled and one
Speaker 1: is spinning up, the other one would be spinning down.
Speaker 1: For that, for that particular set of features, that's not
Speaker 1: just limited to spin. There are other things we have
Speaker 1: to take into consideration, but that goes well beyond just
Speaker 1: the basic idea of entanglement. Entanglements very important with this
Speaker 1: when it gets to quantum computing, the concepts of superposition, entanglement,
Speaker 1: and coherence are all really really important. So you asked,
Speaker 1: you know about quantum computing. That's that's the where we're
Speaker 1: getting at. The idea of quantum computing is being able
Speaker 1: to harness these features of the quantum world in a
Speaker 1: way that can do compute computational work for us and UH.
Speaker 1: And the the base unit of that. You know, if
Speaker 1: you were to say the base unit of a computer
Speaker 1: is the bit, either a zero or a one. The
Speaker 1: base unit for a quantum computer is the cubit, which
Speaker 1: I had to be reminded, is not a little orange
Speaker 1: guy who bounces around the pyramid. Okay, so instead of
Speaker 1: a silicon microprocessors, say, you would have computational activities being
Speaker 1: done by something like a photon or an electron or
Speaker 1: preferably lots of them. We need at least two. But um,
Speaker 1: although I guess I know you need at least two.
Speaker 1: So what the cubits are? Uh? Interesting in that if
Speaker 1: a bit a bit can only be a zero or
Speaker 1: a one, it's one or the other. It gives you
Speaker 1: a single value. Yes, cubits are both zeros and ones
Speaker 1: at the same time superposition uh, and technically all values
Speaker 1: in between, although that's not really that important. So the
Speaker 1: interesting thing about cubits is that the the relationship between
Speaker 1: cubits and computing power is exponential. You take two to
Speaker 1: the power of however many number of cubits you have,
Speaker 1: and that is the equivalent of your quantum computer's power,
Speaker 1: meaning that with with you know, two um cubit's you
Speaker 1: have four potential values. There. Uh. You have to look
Speaker 1: at the things as like, uh, two zeros zero, one
Speaker 1: one zero or one one um and they're all the
Speaker 1: same things, and there are all of those at the
Speaker 1: same time, right, But if you were to add another
Speaker 1: cupid in there, then you're talking about two to the
Speaker 1: third power. So you're talking about eight pieces of information
Speaker 1: from three cubits, which is different from the way it
Speaker 1: would be if it were just bits. And as you
Speaker 1: add cubits it becomes exponentially more powerful. By definition, you're
Speaker 1: talking about actual exponent here the inn in that two
Speaker 1: to the nth power. So the interesting thing here is
Speaker 1: that all of these different cubits could uh and inhabit
Speaker 1: these two values of zero and one at the same time.
Speaker 1: If you have enough of them, then you could, in theory,
Speaker 1: run a very complex problem through a quantum computer and
Speaker 1: it could solve for all aspects of that problem simultaneously
Speaker 1: in parallel because it's essentially doing all of those calculations
Speaker 1: at once because all of the cubits are all possible values.
Speaker 1: So it's kind of uh great for very specific types
Speaker 1: of difficult problems. Okay, so this sounds like, though, um,
Speaker 1: it's not going to be a replacement for the kinds
Speaker 1: of computers we use now, not at all. Because while
Speaker 1: it's great for certain complex problems like the traveling salesman
Speaker 1: problem where it could solve for all of those different
Speaker 1: variations simultaneously. It's not necessarily going to be any faster,
Speaker 1: and in fact, might even be slower than a classical
Speaker 1: computer for your basic computing functions that that regular schmos
Speaker 1: like like myself, like like I do. If it's not
Speaker 1: gonna show YouTube super faster, you're not going to be
Speaker 1: able to run the latest video game even faster, like
Speaker 1: I love the idea of running a video game on
Speaker 1: a quantum computer and all possible outcomes of the video
Speaker 1: gameplayouts simultaneously, like I was both good and evil and
Speaker 1: everything in between. But that's that's not exactly what would happen. Okay,
Speaker 1: So you're saying that a machine like this might have
Speaker 1: really incredible powers in some kind of specialized way, very specialized,
Speaker 1: like cryptography breaking. If if we had a working quantum
Speaker 1: computer of sufficient power, cryptography as it exists now would
Speaker 1: be meaningless. And the reason for that is that basically
Speaker 1: the way cryptography tends to work is take two really
Speaker 1: large prime numbers, like really really large. We're talking digits
Speaker 1: that are hundreds of digits long, like it's it's an
Speaker 1: enormous number, and then you find another enormous prime number,
Speaker 1: and you multiply the two of them together and you
Speaker 1: get that product, and then your your encryption is based
Speaker 1: upon a party that's authorized having one of those two
Speaker 1: large prime numbers, and as long as it's one of
Speaker 1: the two right to correct numbers, they can get access
Speaker 1: to that uh, that particular information or site or whatever.
Speaker 1: I'm oversimplifying for the purpose of this podcast. Now, publicly,
Speaker 1: all you can see is the product. So you see
Speaker 1: this huge product. I mean, it's a no enormous number.
Speaker 1: I remember, it's the product of two big prime numbers.
Speaker 1: And if you don't have the information already, trying to
Speaker 1: figure out which two prime numbers made this even bigger
Speaker 1: number is really hard to do. In a way a
Speaker 1: classical computer would do it, is it would start by
Speaker 1: dividing by prime numbers and then run through all of
Speaker 1: the prime numbers that possibly could be. So, if you're talking,
Speaker 1: if you pick a large enough prime number, that alone
Speaker 1: is going to guarantee that any computer working on trying
Speaker 1: to force this cryptography, this brute force stile attack is
Speaker 1: going to take longer than it would be you know,
Speaker 1: feasible to run. So you would you know, most people
Speaker 1: would not ever bother to try, because to do so
Speaker 1: successfully would take forever. But if you had a quantum
Speaker 1: computer that could solve for all potential prime numbers at
Speaker 1: the same time, you could crack that roll relatively quickly.
Speaker 1: In fact, yeah, it could. It can make the most
Speaker 1: advanced encryption tools useless. It could also usher in a
Speaker 1: new era of quantum cryptography, which would be even more
Speaker 1: difficult to crack. But you know, it's it's one of
Speaker 1: those things already where that's just one application. Obviously, there
Speaker 1: are lots of other applications for quantum computing. Yeah, that
Speaker 1: was one of the early applications. Actually, in the in
Speaker 1: the early nineties, Peter Shore of Bell Labs developed a
Speaker 1: quantum algorithm that that was a method of of entangling
Speaker 1: cubits and using superposition to um to find prime factors
Speaker 1: of an integer. Although that's not to say that that
Speaker 1: we can run that on all of our fancy current
Speaker 1: quantum computers. It was really like a proof of concepts
Speaker 1: saying that once we are able to do this, it's
Speaker 1: going to change our world, and it's good to know
Speaker 1: about it now rather than three months after the world's
Speaker 1: fastest quantum computer is made, and then we all realize
Speaker 1: all of our stuff is public. It's better to know
Speaker 1: it now, so we can say, huh, that's a problem.
Speaker 1: How do we fix this? So I mean, but yeah,
Speaker 1: it's a great example, and a lot of work has
Speaker 1: been done on quantum computers since just that that that
Speaker 1: algorithm was really for a hypothetical quantum computer. But now
Speaker 1: we've got people who have actually built at least preliminary
Speaker 1: quantum computers. Yeah, what's out there? I think I think
Speaker 1: the fanciest one that we've got was built in two
Speaker 1: thousand and seven. It's it's called the d Wave and
Speaker 1: it's a sixteen cubit quantum computer. I know they were
Speaker 1: working on one that would have been five and twenty
Speaker 1: eight cubits, which would have been phenomenal, and that that
Speaker 1: would have been unveiled within the last year or two,
Speaker 1: But I honestly don't know if they ever uh successfully
Speaker 1: demonstrated that one. But the fact that we've had people
Speaker 1: demonstrate this at all is pretty phenomenal because keep in mind,
Speaker 1: you have to be really careful with the way you
Speaker 1: operate one of these things, because just by observing it,
Speaker 1: by by trying to interpret the results you could cause decoherence,
Speaker 1: and then you end up with a very primitive classical
Speaker 1: computer that can't do much of anything, Like can you
Speaker 1: imagine going from a sixteen cubit computer to a sixteen
Speaker 1: bit computer? Would not be great? Right, And they've been
Speaker 1: working on these kinds of problems for UM since the
Speaker 1: since the sixties and seventies and eighties when all of
Speaker 1: this was sort of starting to come together, and it
Speaker 1: required a lot of work in UM and first of all,
Speaker 1: bringing reversible logic gates into the computing world, which which
Speaker 1: allows you if you have a one way gate, then
Speaker 1: you're going to experience a lot of data and therefore
Speaker 1: heat loss in your computer system. UM having a reversible
Speaker 1: gate lets you UM basically not burn out your processor
Speaker 1: every time you turn it on. Essentially, UM and and
Speaker 1: quantum electrodynamics, which is just starting to hum look at
Speaker 1: how electrons and photons interact with each other, so that
Speaker 1: we can start creating these little quantum pieces of of
Speaker 1: electrical information, right right, yeah, I mean, how do you
Speaker 1: harness this stuff? It's it's really tricky. Are you have
Speaker 1: to be able to create entangled particles? That's already kind
Speaker 1: of tricky there's certain minty materials that are being used
Speaker 1: right now in an experimental way that that are potentially
Speaker 1: a source of entangled photons. That's pretty exciting stuff. You
Speaker 1: have to figure out how to create a system that
Speaker 1: these can work in that is not going to allow
Speaker 1: it to go into decoherence. You have to figure out
Speaker 1: how to program for it so again that you can
Speaker 1: take advantage of it using it for the right sort
Speaker 1: of problems, and you have to figure out how to
Speaker 1: get the solution out of it again without disturbing the system,
Speaker 1: which is pretty tricky stuff. And even then, you're talking
Speaker 1: about probabilistic results, right, you mean you're getting results that
Speaker 1: are assigned certain probabilities of being correct versus incorrect. And
Speaker 1: sometimes the probabilities you get are so high that you
Speaker 1: might as well say it's a certainty. I mean, you
Speaker 1: can't really say that statistically speaking, there's always some room
Speaker 1: for uncertainty, but you know from human experience and be like, well,
Speaker 1: you know, times out of a hundred it's right, but
Speaker 1: there's still a chance that could be wrong and not
Speaker 1: all and of course some results may end up being
Speaker 1: like we're sure this is the right answer, So it's
Speaker 1: a it's a very uh specific, kind of niche oriented
Speaker 1: version of computing. It's not something you're not gonna go
Speaker 1: and get your uh your your your laptop. That's gonna
Speaker 1: have you know, the cotum version of the last model
Speaker 1: you owned, right, sure, and it is it is. Yeah,
Speaker 1: like you said, just slow going. I mean it wasn't
Speaker 1: until two thousand and one that there was a successful
Speaker 1: demonstration of shorts algorithm, and that was with a seven
Speaker 1: cubit computer that found the factors off. Yeah, they have
Speaker 1: factors of It's still it's still something. I mean, hey, no, no, no,
Speaker 1: I mean that's impressive. I mean I think that the
Speaker 1: very first one added one in one and everyone was
Speaker 1: so excited. I mean I mean understandably so. But nonetheless,
Speaker 1: and you know, and there's there's a few different ways
Speaker 1: that you can work on this coherence problem. I think
Speaker 1: that that is the largest issue that we're talking about. Um, yeah,
Speaker 1: that's that's I mean, none of these are trivial, but
Speaker 1: I would say that's the hardest or from what I understand,
Speaker 1: keeping in mind, I'm not a quantum physicist, right because
Speaker 1: I mean you can either I mean, you can like
Speaker 1: trap ions and super cool them until they're in a
Speaker 1: quantum state so that you can work with them, or
Speaker 1: um you can use liquid to to kind of wrangle
Speaker 1: cubits so that you can spread a single cube it
Speaker 1: across a few different molecules, which will decrease your your
Speaker 1: rate of coherence. Right, But all of this is you know,
Speaker 1: I mean, we're talking about very tricky particle physics. Yeah.
Speaker 1: And while we're talking about you know, kind of humble beginnings,
Speaker 1: keep in mind that other things that we depend upon
Speaker 1: today very heavily had very humble beginnings. For example, the Internet.
Speaker 1: You know, if you remember back when the Arpanet was
Speaker 1: first being put into into action, you know, that was
Speaker 1: a predecessor to the Internet. Some people call it kind
Speaker 1: of like the grandfather to the Internet, but it was
Speaker 1: it was a network of networks, was the idea, and
Speaker 1: it was this um. The one of the earliest messages sent,
Speaker 1: actually the first message set UH ended up crashing midway
Speaker 1: through the message. It was a one word message. So
Speaker 1: you know, you've got, you know, something where you point
Speaker 1: to that and like look at that. If we had
Speaker 1: just assumed that everything that followed that that failure was
Speaker 1: also going to be a failure, we would not have
Speaker 1: the Internet right now. So while we talk about these
Speaker 1: kind of tiny exam balls, you know, when you're thinking
Speaker 1: about proving a concept to be viable, that's huge, right,
Speaker 1: even if it seems relatively tiny and you're talking about, oh,
Speaker 1: you found the factors of fifteen. Wow, that's something that
Speaker 1: I learned in third grade. But you know, for something
Speaker 1: that until that point was hypothetical, that's amazing. So yeah,
Speaker 1: I mean, these quantum computers have a lot of interesting potential,
Speaker 1: not just in decryption or even the traveling salesman problem. Joe,
Speaker 1: you had, you saw something, right, Yeah, they might be
Speaker 1: able to help us actually study some things in the
Speaker 1: real world that are really difficult to study with the
Speaker 1: computers we have today, or might be really expensive, say
Speaker 1: to simulate physically. I've got a press release from last
Speaker 1: year from the n I s T Information Technology Lab UM,
Speaker 1: and what this talks about is that quantum computers might
Speaker 1: be able to simulate particle collisions. So the kind of
Speaker 1: work that we have to do now with like the
Speaker 1: particle accelerator, like the large Hadron collider and something it's
Speaker 1: miles across and die amateur, Yeah, it could could actually
Speaker 1: be simulated just in software. And of course, like with
Speaker 1: a regular computer, it's really hard to do this because
Speaker 1: digital you know, the computers we have today can't determine
Speaker 1: all these quantum states. There's just like too much information
Speaker 1: to keep track of um. But this press release talks
Speaker 1: about a team that came up with an algorithm that
Speaker 1: could basically run on any quantum computer, regardless of what
Speaker 1: it's quantum hardware was um, and it would simulate all
Speaker 1: of the different ways that two different types of particles
Speaker 1: could collide and interact. Interesting. Yeah, see, this is kind
Speaker 1: of fascinating stuff. The idea that we can uh add
Speaker 1: in all these known factors that we are aware of
Speaker 1: and create a simulation that could potentially create stuff we
Speaker 1: aren't aware of. It's kind of to me, that's that
Speaker 1: that's almost like magic at that at that stage where
Speaker 1: you're like, all right, I know what this does, and
Speaker 1: I know what this does, I don't know necessarily all
Speaker 1: the things that can happen when the two collide, and
Speaker 1: you create a simulation that can actually show you that.
Speaker 1: To me, it boggles my mind. You know, it's just
Speaker 1: such a phenomenal thing. And yeah, again, the quantum computer
Speaker 1: would be a use in that situation, but not so
Speaker 1: much if you want to play mind Sweeper. Well though,
Speaker 1: we're not saying necessarily that a quantum computer could never
Speaker 1: run a game or a video player or something like that.
Speaker 1: We're just saying like, there's really no reason you'd need
Speaker 1: one when a classical computer can do the same thing
Speaker 1: for a long time. Because, I mean, while while your
Speaker 1: power of your quantum computer does, uh does expand exponentially
Speaker 1: with the number of cubits you add, you still would
Speaker 1: have to add a lot for it to really uh
Speaker 1: for for classical applications, for it to be better than
Speaker 1: a classical computer. Now quantum applications, it would just leave
Speaker 1: everyone else in the Yeah, but you would you would
Speaker 1: need you know, a whole gallon of quantum, right, Yeah,
Speaker 1: you gotta get that. Gotta go over to the quantum
Speaker 1: refueling station and fill up your quantum tank and bring
Speaker 1: it back just to just to play like like Super
Speaker 1: Mario Brothers. Oh yeah, I don't know about you, guys,
Speaker 1: but I'm ready to go and play some video games.
Speaker 1: So I'm gonna wrap this up. Guys. If you enjoy
Speaker 1: our show, please go check f w thinking dot com.
Speaker 1: That's our home web page where We've got all the
Speaker 1: blog posts and videos and podcasts, cool stuff that you
Speaker 1: don't want to miss. Go check that out. I remember
Speaker 1: you can interact with us on Google Plus, Facebook, and Twitter.
Speaker 1: Just look for f W thinking that's us. We're happy
Speaker 1: to talk to you, and we will talk to you
Speaker 1: again really soon. For more on this topic in the
Speaker 1: future of technology, visit forward Thinking dot Com, brought to
Speaker 1: you by Toyota Let's Go Places