Welcome back to Impact Quantum, the show where curiosity meets the cutting edge of quantum computing—and you don’t need a PhD to keep up. In this episode, our hosts Candace Gillhoolley, Frank La Vigne, and BAILeY are joined by Michael Magid, a doctoral candidate at Binghamton University, whose research sits at the crossroads of system science, quantum artificial intelligence, and quantum information theory.
Together, they travel from the suburbs of Westchester County to the coldest corners of quantum labs, exploring the reality of what qubits can (and can’t) do, the biggest misconceptions surrounding quantum computing, and how global collaboration—and COVID-19—shaped the quantum landscape. Michael breaks down the complexity of quantum for both newcomers and advanced listeners, sharing insights on education, AI-powered learning tools, and how to get started in this rapidly evolving field.
Tune in as we demystify quantum jargon, discuss how quantum might revolutionize medicine, and examine the ethical and practical challenges ahead. Whether you’re quantum-curious or already knee-deep in the field, you’ll find inspiration and tangible advice for contributing to the quantum future, all while learning why, when it comes to qubits, it’s normal to leave with more questions than answers.
Timestamps
00:00 Quantum AI Systems Science
05:20 Understanding Quantum: A Beginner’s Journey
09:42 ChatGPT: Tool with Limitations
13:28 Quantum’s Potential to Solve Problems
15:50 “Quantum Solutions for Efficiency”
18:08 “Shor’s Algorithm and Quantum Impact”
21:01 Quantum Computing Delays Explained
26:33 IBM and Moderna in Quantum Healthcare
29:47 Undisclosed Tech Innovations Impact Discussion
30:40 Leading Quantum Research Companies
36:43 Exploring Quantum Innovation Opportunities
37:48 Focus, Adapt, and Optimize Skills
41:09 Exploring Quantum Solutions in Logistics
45:46 Quantum Cryptography: The New Frontier
48:17 “Quantum Musings with Michael Magid”
Transcript
In this episode of Impact Quantum, we chat with Michael
Speaker:Magid, a doctoral candidate at Binghamton University
Speaker:who's knee deep in the wild world of quantum AI. From
Speaker:Norwalk to near zero temperatures, we cover everything
Speaker:from how quantum computing could revolutionize medicine to why you
Speaker:probably still don't understand what a qubit does. And
Speaker:that's okay. If you've ever wondered what system science
Speaker:is or thought quantum curious sounded like a
Speaker:personality trait, this one's for you.
Speaker:It's not just Scrodinger's cat that's confused.
Speaker:Hello, and welcome back to Impact Quantum, the podcast where we explore the
Speaker:emergent field and ecosystem of quantum computing.
Speaker:And you don't need to be a PhD to play along. We believe
Speaker:very much that all you have to do is bring some curiosity with you and
Speaker:maybe a math textbook or two. With me is one of the most
Speaker:quantum curious people I know, Candace Kahooly. How's it going, Candace? It's
Speaker:great. Thank you so much. I'm very excited because today we're
Speaker:talking to someone. We just went down a little memory lane back to where
Speaker:we both grew up, and we basically were neighbors. It was very, very
Speaker:exciting. A little bit of Westchester county love for those. That's right.
Speaker:Which is funny because IBM, if memory serves, is headquartered in
Speaker:Westchester county, and I think they're super awesome.
Speaker:Quantum lab that I'm trying to get a tour of is up there.
Speaker:I went to university just south of Westchester county
Speaker:in a wonderful part of the world called the Bronx. And
Speaker:the boogie down. The boogie down and. Yeah,
Speaker:so I'm somewhat familiar with Westchester County. Well, who are we
Speaker:speaking to? We know where he's from, but we know who it is. Right. So
Speaker:today we're talking to Michael Majid. He is a doctoral
Speaker:candidate at Binghamton University, and we're very
Speaker:excited to speak with him today. Hi, Michael. Hi,
Speaker:Candice. Hi, Frank. It's a pleasure to be on this program. Thank you both for
Speaker:inviting me and thank you again for this opportunity. Awesome.
Speaker:And what is your PhD in? So my PhD is in the
Speaker:field known as system science. And within that field, we're able to
Speaker:do a significant amount of work in different data science related
Speaker:fields. System science, in the end, is just the science of systems,
Speaker:which is a bit of a weird way to
Speaker:explain it. But if we're going to be talking about any
Speaker:in parts that are interrelated, that can be
Speaker:itself a system. So what we do is we take a look how all these
Speaker:parts are interrelated and find how
Speaker:they're interrelated and why they're interrelated. My specific work is in
Speaker:quantum artificial intelligence as well as quantum information
Speaker:inspecting how different quantum networks, as well as how
Speaker:we can use system science techniques and data science techniques
Speaker:for developing quantum algorithms.
Speaker:That was described so beautifully. I just.
Speaker:Bravo. Like, I. When you.
Speaker:In this world, in this world, like, you know, in the quantum
Speaker:world there, it's really, really hard to,
Speaker:to, you know, make these positions that people
Speaker:have understandable to people who are outside of the field. But just
Speaker:listening to how you were describing it, I was. I was with you
Speaker:all the way. And that was. That was fantastic. I appreciate
Speaker:it. Could you do me a favor and hold those thoughts and give them to
Speaker:my professor so he also knows that I can do it?
Speaker:Well, I think that's important. Right. There's a lot of people who are in the
Speaker:quote unquote, hard sciences or even the soft sciences. Right. They just
Speaker:can't explain it to like the layman. Right?
Speaker:Yeah, it's. Yeah, go ahead. I didn't mean to cut you off. Oh, no,
Speaker:no worries at all. It's the difficulty of
Speaker:zoom interviews is this the
Speaker:teaching itself? And understanding how to connect with people
Speaker:in itself is a skill. And I'm very lucky to have the
Speaker:advisors and professors that I have because they are
Speaker:the best teachers I've ever had. They have
Speaker:shown me not only what it means to teach, but also to love
Speaker:teaching and to help people understand which is the core of what teaching
Speaker:should be. It's not just, here's a textbook, let me throw some stuff at you.
Speaker:The idea is, why should you know this? How is this related
Speaker:to what you know in general? How can we help you understand this a little
Speaker:bit better rather than trying to figure out what is the best way for me
Speaker:to disseminate this information quickly?
Speaker:Interesting. Such a spokesman for it too. Like, I
Speaker:could see how you could really communicate with,
Speaker:you know, college kids and to really kind
Speaker:of explain to them, you know, why, you know,
Speaker:what you're doing is exciting and, you know,
Speaker:actually. And to that point, like, what would you want to kind
Speaker:of advice would you want to give if, you know, these kids want to
Speaker:get involved in the quantum ecosystem?
Speaker:So for, let's go with both kids and basically anyone who wants to go into
Speaker:the system, not having that much background into it. So
Speaker:I started this coming from a biomedical engineering perspective.
Speaker:My previous master's was in biomedical engineering, so I already
Speaker:had a science background. I already had some quantum understanding because of the
Speaker:chemistry classes as well as the chemistry that I would do
Speaker:Part of my degree and part of the jobs I had as a biomedical engineer,
Speaker:the main thing to understand with
Speaker:quantum is that the best way to explain it is a.
Speaker:Prof. There's a. I believe there's a viral video of a professor who's teaching
Speaker:quantum and he basically said,
Speaker:right now I don't know anything about
Speaker:quantum. And by the end of this course, none of you will know anything about
Speaker:quantum. Which is a
Speaker:beautiful way to put it because quantum in itself is a
Speaker:different mindset of trying to understand how this stuff works.
Speaker:What I'm saying is that if you don't, if you feel like you don't understand
Speaker:it, you are learning. If you feel like you understand it, you are
Speaker:ignoring something. And this is a good idea with a lot
Speaker:of higher level math concepts that I found. And I'm
Speaker:saying this not as someone's like, oh, I know this stuff. No, I don't know
Speaker:this stuff. I went through the struggle, so learn from my mistakes.
Speaker:This. There's a lot of high level stuff that is
Speaker:in quantum and data science and all this. It takes a long time to learn
Speaker:and it takes a long time to truly understand it. Never be afraid to ask
Speaker:questions, reach out to people, reach out to professors, reach out to me.
Speaker:If people don't respond, people are busy.
Speaker:Sometimes the second message would be good if people
Speaker:don't respond, maybe just because they
Speaker:are too busy with everything else. The. But my
Speaker:point in saying this, professors love to. To teach.
Speaker:Professors in this field love to share their knowledge about this. They may not be
Speaker:good at sharing knowledge and it's going to be something that
Speaker:you want to be patient with them. Not every professor knows exactly how to
Speaker:teach you. So you need to help them on what your
Speaker:learning style is and how to. And do your own work on how to
Speaker:ask them the appropriate questions, which is more of a general question for anyone
Speaker:going into academia and interacting with academia. I
Speaker:digress. There's so much in the quantum space
Speaker:that allows you to start from nothing. There's books
Speaker:on it, there's textbooks. The one that really worked for me because I came from
Speaker:an information theory background was Mark Wilde's book
Speaker:on From Classical to Quantum Shannon Theory. But again, I came
Speaker:from an information theory background because of my data science background and that really helped
Speaker:me. A lot of other books that there's several professors at
Speaker:Cornell and Yale who have really good introductory textbooks to quantum
Speaker:mechanics and those are helpful. I spoke to one
Speaker:of them about it, saying that it's written. Some of them are written to the
Speaker:point that Anyone who hasn't had any
Speaker:chemistry or any quantum physics or any physics background
Speaker:can start from the ground and go. There's always resources to go.
Speaker:As long as you keep asking questions. As long as you keep being quantum curious.
Speaker:I couldn't have said it better. Well, we could have said it better ourselves. That's
Speaker:awesome. We definitely will talk to your professors because
Speaker:there's our new tagline, Candace and I'm glad you mentioned
Speaker:asking questions. Right. And
Speaker:it's definitely a field where I don't think anyone
Speaker:really knows exactly. Like is it Richard Feynman had said the famous
Speaker:quote, like, if you think you understand quantum computing or quantum physics, you don't understand
Speaker:quantum physics. Physics. Right. Like, and he was a pretty smart
Speaker:guy. Right. Like he was among, I think he was
Speaker:on the Manhattan Project at one point like as kid or whatever or pretty early
Speaker:in his career. But
Speaker:I also see you've done a lot of AI
Speaker:and LLM type research. Do you think that
Speaker:LLMs could help people learn this sort of thing? Like
Speaker:I use a lot of AI based learning tools myself. Right. So Notebook
Speaker:LM probably the most obvious one. Right. Do you think that
Speaker:you think those are good tools to help people learn?
Speaker:Yes, but you need to remember it's not a professor, it is a tool.
Speaker:Tools have limitations, tools can break and tools don't get the
Speaker:job done exactly as you want it unless you design it to be. So
Speaker:when you let's go with the ChatGPT, because we all
Speaker:know ChatGPT, we will have some information about that. You ask ChatGPT a
Speaker:question about quantum computing in general, because of the generality of the question,
Speaker:it's going to give you a. It can may not give you the exact response
Speaker:that you're looking for. And as you're continuing to ask questions, it's going to get
Speaker:more and more towards what you're thinking. But if you don't know which questions to
Speaker:ask, it may go into the wrong direction and give you the wrong information. It
Speaker:may also be starting to make up information and going into a logical in
Speaker:and of itself. Because at the end of the day,
Speaker:are you guys familiar with what an NLP is?
Speaker:So what I like to say is an LLM is three NLP in a trench
Speaker:coat. It's still just a processor. It's still just trying to understand
Speaker:language. And if you're giving it the wrong language and the wrong concepts and you
Speaker:don't know how to communicate scientifically to an LLM,
Speaker:it's going to give you maybe not wrong responses but more
Speaker:improper responses and trying to understand which ones are proper
Speaker:and which ones are improper. It can be the difference between understanding a
Speaker:concept and not understanding the concept and then disseminate.
Speaker:And if you're going to be talking with other people about it, you could be
Speaker:disseminating that information incorrectly as well.
Speaker:Yeah, I often wonder about that. Like how do you know?
Speaker:How do you know if the LLM is hallucinating? Because LLMs
Speaker:are really good at
Speaker:being very convincing of when it's wrong. Yeah.
Speaker:The good news is a lot of LLMs now have web access and even
Speaker:on the base level. So you can ask it to provide a source, go back
Speaker:to the source and then go and double check to make sure that source first,
Speaker:first of all exists. If it doesn't exist, well, some of the information
Speaker:may be wrong. And then if you find a source and it
Speaker:has that same information and agrees with that information, which is the important part,
Speaker:because even if you can read an entire paper and
Speaker:at the very end of the paper they said these results are not statistically significant.
Speaker:And if you just miss that one bit and the people didn't write the paper.
Speaker:Exactly, the LLM and everyone else is going to miss that part.
Speaker:So what I would recommend first before
Speaker:trying to educate yourself on any scientific topic through LLMs,
Speaker:is to have a education on both
Speaker:prompt engineering as well as a basic understanding of
Speaker:scientific literature and scientific reading. Because
Speaker:that's what happens a lot is the misrepresentation of it. And it's not,
Speaker:it's not always malicious. And when I hazard to say
Speaker:misrepresentation because it comes off as malicious thing, it's mainly just people
Speaker:misread something because they're not familiar with statistics,
Speaker:significance, they're not familiar with the statistical tests. Maybe the way that
Speaker:some people did a certain paper was to prove one point and then somebody took
Speaker:point B from that. All of that has to do with
Speaker:backing in scientific and quantum literature. And that
Speaker:again, that teams takes time. Don't make my main point
Speaker:with all of this. Don't be in a rush. Quantum is new,
Speaker:Quantum is growing. And there is a lot of things that we need
Speaker:to get underway, a lot of things that we need
Speaker:to keep building as I'm sure we're going to continue to discuss.
Speaker:Right? No, absolutely. I know Candace has a bunch of questions.
Speaker:Well, yes. So what is, do you think is the biggest
Speaker:misconception that people have about quantum
Speaker:computing and what it's going to. Do for
Speaker:all of us that quantum can solve
Speaker:everything? Quantum is
Speaker:going to do Three specific things. It's
Speaker:going to solve problems that we weren't able to solve before. These are known as
Speaker:either NP hard or variations of
Speaker:something hard problems that are computationally difficult for us to solve
Speaker:right now because we have the math for it, but
Speaker:it's just going to take so long for the math to happen that
Speaker:we can't do it on the classical computer. There's some
Speaker:problems, it's what's known as non polynomial time.
Speaker:It's not necessarily that we don't have an answer for this. It's that
Speaker:the answer in itself is going to take so long to solve because there's so
Speaker:many ways that we can do it. Excuse me, that's not the way
Speaker:to say it. It's going to take so long to solve that in the way
Speaker:that we have right now, that
Speaker:quantum itself, because it's able to go through all the states
Speaker:simultaneously, as well as entanglement principles and so on and so
Speaker:forth, that quantum speed up is going
Speaker:to allow us to solve those problems. So things like
Speaker:AI may have some speed up, but it's not going to be as
Speaker:significant as it would be with something that is an NP hard problem. And
Speaker:that's the origin of the whole. You
Speaker:know, this would take the lifespan of the universe several times
Speaker:over to solve this problem. That's the origin of that. I don't want
Speaker:to call it a meme, but that idea, we can say meme. It's. Okay. Okay.
Speaker:Wasn't sure if that would qualify as a meme, but. Yeah.
Speaker:Well, my classification. We're not doing humor
Speaker:classification yet, so we'll discuss that on the next interview.
Speaker:The. But yeah, that's the main. The second point in which
Speaker:quantum is going to help is there's a lot of problems that are better solved
Speaker:through quantum. A couple
Speaker:discussions I've had with other people in the field is regarding chemistry.
Speaker:Chemistry is by nature quantum. In order to have
Speaker:the data to go into a system, we have a lot of, and
Speaker:I'm speaking this time as a biomedical engineer, that
Speaker:the data itself needs to be converted into classical data for us to understand it
Speaker:and interpret it with our systems. But because the
Speaker:chemical data by nature is already quantum, we can have a quantum to quantum
Speaker:interface, allowing us to. To have that problem solved
Speaker:directly without having to worry about converting into classical and then
Speaker:reconverting classical to quantum, which is one of the main issues with
Speaker:quantum right now. But the idea is that there's other things that are
Speaker:quantum in nature and we're still trying to understand what Is by definition
Speaker:quantum in nature. And then quantum computing
Speaker:is better handled to do so. And the third
Speaker:is to a point overall, speed up.
Speaker:The issue that we have right now, let's go with AI, is that it
Speaker:takes a lot of time for big models to run. It takes a lot of
Speaker:time for different, a lot of
Speaker:data centers and servers. They take up a lot of power, they take up a
Speaker:lot of energy and so on and so forth because they have so much that
Speaker:they need to run quantum. Because of the nature of
Speaker:the multi states and multi state
Speaker:connections as well as the entanglements and
Speaker:many other factors that we can talk about later. I don't, don't want to
Speaker:get too much too into the weeds with that allows
Speaker:the speed up to be more significant than it would
Speaker:be by just adding more servers and just adding more classical computational
Speaker:methods. And
Speaker:those three points would are the mainstays of how
Speaker:quantum. Quantum will be more important.
Speaker:Now I'm. There's also cryptography.
Speaker:I specifically don't talk about cryptography that much because it's not my
Speaker:forte. There's a lot more on cryptography that has been done for
Speaker:both pre quantum and post quantum due
Speaker:to the fact that quantum can solve a lot of current cryptograph, current
Speaker:classical cryptographic methods. I'm not super
Speaker:familiar with it, so I don't want to speak to something that I'm not super
Speaker:familiar with. Well, that's what's really got people freaked out. I think a
Speaker:lot of people, A lot of people who with the money are freaked out about
Speaker:that. Right. And for good reason. Right. I
Speaker:was recently at a dinner with a big
Speaker:tech luminary and he was kind of like, yeah, he was very down on quantum
Speaker:computing, which I found kind of surprising. And I was like.
Speaker:And he goes. And then somebody else at the table beat me to the,
Speaker:to the punch of like, well, what about Shor's algorithm?
Speaker:Because you know, that's a fluke.
Speaker:And I'm thinking to myself, I think I might even said it aloud. Yeah, but
Speaker:what a fluke though,
Speaker:you know. So for the, you know, I think a good analogy would be like,
Speaker:you know, somebody figured out that if you,
Speaker:I mean it has, it has the potential to really upend kind of
Speaker:how conventional cryptography is done and that that's a problem. And
Speaker:yeah, I mean, you're right. Like, I think there's a lot of people that are
Speaker:hyping up quantum to such a degree of ridiculousness,
Speaker:but at the end of the day it's only really good at solving
Speaker:at least right now. Right. I think. I think right now we
Speaker:know it can solve a very small subset of problems. Right now those
Speaker:are big problems, so yay us. But I also think, too, that.
Speaker:Can you imagine, I think we're very much in the transistor
Speaker:days of quantum computing. Right? So, like, I also
Speaker:think we don't know what we don't know yet. Right. Like, I don't think people.
Speaker:Bell Labs, I think, invented the transistor. Right. I could be wrong on that. But.
Speaker:But I don't think they. They had envisioned TikTok, Right.
Speaker:Or YouTube or podcasts. Right. So I think that. I think that there
Speaker:are plenty of things now that we can't
Speaker:imagine yet could come about because of quantum
Speaker:computing. Right now we know it only solves a certain subset of things, but I
Speaker:also think that we don't know what we don't know.
Speaker:Yeah, and that's a very good point with it, because I also want to make
Speaker:the point that we could be farther in quantum computing
Speaker:if Covid had not happened. Really? So you think Covid really
Speaker:delayed. It had a significant delay for a lot of
Speaker:developments because due to.
Speaker:So there's a concept in logistics known as Lean Six Sigma. Lean
Speaker:Six Sigma works on basically having the most efficient way
Speaker:of doing things in certain areas. What this also led to
Speaker:was a lot of. One of the
Speaker:principles in Lean Six Sigma that had an effect on the shipping industry
Speaker:was that you're not supposed to have a significant amount of reserves in certain areas
Speaker:because it's more cost effective to have more places moving
Speaker:around than it is to have more reserves. So
Speaker:during COVID that's why there was a lot of shipping shortages. Oh, there's a
Speaker:time inventory and all that stuff. Exactly. That's exactly what I'm talking
Speaker:about. Thank you. The. And because
Speaker:they didn't have the backups, a lot of people didn't get food, a lot of
Speaker:people didn't get necessities. But also a
Speaker:lot of big quantum computational
Speaker:projects, specifically building quantum computers, were delayed.
Speaker:Oh, interesting. There was also other things
Speaker:going on in the world that delayed the processing of certain materials that were going
Speaker:into the quantum computers as well. I can't speak to those because it's
Speaker:been a little while and I don't remember everything, but the.
Speaker:This delay still had a significant impact on quantum computing. We
Speaker:would be in, in
Speaker:my opinion, at least five years ahead than we would be now
Speaker:if those shipping delays had not happened. I. I cannot
Speaker:say exactly how much it would be because we cannot. We also would need to
Speaker:factor in how many people got sick during COVID how many people
Speaker:unfortunately passed away, that would have contributed a significant amount to quantum
Speaker:computing as well, and so on and so forth. But the point I'm
Speaker:trying to make is quantum computing doesn't live in a bubble, right? There's a lot,
Speaker:a lot of politics, there's a lot of logistics, there's a lot of everything,
Speaker:ironically, that quantum computing can solve some of the logistics problems. But
Speaker:the, there's a lot of things that quantum computing
Speaker:is affected by and that we also need to take into account.
Speaker:And also what quantum computing affects, including things like climate change.
Speaker:Because quantum computing needs a lot of a significant amount of
Speaker:energy, a significant amount of resources, to the point that
Speaker:I'm sure you both know. But I'm just saying in general, the. We need
Speaker:a significant amount of energy to cool quantum computers to the point that the
Speaker:computers themselves are in subs, sub
Speaker:zero temperatures, but to the point that they're subspace
Speaker:cold level temperatures. Like if you go into the vacuum of space, it is
Speaker:warmer than our quantum computer cooling systems.
Speaker:There's a lot to unpack there. And yes, I've heard that like
Speaker:there's still radiant energy from the big bang, that, you
Speaker:know, it's more colder than would occur naturally, basically. But
Speaker:that's an interesting point you bring up about COVID because when I
Speaker:was, when I first really heard of
Speaker:quantum computing, it was:Speaker:historically it's only open to
Speaker:Microsoft employees, unfortunately. So if you're a Microsoft employee and you're listening to this, you
Speaker:definitely want to check out mlads, that's what it's called. Just search around internally.
Speaker:They tend to be about 18 to 24 months ahead of the curve.
Speaker:And one of the speakers was very adamant that this was
Speaker:ajor player. This is November:Speaker:So now I could never tell. Like,
Speaker:was that just hype? Was she just hyping up the crowd or
Speaker:was there actually some kind of disruption And Covid kind of.
Speaker:You know, I'm not saying that that's the only
Speaker:reason, but your math checks out pretty legitimately, so.
Speaker:t, because nobody in November:Speaker:horizon. So I mean, that would make sense. And you remember
Speaker:Frank, my entrance into
Speaker:the whole quantum world was with my father, who was an
Speaker:IBMer, and he was writing algorithms out on
Speaker:quadrille pads of paper in the 80s.
Speaker:And no one understood anything that he was doing, but a
Speaker:couple people at IBM understood exactly what he was doing and they Were like, you
Speaker:just do. That because you're also very,
Speaker:one, we're back to Westchester county and two
Speaker:and all that too. I mean IBM is one of the
Speaker:few companies in the world that really thinks
Speaker:long term. Right. And they've even said that
Speaker:there's a number of debate. Obviously Jensen kind of brought this up in
Speaker:Jensen Huang early in the year kind of said what he said.
Speaker:But okay, let's say 20 years from 20,
Speaker:25. Let's just say we'll take what Jensen said, it's es
Speaker:as ground truth. Not saying I, but he's
Speaker:walking it back like, you know, I, I,
Speaker:I told you I recently saw him on like Fareed Zakaria and he was
Speaker:talking about how it's, it's really within a handful of years
Speaker:that we're going to start seeing some things, but it's not, you know,
Speaker:mass adoption of it,
Speaker:so, But I'm sorry Frank, I cut you off. Well, that's okay. I think my
Speaker:Internet cut me off. But I mean your dad was doing this in the
Speaker:80s and 90s, right? So this is clearly not like this is something IBM has
Speaker:been working with for a while. And correct me if I'm wrong, but I think
Speaker:Shor's algorithm was written by, I forget his first name. Shor,
Speaker:hence the name Peter Shore. And 94, I think
Speaker:was about 93. 94.
Speaker:So which you know, and I think you also,
Speaker:you drop, you, you dropped a name that I don't think most people realize how
Speaker:influential this guy's been. Claude Shannon basically
Speaker:invented digital information theory. Right. So like the idea
Speaker:he's probably the most influential person in history, that no one has any idea
Speaker:who he, that the average person wouldn't know. Right.
Speaker:Yeah. A good amount of my work has been investigating
Speaker:Shannon Information theory as well as Shannon Entropy and using that as a metric
Speaker:for other, other the problems and seeing how
Speaker:that works. But I also wanted to have a quick note.
Speaker:Funnily enough, IBM is also a huge part of my work as well
Speaker:because I'm at the Watson School of Engineering. Oh, interesting. That's
Speaker:awesome. That's awesome. And I work at Red Hat in my day job,
Speaker:so clearly, clearly Big Blue is never that far away.
Speaker:Right? There we go. Okay. Well actually
Speaker:I think it was this week that IBM just made an
Speaker:announcement about how they were working with
Speaker:Moderna with the MRNA
Speaker:vaccines and they were looking at, you know, how they could
Speaker:really start doing some medical health care with,
Speaker:with using quantum. And I,
Speaker:I was just blown away. Like to me that
Speaker:seemed like something that would be so practical and amazing for
Speaker:people if they could do enough algorithms and to figure out
Speaker:who is going to get like who has a proclivity to what. So they could
Speaker:potentially, you know, avoid it and do better for themselves. I think the
Speaker:medical advancements would just be out of this world.
Speaker:Well, biology, medicine. Yeah, I mean medicine is basically applied
Speaker:biology and biology is arguably applied chemistry. Right. Like so like it
Speaker:wasn't that an XKCD cartoon where it
Speaker:showed like, you know, which is the most pure. That XKCD is this
Speaker:nerd web karma comic and
Speaker:there's one of them where they show like you know, basically
Speaker:they were these, they lined up based on like how
Speaker:abstract their science was and like well you know, biology is applied chemistry, chemistry
Speaker:is applied physics. And then there was some guy all the way like to the
Speaker:side of the room that basically said, well I'm math, I'm a mathematician. Right. And
Speaker:everything else is just applied math. That was, I thought that was funny. Little nerd,
Speaker:little nerd joke there. Sorry about that. No, it's all good. We want that here.
Speaker:So Michael, let me ask you, if you're looking at the quantum ecosystem
Speaker:globally, who do you think is getting it right
Speaker:and communicating to others well about
Speaker:what they're doing so that people can learn? I'm
Speaker:going to split that into two different questions because
Speaker:the people who are. So let's go globally and we'll talk about
Speaker:companies because every country tackles this a little bit differently.
Speaker:US has the biggest base in quantum just because we have Google, we
Speaker:have Microsoft, we have IBM. There's a good amount of other
Speaker:companies that are up in Canada. I believe Xanadu is in Canada and they have
Speaker:a really good base as well. D Wave I believe is over in the uk
Speaker:but I don't quote me on that, I can't remember where they're, they're
Speaker:based out of. But the UK is also having a significant quantum initiative.
Speaker:Japan has a lot of work but not the. Not as much via company but
Speaker:through their institute known as Riken R I K E N
Speaker:and they have a lot of quantum that's coming out of there, not to
Speaker:mention all the academic spaces in every country. France and Switzerland
Speaker:are also having significant amount but again the more academic
Speaker:and government oriented, the company oriented. So let's talk about the
Speaker:companies and so on and so forth. The one that's been the best at communicating
Speaker:has been IBM, has always been IBM. Their
Speaker:software is open source. Everything is
Speaker:very well communicated. If they have, they have very good
Speaker:communication. Whenever they have issues with the software and they have very
Speaker:good communication and new developments and so on and so forth.
Speaker:The newsletters they do are incredible. Everything else is there is
Speaker:wonderful. I also, I've failed to mention mit. MIT is doing a lot,
Speaker:a lot, a lot. But
Speaker:going back to the companies, I believe
Speaker:the Google and Microsoft have
Speaker:been doing a lot, but not have been talking about it,
Speaker:which is both good and bad because in the current system that
Speaker:we have where companies are competing, they need to not say anything. But when
Speaker:somebody creates a new form of matter as a superconducting
Speaker:fluid that allows Quantum to be working,
Speaker:then there needs to be more communication about that and more disclosure
Speaker:about that to make sure that we understand that this is really how it works
Speaker:rather than it's just a fluke that they found in the lab.
Speaker:Right. But the
Speaker:actual research that they're doing is miles and miles ahead
Speaker:because not only because of the funding that they have, but because of the resources
Speaker:and the talents that they have. They have the best talent
Speaker:for this. All the companies do because they not only do they invest in it,
Speaker:they want a Quantum future. Nvidia is doing
Speaker:incredible work. I don't always mention them because they're in
Speaker:my head. They're more AI because of how much of the servers and AI work
Speaker:that they do in general, but they, their basis in Quantum
Speaker:is quite significant. On top of that, don't
Speaker:mention them as much because both Google, Microsoft and
Speaker:IBM have a lot more open access and a lot more access to their
Speaker:systems than Nvidia does. Nvidia does work, but they work more with companies
Speaker:than they do with individuals and they do have academic grants
Speaker:and then do have a lot of work with academia for that kind
Speaker:of stuff, but less with the public than the other than the other three.
Speaker:I also wonder too like how much of the
Speaker:defense industry, the military
Speaker:industrial complex, how much of this are they working on and they're
Speaker:not talking about? I think you bring up an interesting point. There's a lot of
Speaker:innovation going on here, but maybe not everyone wants to share that information for
Speaker:reasons real and imagined. Yeah, and
Speaker:there's always the big question of, I mean
Speaker:the America is home to the Manhattan Project and what we used
Speaker:Quantum for and what. Right. Forgive me
Speaker:for the, the
Speaker:manner of speaking, but really blasted
Speaker:Quantum into a public space, the
Speaker:using. We also have a significant amount of
Speaker:political tensions throughout the world. We, we don't know as much as what
Speaker:China is doing, what Russia is doing, what compared to the.
Speaker:While we're in the US around the time we don't know what Canada is doing
Speaker:either. This isn't, this is not an affront to any
Speaker:country. This is just saying. Goes
Speaker:back to the, the concept of countries and kings, right? They, they
Speaker:always share, they don't always share. Right. It's, it's, it's
Speaker:basically poker, but the stakes are like a lot bigger, right. That
Speaker:not everyone's gonna share their cards. Right. This is not new. Art of
Speaker:War talks about espionage and keeping secrets. And it was
Speaker:written what,:Speaker:2500 years ago. Like so this is not a new concept. So like, you know,
Speaker:chances are any country that's alive, certainly anyone who's alive
Speaker:today, was not around then. So this is, this is, this is more a function,
Speaker:I think of the human condition than any particular political
Speaker:ideology. Yeah, exactly. And the
Speaker:one big issue is that if we're all
Speaker:developing quantum at the same time and
Speaker:we're not communicating about it, what have other, specifically quantum computing,
Speaker:I should say, what have we already developed that everyone has and what have we
Speaker:haven't developed that we all should be going for?
Speaker:Right. And this goes across the board for countries, for
Speaker:companies, for individuals. There may be someone in a different university
Speaker:who's doing similar work than I am and is
Speaker:a few steps ahead of me or a few steps behind me. Right, and you'd
Speaker:be better together. It's very Canadian of me. But you know,
Speaker:I mean, I know I talked about, I don't disagree here at all, but I
Speaker:do, I think we would be better together and I think that
Speaker:eventually there's going to be leaders
Speaker:amongst all the different kinds of cubits
Speaker:and they're not going to be the same leaders. And then,
Speaker:you know, groups can then, you know,
Speaker:silo if they want to, depending on, you know, what qubits they're using
Speaker:for their solutions. But again, it
Speaker:would be better as a community and sharing would is
Speaker:the way to go in my opinion, as the
Speaker:Canadian here
Speaker:who's from New York. So you have to understand my inner conflict. Right.
Speaker:I was gonna say like I'm always. Battling, like I'm a border and bred
Speaker:New Yorker. It's the first thing I tell everybody. But I've been living in Canada
Speaker:for 15 years. I became a dual citizen. But
Speaker:I, I can see why there. I can see certain things that are just done
Speaker:better. Not everything, but certain things are done better,
Speaker:you know, so I think we should share. Let me ask you this,
Speaker:Michael. At Impact Quantum, we're really all about
Speaker:accessibility. What advice would you give
Speaker:to young professionals or curious minds who want to contribute
Speaker:to the quantum future. The
Speaker:short of it is do it. There's a lot of
Speaker:open there. It depends. But the long answer, it depends on which way you want
Speaker:to contribute. So there's ways you can contribute
Speaker:in software, there's ways you can contribute in the hardware. There is
Speaker:reskilling programs that go for quantum
Speaker:engineering, meaning quantum hardware engineering. Like you'd be working with actual
Speaker:lasers and other systems to develop quantum
Speaker:hardware, to see how you can develop qubits, how you can develop quantum
Speaker:computers and quantum service and so on and so forth. There's other programs that
Speaker:are just quantum algorithm stuff and all that is on
Speaker:IBM for free. That's part of the reason that they're. I think of them as
Speaker:the leader in IT because not only do are they able to
Speaker:set up the entire IBM, IBM quizkit
Speaker:language. I believe I'm pronouncing that correctly. I honestly have no idea.
Speaker:That allows you to do quantum computing in Python, but they also have
Speaker:very detailed and very informative
Speaker:documentation for every algorithm that, that exists in
Speaker:quantum computing. And you're able to go through it, able to understand
Speaker:it. And that's actually a good case of when you can use ChatGPT
Speaker:is explain this to me better. You find an algorithm, you,
Speaker:you see what that does, but you're like, I don't know exactly where this should
Speaker:be used. And then you have ChatGPT or another AI, say, well,
Speaker:you can use it this way, you can use this, this type of data source,
Speaker:you can use this type of thing and then build it. There's a lot of
Speaker:competitions out there on different sites of how to use quantum for
Speaker:different things. Of do we, can we use quantum for
Speaker:biology? Can we use quantum for transportation problems? Can we use quantum for this, that
Speaker:and the other thing? There's a lot of conferences too. If you have the ability
Speaker:to go to conferences either as an academic or professional, there are quantum
Speaker:conferences. I believe IEEE Quantum is still,
Speaker:still has vacancies and that's going to, I forget where it is, but it's
Speaker:going to be in a couple of months. And they're basically at the
Speaker:forefront of quantum engineering, both on the algorithm side and the hardware
Speaker:side. But the
Speaker:better way to say it, get involved in whatever you can get your hands on
Speaker:and then if you don't like that, move on to something else.
Speaker:That's great advice, particularly in a day when an age when we're so
Speaker:overwhelmed with information. There is a lot of information
Speaker:out there. Pick one thing and keep going at it. If you don't
Speaker:like it, move on to the next, move on to the next, move on to
Speaker:the next if you have the ability to do so.
Speaker:The best way to think about it, if it's not your job, have fun with
Speaker:it. If it is your job, then figure out which is going to be the
Speaker:best way to help your job. For example, there's something known as a
Speaker:variational quantum eigensolver versus a variational quantum classifier.
Speaker:VQC versus a VQE Eigensolver is
Speaker:better for chemistry problems, classifier is better for AI
Speaker:problems just because that's how they're built. So someone who working in
Speaker:chemistry is better is going to be better suited for a vqe and then
Speaker:someone working in AI is better suited with a vqc. And
Speaker:this is also something that you can use an AI for to say which
Speaker:algorithms, which systems are going to be best for me to use in my job
Speaker:on a day to day basis. Right.
Speaker:Interesting. What do you think are the current
Speaker:bottlenecks in quantum hardware and software
Speaker:that are the most urgent to solve? The
Speaker:availability of qubits and servers and
Speaker:so on and so forth. We're limited by the amount that we can
Speaker:use, which is both good news and bad news. Bad
Speaker:news is obviously we can't use as much. So it's either going to be a
Speaker:high cost for somebody going to be using especially someone who isn't
Speaker:at a either isn't at a university that has access or
Speaker:someone who is or a company that has access to and they're just doing
Speaker:on their own. It's going to be more difficult to use qubits. But
Speaker:the good news is this is pushing for development. As
Speaker:humans we like to adapt and this is another way of doing it. So there's
Speaker:something known as NISK quantum devices and these
Speaker:blend classical and quantum to make a near
Speaker:term system. Some you can also call it a CQ system
Speaker:which is a classical quantum algorithm and algorithm and
Speaker:systems. The one of my projects in
Speaker:itself is a full quantum quantum
Speaker:system and another one, it another one is a
Speaker:hybrid classical quantum system. And the classical
Speaker:quantum system is the quantum
Speaker:side of it doesn't exist. Meaning it's a novel way to
Speaker:use a classical system and we quantumized it in a, in the manner of
Speaker:speaking. But I can go on about that a little bit
Speaker:later. But the main idea is when we
Speaker:have the ability to only use a certain amount and we're limited in the resource,
Speaker:we're still going to adapt. We're still going to try and figure out a way
Speaker:to use it. And we're like, okay, we don't have enough quantum. Okay, we're going
Speaker:to use a little bit more classical to meet the need that
Speaker:we need, that we need to fill.
Speaker:Interesting. What's your advice through kind of
Speaker:existing IT professionals to
Speaker:start looking into this? I'll go back
Speaker:to what I was saying about find which one is going to be best for
Speaker:you. Right. So some IT professionals are going to be more in
Speaker:cybersecurity. So reading things on Shor's algorithm, how
Speaker:quantum is going to affect RSA keys and how to combat that and so on
Speaker:and so forth. That'll be very helpful. Right. And
Speaker:people who are going to be more on the logistics side of
Speaker:it, trying to see how their transportation problems and job
Speaker:shop scheduling problems can be solved with quantum algorithms as well
Speaker:as quantum systems. But everyone to take it all with a grain of salt
Speaker:because using qubits
Speaker:and trying to find how qubits are going to be used for certain
Speaker:problems, mainly like let's say we're going cybersecurity. So we're
Speaker:talking about malicious attacks. We don't have enough qubits to have
Speaker:a significant DDoS attack on the system or something
Speaker:that's going to take tackle a lot of RSA keys at
Speaker:once. Again, I'm not a cybersecurity professional, so some of this may be a little
Speaker:bit nonsense, but
Speaker:the going back to the idea of
Speaker:using quantum for anything, figure out what your thing
Speaker:is and what quantum could solve for you, because there's a lot of things that
Speaker:it's been adapted for. And using quantum in now
Speaker:you can also, you don't need to use quantum specifically, you can use quantum inspired
Speaker:algorithms that will allow for a little bit of a speed of a little bit
Speaker:of help instead of using a full quantum system. And then you don't need to
Speaker:worry about qubits at all. Right. Or
Speaker:emulation, I think is another. Yeah. Thing people call it.
Speaker:Yeah, but yeah, no, that's a good point. Well, there's going to be emulation and
Speaker:then there's going to be quantum inspired algorithms. So when we're going to call
Speaker:emulation, we're going to call more simulation. When you're simulating a
Speaker:quantum algorithm on a classical system, while there's a quantum inspired
Speaker:algorithm where it's going to be a. Let's say we take Shor's
Speaker:algorithm and then use that for a specific cybersecurity
Speaker:problem, but use the ideas behind Shor's algorithm
Speaker:to rewrite the classical issue. Oh, I see
Speaker:what you mean. So there's quantum math involved and there's quantum
Speaker:mechanics, and using the quantum mechanics to basically apply
Speaker:matrix calculations and other methods that Shor
Speaker:does to that cybersecurity problem, and then it becomes quantum
Speaker:inspired. I see. So no quantum
Speaker:hardware, not even necessarily quantum algorithms
Speaker:per se, but.
Speaker:Interesting. Interesting, exactly. That's going to be something that's
Speaker:going to be resurging a lot because of the lack of qubit access, because
Speaker:of people still want to use it, people still want to
Speaker:adapt. And the sad way of saying this
Speaker:is people want Quantum to stay relevant. And without
Speaker:access to qubits on full quantum software, the algorithms and other
Speaker:quantum inspired algorithms are going. And this
Speaker:methodologies are gonna are booming right now, and they're gonna keep booming until
Speaker:we're able to catch up with the qubits. Right,
Speaker:interesting. So if you could accurately
Speaker:forecast one quantum wave or pivot
Speaker:by 20, 30, so five years from now,
Speaker:alignment with commercial applications, talent
Speaker:scaling or policy frameworks, what do
Speaker:you foresee? So
Speaker:as the AI hype dies down,
Speaker:investors and other groups are going to be looking for the next
Speaker:big thing. They're going to assume that Quantum is going to be it for a
Speaker:little bit. And that's what we're seeing the
Speaker:beginnings of now. That's why we're seeing the big story about Quantum. And then it
Speaker:dies down in a couple of weeks. Another big story about Quantum dies out in
Speaker:a couple of weeks. That's similar to what happened to AI at the very beginning
Speaker:of it as well. This is also the same thing that happened to
Speaker:genetic engineering way back in the day, where there was a bunch of really big
Speaker:stories about like the Human Genome Project and then a bunch of big stories about
Speaker:how this is going to solve cancer and so on and so forth. And right
Speaker:before CRISPR hit, there were a bunch of big stores, a bunch of
Speaker:big quan, big, not quantum, excuse me,
Speaker:big genetic changes and big. And a lot of
Speaker:things that really helped get genetics onto its ground
Speaker:that it's been for the past couple decades, and
Speaker:then became a boom in using genetics for basically everything.
Speaker:And that's what's happening to AI now. But the main thing
Speaker:is that this is not small random
Speaker:developments that burst forth. It's a staircase.
Speaker:And each step is being built. Some of the steps just
Speaker:look a little bit better than others. So as these steps are
Speaker:being built, they're going to reach a certain point in which everyone
Speaker:is going to know about it, everyone's going to have access, everyone wants to build
Speaker:it. One of these points is going to be the
Speaker:accessibility of it all, because AI and
Speaker:technology only really boomed when everybody had access. If
Speaker:OpenAI didn't give, didn't give as much access to people,
Speaker:it would not have been as big. ChatGPT would not have been as big if
Speaker:people didn't have access to as much access as they, as they did and as
Speaker:they do. Quantum may have the same thing.
Speaker:However, I'm saying this as somebody who is developing algorithms rather than
Speaker:somebody who's developing algorithms within the university
Speaker:rather than somebody who's developing the systems within
Speaker:a government or military setting.
Speaker:Quantum cryptography is going to be the thing that everyone wants to invest in
Speaker:in the beginning because more the main thing that you can
Speaker:count on with people is that they want to be safe.
Speaker:And cryptography, cryptography and quantum cryptography poses a threat
Speaker:to that. Regardless of what we say about AI, regardless of what we say about
Speaker:climate change, cryptography is the quote, unquote,
Speaker:present and clear threat for a lot of people.
Speaker:That will be the first thing that will spark a lot of investment, that
Speaker:will spark a lot of development, that will spark a lot of everything. So when
Speaker:there is quote unquote breakthroughs and that next step to
Speaker:really see how we can use cryptography and anti cryptography
Speaker:methods and cybersecurity methods. I keep saying photography, but really we're talking
Speaker:about cybersecurity here. Cybersecurity
Speaker:methods in quantum and combating the quantum. Once those are hit,
Speaker:then there's going to be a significant amount of boost, there is going to be
Speaker:a significant amount of interest and then the rest will develop because of that.
Speaker:Interesting. I like that.
Speaker:That's cool. Where can folks find out more about you and what you're up
Speaker:to? Sure. So I am going to be, I'm on
Speaker:LinkedIn as you have the notifications from that. I will
Speaker:be starting my work through GitHub. I'm going
Speaker:to be publishing several things through there and I'm going to be posting my publications
Speaker:as well as on my Google Scholar, my research gate
Speaker:and my LinkedIn as well. So that's my research gate
Speaker:and my LinkedIn will be the places to check. Okay,
Speaker:cool. Excellent. Excellent. That's great. Honestly, this has been
Speaker:fantastic. This really has. I mean this has been, this
Speaker:has been a very enlightening interview. So thank you for that and thank you for
Speaker:your time and we'll let RAI finish the show.
Speaker:And that's a wrap on today's Quantum Ramble with Michael Magid.
Speaker:Proof that system science isn't just a polite way to say I dabble in
Speaker:everything from qubits to the quantum cold. We've
Speaker:decoded just enough to sound clever at dinner parties,
Speaker:but not quite enough to build a quantum computer.
Speaker:Remember, if you think you fully understand quantum, you
Speaker:probably don't. Until next time, stay curious,
Speaker:stay entangled, and for heaven's sake, don't trust an
Speaker:AI in a trench coat.
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