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Greg Meyer

11 Podcast Episodes

Latest 1 May 2021 | Updated Daily

Weekly hand curated podcast episodes for learning

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Episode 327 - Biblical Sexuality (Revs. Jeremy Britt & Greg Meyer)

The Local Youth Worker Podcast

www.rym.org

54mins

19 Apr 2021

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PODCAST: Elevated with Jenna-Leigh Bilong - Greg Meyer

Radiokansel / Radio Pulpit

PODCAST: Elevated with Jenna-Leigh Bilong - Greg Meyer by Radiokansel / Radio Pulpit

19mins

16 Nov 2020

Similar People

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Why Aren't You Over This By Now? (32) Dr. Greg Meyer

Why Aren't You Over This By Now?

Dr. Kelly James and guest Dr. Greg Meyer, LPC, Associate Professor, discuss the personal and spiritual life of helpers.

58mins

1 Oct 2020

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Police off the Cuff After Hours # 10 LA County retired DA Steve Cooley and retired LAPD Captain Greg Meyer

Police Off The Cuff

Police off the Cuff After Hours with LA County District attorney Steve Cooley with retired LAPD captain and use of force expert Greg Meyer.  Steve Cooley was the LA County District attorney from 2000-2012. He has co-written two books Blue Lives Matter, and Blue Lives in Jeopardy. The books deal with the line of duty deaths of officers on the LAPD and in Blue Lives in Jeopardy the outright assassination of active law enforcement officers. Greg Meyer is an LAPD retired Captain and an expert in the use of force.  These two guests pull no punches when talking about the state of law enforcement today.--- Support this podcast: https://anchor.fm/otcpod1/support

1hr 18mins

17 Jul 2020

Most Popular

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Boston 2019 Breakdown- Greg Meyer and Ritz

Midday Treat with HOKA NAZ Elite

1983 Boston Marathon Champion Greg Meyer and one of the greatest American distance runners of all-time, Dathan Ritzenhein, join HOKA NAZ Elite's Scott Fauble and Coach Ben Rosario to talk about the 2019 Boston Marathon and a whole lot more.

35mins

7 May 2020

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Greg Meyer

The Graduates

Andrew Saintsing:Hi, you're tuned into 90.7 FM KALX Berkeley. I'm Andrew Saintsing. And this is The Graduates, the interview talk show where we speak to UC Berkeley graduate students about their work here on campus and around the world today, I'm joined by Greg Meyer from the Department of Physics.Greg Meyer:Hey, how's it going? It's great.Saintsing:How are you?Meyer:Terrific.Saintsing:Cool. It's so great to have you on the show.Meyer:Thanks. I'm happy to be here.Saintsing:So, we were talking about doing an interview and you were mentioning that you study quantum computing. That's right. And I have no idea what that means. And so I'd love to learn more about what that means.Meyer:Yeah, definitely. So, um, I think, yeah, a good place to start is maybe this idea that came all the way from like the mid 20th century from Alan Turing, um, who is like working on computing and that sort of thing in like the forties and fifties, the, the ideas that people thought for a long time, for most of the 20th century, that in short, like no matter how you build a computer, the problems that are hard for it will always be hard. So like, you can build like any of the computers you use, like your laptop, you could use your phone, you could use, like, turns out, you can build a computer out of like marbles, falling down a little track and stuff like that, which is pretty wild.Saintsing:What do mean, you could build a computer out of marbles?Meyer:Okay. Yeah. That's a pretty cool thing that I it's probably worth mentioning. Cause it's pretty wild. Um, so the idea is like what, what makes up a computer in some sense at like the lowest level is just that you can like give it some inputs and that it does some work on those and it gives you some outputs, right?Saintsing:So, like an Abacus is a computer.Meyer:But then there's this idea of what's called turn completeness, which means that any like algorithm that you could run on sort of a generic computer that, uh, a machine is Turing complete. If you could run that algorithm on that computer and you might have to like adjust it a little bit to actually work. So I think an Abacus is actually not Turing complete, cause there's no way to like sort of program it and then have it go by itself. Um, but it turns out that even like, this is kind of ridiculous, but the game magic, the gathering, if you like set up the cards, right. Is turn complete. Like you can like get a program to run on it in some sense by just like playing the game. Um,Saintsing:But like you're, you're, you're doing the cards.Meyer:Yeah. You would have to move the cards around. That's true. That's true. But like everything that you would do would be preset. So with an Abacus, you can like move the different things around kind of however you want. But like if you set it up so that you like have to, there's only one choice in what you can do at each turn of the game, you could like get it to figure out something. And so the same thing with like marbles rolling down this thing, it turns out you can like set up a track for marbles to go down in a certain way that if you put the marbles in, in like a certain order, they will fall through in a way that like computes some function, which is really cool. SoSaintsing:Like know that the marbles always have this way.Meyer:Yeah, because you've like set it up that way. And that's kind of, I mean, how normal, like computers you would think of work too, is like you put electrical impulses in, in a certain way. And then you know, that there'll be by like going through lots of different switches and gates and stuff like that. And then you'll get some answer out at the other end. So this is pretty cool. So this is the idea of like there's many different ways in some sense of like building a computer or where computers, just like something that computes things. Um, and for a long time, so people found out that certain problems are hard to compute.Saintsing:Okay. What do you mean by hard?Meyer:Yeah. So that's, that's a good question. So you might generically think like so hard means in some sense, takes a long time or uses a lot of memory, which sounds like, kind of like find them build a better computer. That's faster. It has more memory, but sort of generically when we talk about things being harder, easy in theoretical computer science, uh, hard is like Harvard is easy as the comparison of like takes a minute to run versus takes like more than the length of the universe to run. So like the idea is like, it's not just like, Oh, it takes twice as long. It's like, it takes an absurdly long time to run. And the reason that that's important is this like, okay, you could wait 10 years and get a computer that's 10 times as fast, but like you're never gonna get a computer that's fast enough to run these calculations that would take like, you know, just this absurdly long time or use an absurd amount of space.Saintsing:So, it's like if we're, if we're on, we have our marble is on the track, there's like a problem that you just have to like super easy. You put it on the track and it finds a hole. And then that problem is solved. Versus if you had the track that just runs for like a mile all the way down the track before it. Yeah.Meyer:Yeah. That's right. And the crazy thing is, yeah, for these, you know, so-called hard problems. It wouldn't even be like a mile long, probably for the, sort of the hard versions of these problems. It would be like, you know, the track would be the width of the universe. Like it's something like that where it's just like totally infeasible to do it on earth. Um, so that's pretty wild.Saintsing:So, all computers, I guess, have different underlying mechanisms that they're operating on. Right. In some sense, they solve the problem and the same way.Meyer:And even if they solve the problem in a slightly different way, that's kind of the really cool thing about this conjecture is it's like saying it doesn't even matter if you try to solve it in a different way, using a different algorithm, whatever. It's just saying like, as long as you're using physics, what you are doing because you're in the world. Right. Um, it doesn't matter how you try to solve it. It will be hard regardless. I see. And as I said, this was kind of like a conjecture, but it seems to have held up. People have come up with all kinds of wild ways to try to like compute things. And it seems like these hard problems regardless are like always hard. So this was true until kind of the eighties or nineties. And then all of a sudden people started thinking about, okay, what if like the bits, the ones and zeros that we use inside computers, what if we let them be sort of quantum mechanical?Meyer:So we let them do the things that particles can do in quantum mechanics, which is like, you know, uh, you might've heard sort of the pop-sci of quantum mechanics. It's like a particle can be in two places at once, or it can be a particle and wave at the same time. So what we're going to let these bits do is just sort of like be in two different States at the same time. So normally a bit is a zero or a one. And we say, okay, what if it can be, what's called a superposition of zero and one it's kind of in zero and one at the same time, which is pretty wild.Saintsing:So, I know I hear the word bit all the time when we talk about computers, can you just explain it a little more?Meyer:Yeah, yeah, definitely. So, um, so, you know, from just like counting from kindergarten or whatever, um, that when you write down a number, it has various digits. Right. And they can go from zero through nine. Cool. So computers count instead of in base 10, which is the zero through nine numbers in base two. So that means that instead of the options being zero one, two, three, four, five, six, seven, eight, nine, the options are just zero or one. And then once you get to one, that's like the nine, because when you go to the next one, you have to add another digit and then you just keep counting zero one, zero one in the ones place. Okay. Right. Yeah. A bit is just, is just one of those digits. So it's just a zero or a one. So when you're say counting or doing whatever operation on a computer, those are the two options that you have for sort of a digit that you can hold in your computer.Saintsing:So you tell it to do some math and then it just like starts reeling off zero one, zero one zero one zero one. And then it gets you to the answer.Meyer:Exactly. Yeah. So you can think of computers kind of as just doing math in the normal way, which is, you know, just storing a bunch of numbers, adding, multiplying them together or whatever. It just happens. That the way that it stores the numbers is not by counting zero through nine it's by counting just from zero to one. And so yeah, when we say bits, that's just like, literally those zeros and ones that are stored in the computer,Saintsing:But then you're telling it that, okay, normally the computer knows there's a zero or a one here and now it's thinking it can be either zero or one at the same time.Meyer:Yeah, exactly. Which is wild. Just one bit doing that is like kind of interesting, but it turns out when you stick a lot of bits together, the sort of in some very vague sense, the, the power that you get out of that grows exponentially with the number of bits. So already, if you have like a hundred bits, the number of different sort of States that you could have a superposition of is like more than the number of atoms in the universe. So it's growing like super, super fast. And this kind of got people excited because they're like, wait, we had this other thing that was blowing up, like the number of atoms in the universe, which is how hard these problems are. Right. What if like we could actually somehow use these bits in a clever way. In the mid-nineties, this professor at MIT, Peter Shor published a paper that was pretty groundbreaking because it showed that there is actually a problem that on as far as we know so far is one of these really, really hard problems. That's totally infeasible on a regular computer. And he said, Hey, if someone managed to build a quantum computer that actually, you know, you can use in this really precise way and actually works, you could actually solve this problem, which is super wild. Yeah.Saintsing:Do you know what the, what is the problem?Meyer:Yeah, so I can tell you about it. It's actually, yeah. So it's pretty wild. So this problem, which is generally thought to be hard is called factoring. It's a pretty simple idea. So say I hand you a really big number and I promise you this number is the result of multiplying two prime numbers together. Okay. Um, but I don't give you any other information. My question to you is what are those two prime numbers that I, that I multiplied together? So for a small number, this is easy. I say like, here's the number 21, what prime numbers say multiply together? And you're like, okay, just think, you know, got to remember fourth grade or whatever for a moment like seven and three multiply together and get 21. But it turns out if I give you like a thousand digit long number, then that problem gets super, super hard. And there's actually no fast algorithm that we know on regular computers to do this. Yeah.Saintsing:You just have to keep multiplying numbers together until?Meyer:Yeah. You basically just try it until you find one. There's some clever ways of making it a little bit better than just like literally trying all the possibilities and hoping. Um, but still they're not fast. And this is actually really important to, because currently, uh, like when you pay with your credit card on the internet, you want that your credit card number to be hidden, right. As you send it across the internet and the way that you hide it is actually by hiding it in one of these problems. So you say, I know no one can read my credit card number because to do that, they would have to factor one of these really big numbers. And it's really cool that you can do that, that you can actually like hide it in that sort of a problem. But yeah. So for like,Saintsing:I guess what does it mean that you like hide it in that problem?Meyer:Yeah. So, so, so in sort of a really rough sense of what it means is that you come up with some kind of like digital lock. You could call it where the key is those two numbers that were multiplied together. But the only thing you send along with it is the big number. That is the result of that. So, you know, because you locked it with this digital lock that if someone managed to, to figure out the key, so they managed to, to actually like unlock this digital lock, they would have had to figure out the two factors of this really big number. But because you like fundamentally, no, that's a really hard problem. You say, okay, nobody's going to be able to break this digital lock. Right. And the details of how to actually like make a digital lock that uses those two numbers is a little complicated and takes a fair amount of math. But fortunately, you know, a lot of smart people have thought about that. So when you're entering your credit card into the internet, you don't have to do that yourself and your computer just handles it for you. The one that people use in particular for like, like if you ever see HTTPS next to a website on the web, the thing that's, that S means like secure. So the thing that's making that secure is actually exactly this problem of multiplying two numbers together, which is really cool.Saintsing:Is it, is it always, it's not the same number?Meyer:No, so, right. So that's really key. Actually. The nice thing about this problem is you can think of a really hard problem, but in which there's only like one instance of it, and then it's kind of useless if someone figures it out because yeah, yeah. Then like fine. Now everyone can read the thing that really nice thing about this is you can always pick two different numbers. And then you're the only one who knows those, but you still know that the problem is hard, right? So that's why it's really nice as it's really flexible. And you can kind of, it's super easy to come up with these numbers on your own, but it's still super hard for someone else to break it. Right? The reason that people kind of were like, Holy moly, about quantum computing is this algorithm that was published in 1994, said, Hey, if someone managed to build a quantum computer, they would be able to take these really huge numbers and find the factors out.Meyer:Which, I mean, if, if we didn't like fix our cryptography, that would be like devastating for the internet, which is pretty wild. But also I think aside from that practical concern, just as something fundamental about this question that we started talking about at the beginning, which is like hard problems are hard, no matter how you build a computer, because this is saying, this is a hard problem. And we've built a computer still using physics, um, that could maybe actually solve this problem. So you might have to change that, that original conjecture to say, um, hard problems are hard, as long as you're only using what we call classical physics, which is like not quantum physics, which is pretty wild. So once you add in quantum mechanics, you can start to solve these really hard problems.Saintsing:That way we would just have to come up with new security measures. Yeah.Meyer:Yeah. And that's something that a lot of people are working on right now, too, because even though no one has managed to build a quantum computer that works well enough to run this sort of like to solve this sort of problem, it seems like it's coming. And presumably it's a good idea to figure this out before someone actually builds one,Saintsing:You were saying that when I said that we w we shouldn't be expecting them in the near future, you were saying that maybe there would be?Meyer:Okay. So the factoring problem I was talking about solving that one is probably pretty far off. So I think the current record for, um, factoring using that algorithm that was published in 1994 on a quantum computer, the current record is factoring 21. So it managed to figure out that the factors are seven and three, which as I said earlier is probably pretty easy to figure out without using that algorithm.Saintsing:Wait, do you mean like, that's the hardest problem that can figure out?Meyer:That's the hardest problem that someone has actually managed to build a machine to figure out using that algorithm.Saintsing:And so, I mean, you know, obviously I just know 21 because I memorized the times-tables like actually for a computer, if you had no knowledge of the factors in 21, that is like a really hard problem.Meyer:So it's not a hard problem because,Saintsing:Oh, cause you only have like so many numbers to check.Meyer:Yeah. So you can literally just check all the numbers below 21 and be like, okay, that was easy for you. It's these things. So the reason that it starts to get hard is you just start making these numbers a lot bigger. And then the numbers, the number of numbers that you have to check just blows up. And then at some point there are so many that it's just like totally unreasonable to try to do it. So the factoring 21 thing, obviously wasn't meaningful in any practical sense, but the reason it is meaningful is it says, Hey, look, this algorithm does actually work. Even at this really small scale. And if we managed to build a quantum computer, that's big, rather than this really tiny one that, that they managed to build, then maybe it can actually solve the same problem on some really big numbers.Meyer:Right. Um, so it was kind of a proof of concept. Right. But so speaking of proofs of concept, a question that a lot of them people, a lot of people have been wondering is they're saying, okay, so it's pretty clear that it's hard to build a quantum computer that can factor numbers really well, but maybe there's some other problem out there that's still really hard for regular or classical computers as we call them. So it's still really hard for regular computers, but is easy for quantum computers. So maybe there's something that's a lot easier for quantum computers than factoring.Saintsing:Just to go back, the algorithm that solves the 21 factors that is something that a regular computer could not run. Right?Meyer:Yeah. It's sort of fundamentally couldn't run because it's not quantum. Right. I guess you could like quote unquote, simulate a quantum computer on your regular computer to get it to run.Saintsing:You would still be like relying on the underlying bits, like bits that have definitive states.Meyer:Yup. And if you try to simulate a really big quantum computer, your computer, won't be able to do it, obviously, because if you could just simulate a quantum computer, then quantum computers just wouldn't be very interesting.Saintsing:Okay. So you're looking at the hardest hard problems that regular computers can solve and how fast quantum computers can solve.Meyer:Yeah. So we're trying to find the like easiest problem for a quantum computer. That's still hard for a regular computer. Right, right. Because we want, we want just like a proof of concept. We want something that like, even there are quantum computers don't work very well right now. We just want to be able to show for some problem as contrived as it might be, look, the quantum computer was able to solve this and we couldn't do it on a classical computer. We just want that proof of concept. Right. No matter what the problem is. Okay. So it's not going to be like really practically, useful in any sense, but it works as like, um, just to prove that maybe quantum computers can really do something that classical computers can't because up until literally last year, you know, people would come up with this algorithm and said, if someone could build a working quantum computer, we would be able to break this problem.Meyer:But then a bunch of skeptics were like, well, maybe it's just fundamentally impossible to build a quantum computer that can do that. Like maybe there's something fundamental about how hard it is to control, you know, these electrons or atoms or whatever that actually makes it impossible to build a machine that can do that. Right. So what we'd like to do is, you know, build a machine that can solve some problem just to prove to people, Hey, look, it really is true that there are some problems that quantum computers can solve that regular computers. Can't right. Um, so in terms of doing this proof of concept, um, yeah. People are wondering, you know, what's the, what is the easiest thing we could do on this quantum computer that we can't do on a regular computer? And it turns out one good idea for that is just literally have it do like random operations. Like you just feed it some data and then it just does random stuff to it. Um, but the key is that it does random quantum stuff to it. So that a classical computer wouldn't be able to keep up because it would have to try to like simulate the quantum mechanics. And, and we know that classical computers aren't good at thatSaintsing:Doing like addition or something on a bunch of like, it's just like doing something.Meyer:Yeah. So like, if, if you were to run a random, a random thing on a computer, you might think that it picks like, yeah. Plus times minus divide and like, or any number of other operations and just like randomly picks them and just keeps applying them to the data over and over with like maybe you multiplied by some random number and then you divide by some random number and add things. And like you just keep doing random stuff. And you're going to do a similar thing on your quantum computer, except you're not just going to use plus minus divide multiply. You're going to do some like, you know, sneaky quantum things, which are kind of hard to describe in like a, in a generic way. But the point is that the quantum operations that you would use to, for example, that you would build an algorithm like this factoring algorithm out of, you're just going to pick random ones of those and just apply them randomly to this data.Meyer:Okay. Google, there's a group at Google that's that's, um, working on building a quantum computer and they actually just, a couple months ago, came out with a paper saying, Hey, we did this thing where we had our computer, just like our quantum computer just do random stuff. And we managed to do it big enough that, that it was so big that there's no classical computer that could actually manage to keep up with the, with the calculations, which is super cool. So this was like, sort of the first proof of concept saying, even though this is a super contrived kind of useless problem, which is like literally solving a random problem, um, what it does show is that there's something we did on a quantum computer that we couldn't do on a regular computer. And that's already a really cool thing. So it's showing that this, this, um, this idea of quantum computing actually like works in some weak sense, but still in a meaningful way, we're getting closer to what I'm actually sort of working on now believe it or not.Meyer:In particular, the one really hard part of this experiment that they did, where these are, they're running, these random things is, you know, the hard part about building a quantum computer is making it reliable. Like it's, it's, it's really hard to make sure that it's actually doing the things that you asked it to do. Um, because these electrons or atoms or whatever are really hard to control. So you want to check that after you've solved your problem, that the answer was actually right. The problem is the whole point of the, the random circuit problem, which is the one that we're talking about. The whole point of that is that it's really hard for a regular computer to solve. So then there's this question of like, wait, how do you actually check that it did the right thing. Right, right. So that's like sort of a fundamental issue with this and what they did is they just said, okay, we're going to pick an instance of the problem.Meyer:So we're going to pick a specific, random problem that is big enough that only like the biggest supercomputer in the world can actually get the answer. And then we're going to say our little machine, which fits in, you know, just like a room or, you know, it's just like the size of a refrigerator managed to solve this problem in a minute. And it took the biggest supercomputer in the world, like a week to solve it. And we're going to say, you know, therefore this thing is clearly faster. Like our quantum computer is clearly faster, but we can still check the answer. Cause we managed to actually get the answer on this huge supercomputer.Saintsing:Right I gotcha. So the limits of regular computing verse to see, so you can still get the right answer,Meyer:Right. So, so that, so that you can still check that the answer's right. Cool. There's kind of a cool question though, which is like, are there problems like that, that a quantum computer can solve, like in the near term, like in the next year or two that are actually hard for normal computers to solve, but easy for them to check. Okay. So yeah, just solving the problem and, and being handed the answer and checking the answer are not exactly, you know, not necessarily equal and how hard they are.Saintsing:Right. Just like the one that we started off with, you could multiply the numbers together really.Meyer:Right. Exactly. That's a, that's a really good example. So yeah, if someone hands you with the two numbers and say these two numbers multiply together to make the big number that you gave me, you can literally just check that you just multiply it and say, okay, yeah, you're right. They do multiply together to give that. But as we said earlier, running the algorithm to get, you know, those two factors is really hard. So we're wondering, is there some easier thing that does the same thing and so way back in 2008, which I guess wasn't way back in, like, I don't know, in the timescales people probably normally think about, but is way back in terms of like sort of scientific computing research time, right? Like a lot happens in 12 years or whatever it's been. So in 2008, people had this idea, which was, maybe we can do something like this, this sort of like random circuit, this do a bunch of random operations and have your, your quantum computer give an answer, but we're going to give those random things. They're not going to be totally random. We're going to give them a little bit of structure so that the answer that they give out is easy to check.Meyer:And they kind of came up with a way to do this. And they said, you know, we can't figure out any way to do this on a regular computer. It looks like other problems that are also really hard for regular computers. So we think this is actually a really good instance of, of a problem. That's really hard to solve on a regular computer, easy for a quantum computer to solve, but still, um, easy for a regular computer to check. Right. Right. Does that make sense? Yes. So that was kind of out there for a while. And actually just a couple months ago in December, I was thinking about these sorts of problems. And I came across that paper and I thought it was kind of interesting that they were able to sort of compare it to these other problems that are hard on a regular computer, but they weren't actually able to like prove definitively that it was actually hard.Meyer:So it was kind of this open question for, for the past decade or so of like, you know, is this problem actually hard? And I think that sort of their idea was, yeah, it probably is hard, but we just haven't figured out how to prove that yet. Um, and they had proved a bunch of sort of related things like that. Certain parts of it were hard, but it wasn't possible to sort of plug them all together and say, this entire thing is hard and there's no way for a regular computer to answer this thing. Right. Okay. And actually in December I published a paper that says, Hey, here's how you can actually solve that problem with a regular computer. Um, which I was pretty excited about. So it was saying, I mean, it's kind of a bummer because this seems like it would be a really convenient thing and it's sad that it doesn't work. There's actually a way to solve this problem on a regular computer. So it's not anymore a very good like test of quantum computing, um, which is a little sad, but it was also a really fun result to like, to be able to figure out a way that you can actually solve this problem.Saintsing:Yeah. Yeah. Cool. And so, yeah, kind of a, you made these people a little mad, huh?Meyer:No, I didn't actually. So I was actually really happy. They were very, I would say they were very good scientists in that they said very clearly in their paper, we are able to show that these things, that these various parts of the problem are hard, but we can't show that the whole thing is hard. We want people to try to figure out if it's actually hard. So they actually put online just an instance of this problem. They said, you know, like I was saying, you could hand someone a really big number. They put the equivalent of that online. Just like, here's what we would hand to the quantum computer. If you can figure out the answer, whether by using a quantum computer, not like if you managed to build a quantum computer and find the answer, or if you managed to do it somehow else, we'll give you $25. If you send us the answer, which is really cool.Meyer:Because they were kind of like trying to encourage people to think about it. So yeah. Situation. So like, like a couple months ago I sent them an email and I was like, Hey, uh, this should be the answer to your thing. Um, and they were actually super excited about it. They thought it was really cool that, um, that it had finally kind of gotten answered. So yeah, definitely. Yeah. You might imagine that that might be an instance of scientists being like, Aw, dang it. Someone like refuted our results, but they were actually really awesome about it. And they said they were like super excited that someone had made this advance, um, of, of figuring that out. So yeah, it was, it was really fun. So I made like half of my grad student salary for, for the year fine by solving this problem.Meyer:But yeah. So, so that was a really fun thing to work on. And sort of the, the questions that I'm thinking about next are sort of, you know, is there some sort of replacement, like, is there some way to change what they did to make it so you can actually prove that it's hard for a regular computer or is there just like some other kind of protocol that you can run that, that you can really actually like prove definitively would be hard so that there can't be any sort of like sneaky way to solve it, um, on a classical computer. So that's kinda what I'm thinking about now. Uh, which is pretty fun. I don't know. I enjoy.Saintsing:So, like your research, do you think it's a lot of fun, right?Meyer:Oh, definitely. Yeah. I think it's really cool.Saintsing:Have you always wanted to solve math problems in high school? Were you like they would give you a hard math problem? You'd be like, yes.Meyer:Yeah. So yeah, I kinda, um, so yeah, I've, I've kind of like always enjoyed math and that sort of thing. I think so part of where this has come from is like, I really like cryptography, which is, you know, the idea of like, how can you sort of like hide information sort of like we were saying earlier, like, you know, how can you keep credit card numbers safe on the internet and stuff like that. Um, and I think really interesting and super cool that you can use math for these like practical purposes. Like you can have a math proof that says, no, one's going to steal all my money, which I think is a super neat thing. And these questions of like what problems are hard and what problems are easy for computers are like super intimately tied to that. Because what you're looking for when you want to build these digital locks is, is a problem that's really hard for, for a computer to solve. Although it sounds like pretty abstract, like figuring out, you know, whether you can come up with problems that are hard for regular computers, easy for quantum Peters, or maybe also hard for quantum computers. And you can prove those sorts of things. That's actually like really relevant practically to like building a secure internet, which is really cool. And I think that's part of what motivates me to think about these sorts of things. It's just that like, um, there are some pretty important practical implications.Saintsing:How daunting did your field seem to you before you got into it?Meyer:Yeah. So that's a really good question. So I think maybe part of the reason that it didn't feel super daunting is cause I didn't originally intend to really think about these sorts of things or like, I guess not think about them, but to like to do it as research. So I'm in the physics PhD program, not in like the computer science PhD program. Um, and I came to Berkeley, like working on, not even really these problems, I was working on more questions of like, you know, if you throw a bunch of atoms in a box and they're all talking to each other, sort of like, what do they do? Like what collective behaviors come out of them? So pretty kind of different, but at a very like fundamental lever level related problems. Um, and I was just sort of thinking about like this cryptography stuff kind of for fun. And I, you know, took a few cryptography classes in the computer science department and like math classes just cause I kinda thought they were interesting, but then I started finding these papers that, you know, put these ideas of like quantum physics and cryptography together. And I just like, it just really got me excited. So, so I think, yeah, maybe the field wasn't too daunting just because I like didn't mean to work on it until recently.Saintsing:So you kind of like already had the background necessary or you know, you had the foundation in place and then once you started actually exploring this field, it didn't seem like it wasn't some, it wasn't something that was inaccessible to you.Meyer:Yeah, definitely. Yeah. It's not like, you know, freshman year of college. I was like, I am going to do this in six years. I was like a, certainly not that I, uh, yeah, I think I might've been like an, a mechanical engineer or something, but for some reason I just like really was scared of chemistry and you had to take chemistry to be a mechanical engineer. So I decided to do physics instead.Saintsing:So interesting. Yeah. Because I know like I, you know, I majored in chemistry and undergrad and all the chemistry majors were like, I, I don't want to take any more physics. Like when they, when you have to do physical chemistry, it's just like, I don't know, I guess, different,Meyer:Different people's brains, like just hook onto different things better, you know?Saintsing:So all of the stuff you talked about sounds like very complicated. Do you ever just get overwhelmed thinking about all of it?Meyer:Yeah. I mean, definitely. I like to take a lot of like breaks during the day. Um, and a lot of times I'll just like go on, walks around canvas and like think about whatever to try to like clear my head a little bit, but also something like to really, I really like to do in my spare time is bake bread and something I really like about it is that it's like kind of the polar opposite of like the research that I do. Like it's not very quantitative. I like to like, not even really pay attention to the recipe really. And just like, you know, get a feel for the dose, see if it needs like more flour just by, you know, how it feels and stuff like that.Meyer:Um, and it's just like super tactile, not very logical. And I think it's really nice to have something to do that like just uses a totally different part of your brain, you know? And uh, and then you also get really tasty bread at the end. Well, hopefully, maybe it tastes like trash, but you know, yeah. You might have a tasty snack at the end of it too, which is a nice, a nice bonus.Saintsing:Nice. You're either doing science or you're baking bread.Meyer:Obviously. I like to do other stuff too. I also really like to be outside. Um, so I really like to go hiking and also go like mountain biking and do stuff up in the mountains. I have a little dog that really loves to go on adventures along too. So, um, yeah, he's, he's really happy to go cruise around the mountains as well. Yeah. Yeah.Saintsing:It's just great to have anything to turn out your turn, your brain off for a while.Meyer:Yeah. Yeah. And even, even if your brain isn't turned off, even just like a different place to, to like sort of have your mind think about whatever, you know, sometimes that's where you actually figure stuff out is, is when you're, when you're not trying to think about it, which is nice.Saintsing:Right. Cool. Unfortunately, it looks like we're running out of time on the interview. Do you have anything you'd like to say before the end of the interview?Meyer:Yeah, definitely. I think that if you take one thing away from listening to this, I would hope that it's that quantum computers aren't magic. There's a lot of sort of hype in the news that says like, you know, quantum computers are gonna like, you know, be able to solve every, every problem we can't solve or they're going to be able to like, they're going to totally destroy the internet or like whatever. And like, there are a couple very specific problems that they're really good at, but like in 20 years you're not going to be sitting there typing on a quantum computer. At best, you might be connecting to one on the internet to solve really specific, probably scientific problems, quantum computers, aren't magic. If someone tries to tell you that they've built a quantum computer that can solve any problem in the world, you might want to be a little skeptical.Saintsing:Okay. It's like any of those things, right? Like they said, three D printing was going to completely change everything.Meyer:Yeah. It's like, yeah, it's useful for a couple of things.Saintsing:Okay. We'll tamp down our expectations sounds Meyer:And then you'll be really excited if it does do something crazy cool.Saintsing:Great. I've been speaking today with Greg Meyer, from the department of physics. Thank you so much for being on the show,Greg.Meyer:Thank you so much for having me. It's been awesome.Saintsing:Yeah. It's been great. Tune in, in two weeks for the next episode of The Graduates. See acast.com/privacy for privacy and opt-out information.

32mins

20 Apr 2020

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12. #EC19 Day 2 Recap - Interviews w/ Bryan Martin, 8x8 and Greg Meyer, iCruise

Communications. Transformed.

Day 2 at #EC19 we chatted with great guests about their experience at #EC19 and how communications have transformed their business. Guests included: Bryan Martin, Chairman of the Board and CTO at 8x8 Greg Meyer, VP of Revenue Management, iCruise / WMPH Vacations

28mins

20 Mar 2019

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Improving Healthcare Data Interoperability with Cerner's Greg Meyer

Pivotal Conversations

In this week's episode of Pivotal Conversations, Dormain and Jeff chat with Greg Meyer, a distinguished engineer at Cerner, a maker of healthcare software. Greg talks about a new specification he helped develop to achieve interoperability and easier data movement between healthcare systems. He also explains how the company is modernizing its development practices to increase the pace of innovation.

43mins

11 Dec 2018

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Improving Healthcare Data Interoperability with Cerner's Greg Meyer

Pivotal Podcasts

In this week's episode of Pivotal Conversations, Dormain and Jeff chat with Greg Meyer, a distinguished engineer at Cerner, a maker of healthcare software. Greg talks about a new specification he helped develop to achieve interoperability and easier data movement between healthcare systems. He also explains how the company is modernizing its development practices to increase the pace of innovation.

11 Dec 2018

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In the Lead Pack with Greg Meyer

The Boston Marathon Podcast

Winning the Boston Marathon had been a goal of Greg Meyer's for several years, and one day in 1983, it all came together and he broke the tape in 2:09:00. He sat down with Tom Grilk in March of 2018 to talk about that special day, his training leading up to it, and the state of the sport, both then in the 1970s and 1980s, and now. 

54mins

23 Apr 2018

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