344: Superposition, Entanglement, and Interference
Transcript for Embedded 344: Superposition, Entanglement, and Interference with Kitty Yeung.
EW (00:06):
Welcome to Embedded. I am Elecia White alongside Christopher White. This week we're going to talk about many things, physics, art, quantum computing, teaching, fashion. So I guess we have six guests on, oh, actually given that list, we could really only have Kitty Yeung as our guest.
CW (00:27):
Hi Kitty, thanks for joining us.
KY (00:30):
Thank you so much for having me.
EW (00:31):
Could you tell us about yourself?
KY (00:35):
I am Kitty. I work as a senior program manager and creative technologist at Microsoft. I currently work on quantum computing, and I produce education materials for quantum computing and I am a physicist, but I love art. So I have a fashion brand called Art by Physicist, which I design dresses and wearable technologies for.
EW (01:05):
I'm hoping we get to talk about all of that but, I also am hoping we don't end up with a three hour long show. So before we get started, we want to do lightning round where we ask you short questions. We want short answers and if we're behaving ourselves we'll, won't say are you sure? And how and why and where can I get one? Christopher you go first?
CW (01:26):
Sure. The Copenhagen interpretation, fact or fiction.
KY (01:30):
Neither, is the interpretation.
CW (01:34):
She does work in quantum mechanics.
EW (01:38):
Would you rather complete one project or start a dozen?
KY (01:43):
Complete one project.
CW (01:46):
There's two options for this question, I'll ask you the one way and then if you don't like I'll ask a different meta question. How many electrons are in a chicken?
KY (01:56):
I don't know. That's the short answer.
CW (02:00):
Is that a fair question to ask a master's candidate?
EW (02:02):
Master's in physics.
CW (02:03):
Yes.
KY (02:03):
It's unfair. But you need to give them additional information for them to calculate.
CW (02:11):
Great. Thank you.
EW (02:12):
Like the weight of the chicken.
CW (02:13):
I feel much better now.
KY (02:16):
Density. Assuming is mostly water in...
EW (02:20):
Yeah. All right, do you have a favorite acronym?
KY (02:24):
No, I don't like acronyms.
CW (02:27):
Do giraffes make sense?
KY (02:29):
Yeah, totally.
EW (02:32):
Do you have a favorite fictional robot?
KY (02:35):
I like Marvin from the 2005, version of The Hitchhiker's Guide to the Galaxy.
CW (02:44):
And do you have a tip everyone should know?
KY (02:47):
I recommend everyone teach their kids automation.
EW (02:52):
Why automation?
KY (02:56):
Is going to be very useful if they have a hobby they want to do, they can have some of the labor is done with machines and they can do more creative work.
EW (03:08):
Okay. So professionally, your primary method of earning money, what do you do?
KY (03:14):
I work at Microsoft as a physicist and a program manager and that's my day job. And I love that too, because it allows me to stay as a technical physicist.
EW (03:32):
Okay. So at Microsoft, physicist, you work in quantum computing?
KY (03:37):
Mm-hmm (affirmative).
EW (03:39):
What does that mean?
KY (03:41):
It means different for different people working in the group. So I manage the education effort for the quantum computing contents. Also I manage the documentation and create the Ms Learn education materials. And also I teach, I teach the community sometimes give workshops. Also for different people, we have a lot of different roles in quantum computing.
KY (04:14):
So there are researchers, there are also programmers, there are a lot of program managers that need to help create products. So my role is quite unique and fun to produce materials that we need to communicate to people. Because this is relative still a emerging technology and emerging industry.
KY (04:42):
We need to give people the learning that they need, in order to solve their problems using quantum computing or learn the materials in order to become the next generation of quantum computing workforce.
EW (04:57):
What do you at the quantum computer other than crack passwords?
KY (05:04):
Yeah, sure. Shor's algorithm is definitely one of the interesting ones that has a application. So is maybe a negative application because using Shor's algorithm, you can very quickly break as you said the RSA encryption method. But that also means that we need to come up with better algorithms to have more secure encryption methods.
KY (05:32):
And other than that, there are a lot of problems that our current classical computers are not able to solve. Or even some problems our most powerful, super computers can run into limitations. So things like simulation for chemical materials discovery, drugs. Those are relying fundamental quantum mechanical interactions.
KY (06:02):
So maybe the best computer still struggle when we try to simulate and run simulations to understand the materials and coming up with designs of these materials. There are also some problems that are not fundamentally classical. They are... Sorry, they're not fundamentally quantum, they are classical problems.
KY (06:25):
But we run into every day like optimization and cryptography you already mentioned, and data processing that we could leverage the different way that quantum computer offers. To solve these problems using quantum inspired or a quantum mechanical method, to represent those problems and solve them more efficiently
EW (06:54):
These sorts of problems we're talking about, are these the ones that in CS are called NP hard or PSPACE complete?
KY (07:01):
Yeah, there are quite a lot of them in that.
EW (07:04):
I mean, can quantum actually solve that level of problem?
KY (07:10):
There's ongoing research and, this is definitely a developing field that a lot of researchers are trying to come up with new algorithms, to solve these classically unsolvable problems.
EW (07:25):
Okay. So I come to you with a problem, like there are some origami folding methods that are determining whether or not they're foldable, is definitely harder than NP complete, maybe PSPACE based complete. So what do I do? I mean, quantum computing has always been this thing that's like...
CW (07:50):
Maybe we should back up and talk about what quantum computing is.
EW (07:54):
Well, I mean, it's obviously computing with quanta.
CW (07:58):
Yeah.
KY (08:02):
Yeah, actually...
CW (08:03):
Because it sits completely different from normal computing methods.
KY (08:10):
Yeah. Like normal computing, classical computing we rely on bits, that's using transistors on and off. But in quantum computing you can leverage this superposition of different states. So it's not just zero all one, you can have zero and one, superposition or linear combination.
KY (08:30):
So you have a probability of having zero and a probability of having one in your qubits system. So in this way, you can actually have two effects coming out due to superposition. You can have interference of amplitudes between these different states and you can also have entanglements between qubits.
KY (08:55):
So entanglement means that when you put them into a specially arranged configuration, you can measure one of the qubits, without measuring the other one you already know the result of the other one, their results are correlated. So that you can imagine could be very useful in quantum communication.
KY (09:17):
And interference allows you to extract this powerfulness of the quantum computing that you can let more likely result to come out. And the less likely results will be canceling each other out. So you can get these interference between amplitudes. So quantum computing is a clever way for you to leverage these three concepts.
KY (09:49):
You can write algorithms to let your qubits represents the data, you can encode whatever number or text into your qubits. And then feed that into some algorithm that allows you to do this interference and entanglement. And very efficiently at the end, you can get the type of data that you desire.
KY (10:17):
Is not going to be faster, is not going to be like... I think a lot of confusion around parallel computing is now going to be always faster than all of the existing classical algorithms. But for certain problems you can leverage superposition, entanglement, and interference to take advantage of.
EW (10:40):
Okay, I'm going to go back to origami because it's something that I understand. When you start out...
KY (10:45):
I don't understand origami.
EW (10:47):
Okay. When you start out with a piece of paper, you can get a crease pattern from various places. And there are mountain and valley folds, and that is part of the crease pattern usually. But there's this idea that you can have a whole bunch of lines on the paper that should represent mountain and valley folds, but you don't know.
EW (11:11):
You don't know which it is, is it up or down? And then the question becomes, is this a foldable pattern? What does it fold into if you don't know which are up and down? What are the possible folds? And so it sounds like what you're talking about with the probability, if I set all of the folds to 50% up, 50% down.
EW (11:36):
And then I entangle some of the points so that, if two points are on an edge, they have to go up or down themselves. Am I thinking about this right? I know this is putting it in a different frame but...
KY (11:51):
That's a very interesting question, yeah. I think there might be two ways to think about this. I'm not an expert in origami.
EW (12:01):
Me neither, really.
KY (12:03):
I guess it would depend on the type of problem you want to solve with your code. So representing your mountains and valleys with amplitudes. Yeah. I don't think those problem is a quantum mechanical problem, but you can, if you want to play with interference, perhaps you can represent it either way.
KY (12:34):
But the other thing that I can think of that quantum can perhaps help, is not strictly quantum computing using interference and entanglement. Is more like learning from quantum mechanical reactions, and then represent your system with a Hamiltonian that can allow you to find the minimum energy state.
KY (13:00):
This I know that, it has been applied through origami that how do you fold a piece of paper into a certain shape? How much energy would that take and what is the minimum energy number of phones or whatever configuration that's your system is the most comfortable and most likely to be in?
KY (13:20):
Perhaps this could be a question you can represent it with a quantum inspired optimization problem. So perhaps you can write the Hamiltonian of your system and solve it as matrix to do a minimal energy. Like Eigen energy, eigenvalue type of calculation. That could be something interesting to explore.
EW (13:48):
Yes. Although setting up the Hamiltonian is actually the hard part here.
KY (13:54):
Yeah, sure.
EW (13:56):
Because there are too many options. If you have one fold on a paper, it's either a mountain or a valley. If you have two and they cross, now you can do some interesting things and if you have a hundred, it just gets impossible.
CW (14:12):
I want to interject and just say that this conversation makes me so happy.
EW (14:15):
Yeah. I think he won quantum bingo already with Hamiltonian.
CW (14:20):
Well, it's been 344 episodes and finally somebody has mentioned the Hamiltonian.
KY (14:25):
I was wondering if I should mention it.
EW (14:29):
Okay. One of you explain what a Hamiltonian is.
CW (14:33):
I'll let the person with the PhD do it.
KY (14:37):
I would just explain it in a pretty high level. That is a way for you to capture the behavior and state of your system is basically it has the unit of energy. So say for example, some thought experiment if you want to roll down a ball from a mountain down to the valley is converting from a high potential energy state to a high kinetic energy state.
KY (15:15):
As it rolls down and speeds up. And both the kinetic energy and potential energy can be captured in your Hamiltonian as two terms. And in quantum mechanics, you need to work out the energy of your, say a hydrogen molecule. You write it into a Schrödinger's equation and it tells you how your system behaves.
KY (15:42):
And the Schrödinger equation solution will include the energy, the potential energy, or kinetic energy or some other terms, in your system. And also the wave function that's that can describe how your quantum mechanical state behaves.
EW (16:01):
Okay. I have more origami questions, but...
KY (16:06):
I need to... I should have googled more about it.
EW (16:09):
No, I didn't even put it in the outline. I mean, the reason it's interesting from a quantum perspective is some of the problems that come up with paper, are way more complex when you apply them to proteins and protein folding is really interesting. But it's also unbelievably difficult to predict.
CW (16:29):
So can you give us an example of the simplest, what's the hello world of quantum computing?
KY (16:36):
Depending on the type of problem you want to solve. So if it is a hello world to test, if your system is in a quantum state, you could use a teleportation demonstration.
EW (16:53):
Yes. The hello world of quantum computing is a teleportation demonstration. That is the best.
KY (17:02):
So if you can show your system, if you had two qubits and if you can show that they can teleport that means you can't entangle them. And that also means you have put in a quantum state. But there are things that are much simpler. So we have the Q# language that we can use to...
CW (17:25):
Of course, I was going to ask and I was going to make a joke that it was going to be Q# and it was.
KY (17:31):
Yeah. Like you don't have to get into the hardware and the internal working of a qubit to do quantum programming. So we have this whole set of libraries and everything that you need as a new language for computation. We have one design for quantum computer. We can use Q# to program any type of quantum computers.
KY (17:57):
And you can just simply write some code and say hello world, and perhaps you can write like simple entanglement or superposition code to demonstrate. So that's probably the hello world for it.
CW (18:11):
Okay. Is Q# something somebody can play with without a quantum computer? I mean, can it be simulated?
KY (18:19):
Yeah. And all that you can find on Microsoft's Documentation, Quantum Documentation. Just search Microsoft Quantum Documentation. And there's still a whole list of Q# documentation and it has the simulation. And we also have the cloud computing service, the actual quantum service that allows people to write code on your own computer. But then connect to a quantum computer through the cloud and then program it that way.
EW (18:53):
He is so excited right now, I cannot tell you.
KY (18:57):
Yes, you should jump on it, I tried it. They have a lot of free learning materials. GitHub, Open-source. You can even write anything right now and contributes to the GitHub's repositories.
EW (19:10):
Okay. I want to talk about that. But first, I want to talk about the quantum computer itself. I mean, mentally, I remember having a wet chemical computers described to me long ago where you put a problem into a protein and then you shake it around and it turns colors to answer your question.
CW (19:31):
And I remember there were DNA based computers too. So give it a particular strand of DNA and it would solve a problem.
EW (19:37):
Yeah. So my mental model of quantum computers involves shoving electrons in places then shaking them, which I don't think is right. What is the hardware look like? How do you build a quantum computer?
KY (19:50):
There are different types. There are different kinds of architecture of the commonly built ones, that's pursued by industry and some academics. There's the superconducting circuits, which is like CMOS fabricated using conductors and inductors and you can create a resonance in your circuit.
KY (20:15):
And that you can use to represent your qubit's states in the superposition then you can entangle them. We also have trapped ions. We try using ion that have spins. You can define certain spin to be... Or certain spin energy, to be your zero state and another one to be one state.
KY (20:41):
And you can, when you pull that to go up and down and you can put them in superposition. So basically you need a two level system that you can control and make. Because they're already quantum mechanical systems, their energy levels are already in superposition. And then you need a way to manipulate which state they are on.
KY (21:05):
Microsoft is building this topological type of quantum computing. So it is a stack of materials that's got superconductors, semiconductors, insulators, stacked together. And you can create this special states for electrons to occupy. And they, at certain places on the nano wire, you can create those states.
KY (21:32):
And when they're occupied, your system, your qubit can be in the zero. Once they, if they're empty it could be zero state. So it's using many, many electrons interaction between each other and extracting this topological behavior of your system, to represent your zeros and ones.
KY (21:52):
So there are different types and their pros and cons between all of them. So the industry is definitely working very hard to build more and more scalable ones, to use them for different applications.
EW (22:07):
Scalable that's the word. So those all sound like things you build individually, not like transistors, which you just buy a chip full of them.
KY (22:25):
Yeah. Because transistors has been very, very mature.
EW (22:29):
Yes. Yeah.
KY (22:30):
In that case, yeah.
EW (22:31):
How many of these are in a computer? How many of these? So I assume it's going to... Quantum computing is Azure that you log in and you get some time on a quantum computer.
KY (22:45):
Yeah, that's right.
EW (22:47):
So how many...
KY (22:48):
How many qubits?
EW (22:49):
How many qubits? That's right. How many qubits can I have?
KY (22:53):
Well, it depends on the companies too. I think that those numbers we can probably find online is not that important actually. How many qubits can you have? It's more about if you can scale them and build certain tasks to solve them, solve certain problems that you can use them to solve.
KY (23:22):
And if they can be entangled, because you could have a lot of qubits but none of them is entangled so that's useless. There's also error correction you'd have to take into account. So the actual number of qubits that you need for a algorithm is smaller, much smaller than the actual numbers that you would need, to take into account error corrections.
EW (23:51):
Stupid probability.
KY (23:54):
Yeah. So you ought to have a robust hardware system so that you can minimize the actual qubits that you need, but it's very difficult.
EW (24:05):
So as part of setting up a quantum computing problem, I am designing the algorithm, I am inputting it into the computer, very, very difficultly. Through Q# which I'm sure is easy. And then I run it and the results are instantaneous, right?
CW (24:32):
Right. Either you got the answer or a demon appears and eats you.
EW (24:36):
I've always worried about that.
KY (24:40):
Well, any computation takes time.
EW (24:43):
Okay. So that is a myth in my head, that quantum computing, because it works...
CW (24:50):
Instantaneously.
KY (24:52):
No.
EW (24:52):
Because there's no probability, it just I mean, they should entangle, they should interfere and then I should get the answer. I mean, how long can that possibly take?
KY (25:03):
Boy, you have to put them into the actual hardware and also you need to compare what algorithms you are doing. I can give you a scale, like the Grover's search algorithm, which is a algorithm use, that's using entanglement and interference. And is trying to find items that you're looking for that, on order list.
KY (25:30):
So I like to give people this metaphor is like, you're looking for a book in the library, you know the title, but this library is very disorganized. Everything is just not ordered at all. So if you are using a classical algorithm, then you have to look at each item one by one.
KY (25:55):
If you are lucky, the first one is what you're looking for. But if you're unlucky, maybe the last one is what you're looking for. So then if you have N books, then you have to look at it like N times. If you are using Glover's algorithm, which is letting you feed all of your books into your entanglement, and interference box, then the books that you're not looking for are canceling each other out.
KY (26:31):
And when you output one that you're looking for has a really sharp peak and you can identify the item. And that could be much faster, you don't have to look at every single book one by one. So the classical algorithms scales with two to the end, if you have N bits. But the Grover's algorithm has a scale of two to the N over to if you have N qubits.
CW (26:59):
So it's better?
KY (27:02):
If you have a very large N, then you would see Grover's would have a much...
CW (27:08):
Oh, the exponent is N over two.
KY (27:10):
Yeah. Yeah, exactly. So you don't know the absolute factor if you run the algorithm once, how long it will take. But you can see that if N is big enough, then Grover's will be advantageous.
CW (27:22):
Got you.
KY (27:22):
So it's like a competition between the fastest super computer and the fastest quantum computer.
EW (27:29):
Okay. I think we're reaching the point where I want to whiteboard and to understand better. But you've already done that. You've been teaching that both for Microsoft and for Hackaday. How does that work? Is it... Yeah, how does that work?
KY (27:49):
Yeah, I've be teaching on Sundays at HackadayU since April. I started teaching those. It was just quite spontaneous is I wanted to draw a lot of the understandings I had about what I love to do. And quantum computing is what I wanted to represent with comics. And then, Hackaday started this ask for content that during the pandemic we wanted to offer the community, some new learning then quantum computing is a great topic for that.
KY (28:30):
So I actually started teaching people during the whole lockdown and is being, I guess tomorrow will be this 20 session that I would teach. And then Microsoft Reactor is also promoting the event. So it became like a cohost thing for Hackaday and Microsoft Reactor. We got a lot of community from different channels, that's joining the class ever Sunday.
EW (28:58):
And it's recorded so people can catch up and then join the class live.
KY (29:05):
Yeah, exactly. We are teaching through Teams. I draw a piece of comic every week. So before people join the class, they can see the comics, they know what topics we're going to talk about and all of the slides are saved and uploaded on hackaday.io.
KY (29:26):
I have a project called Quantum Computing through Comics and people can find all of the recording links there too.
EW (29:35):
And the Hackaday the folks wanted me to mention, that they're currently hiring teachers for all related to engineering, hard science and math. People can email superconference@hackaday.io. So you'll be getting more compatriots.
KY (29:54):
Great.
EW (29:54):
And you've mentioned the comic. What made you decide to do a comic book style instead of Visio or other more traditional methods?
KY (30:04):
I think comic is quite traditional. I hand drew everything. Is just an art form that I'm very comfortable with and I love doing. I've been drawing as long as I can remember. So I was a kid, I started drawing and I've always been using comics and graphic novel style to convey ideas.
KY (30:33):
So this became a natural choice of a media for me. So I also wanted to present quantum computing not in a very heavy way, because to some people it could sound a bit intimidating. And I think there's a lot of myths and hype about it that is not necessary. Actually quantum computing is not that hard, we just have to explain that clearly not in an intimidating way.
KY (31:07):
So the comics actually played a pretty important role in drawing people's interest, and people stop thinking that's a really hard thing that we can't do anymore. So I'm very happy about the effect.
EW (31:24):
Making it approachable is very important.
KY (31:27):
Mm-hmm (affirmative). Yes.
EW (31:28):
Your comics often have a cat in them. Is the cat named Schrödinger? Or does the cat have a different name?
KY (31:38):
Oh, good question so...
CW (31:39):
You can't know.
KY (31:41):
... they are actually different characters. The name, yes. Well that is from Schrödinger's origin original joke, that I think he actually came up with the matter for to mock on them, ideas. That if you put a cat in a box, the key here is that in the box you have a radioactive mechanism that is itself quantum.
KY (32:08):
And that can trigger a poison to be spilled or not. So if the cat drinks the poison, it will be dead, if the cat doesn't then it will be alive. But you will never know until you open the box and see what the result is. But the key here is that, it is triggered by a quantum mechanical reaction is not just any cat in the box.
CW (32:32):
Right.
KY (32:33):
So...
EW (32:34):
No, just putting the cat in a box is not a good way.
KY (32:38):
In my comics... So I like cats a lot and the comics actually has many characters. I recently made a page that tells people their names, and they can actually use it as a game that they can look at the name and what they do. So I have personas of a researcher who comes up with algorithms.
KY (33:08):
I have programmers who come up with applications and writes problem into a quantum computing solution. And they're early adopters, they're learners. They all have different names. So people can use that page to identify who they are. And in which class they appear.
KY (33:30):
I want to encourage people to do this, and then they can watch that whole exercise, whole class and then write down what they learn in a way drive people to really understand the class. So if anyone sends me their thinking, I can even give them a certificate, is called an out of the box thinker certificate.
CW (33:53):
I like that.
EW (33:53):
I've got Alison, Bob and a referee. Okay. I shouldn't be reading this now I should be paying attention. The comic style really does make it quite approachable. Quantum has been something that's quite intimidating. I mean, you say the word quantum and like...
CW (34:10):
It's so cool though. Sorry.
EW (34:13):
It's just is scary. Cool and scary. But spooky action at a distance, this isn't real, I'm not doing this.
CW (34:20):
Yeah, but those parts are all... A lot of those go into interpretation of what this all means. Whereas the actual mechanics of doing quantum and that's the part I like. All the other stuff is for the cosmologist to figure out.
KY (34:36):
Yeah, I think is probably we physicists didn't do a good job, explaining a lot of things and we should make it more accessible, but not hype it. Not make it sound so mysterious that if you don't have a PhD in something sciencey, you can't learn it. But the truth is if you are passionate and curious about it, and you focus on the concepts, you can very quickly get started using a quantum computer. So I think we need to do a better job demystifying it.
EW (35:21):
So this seems like you teach and you teach for Microsoft, you're doing teaching for Hackaday and you do physics. But that's okay, so that's your day job. At night, you put on superhero costume and do other things.
KY (35:41):
Yeah. And I think I'm on the opposite shift now that... At night I need to work with my colleagues in the US.
EW (35:50):
Right.
KY (35:52):
Yeah. But in my spare time, if I can find it. I do some creative work like design, fashion, and paint. Do some other graphic novel drawings. And I also do music. I play the piano and the harp and I also sing.
EW (36:11):
What planet are you from? Tell us.
KY (36:14):
I'm from the moon, not another planet.
EW (36:20):
Okay. So music. Classical, I mean, harp and piano is usually classical. Okay.
KY (36:27):
Well the... Yeah, I love jazz as well, but I am classically trained. So most of the pieces I play are from the classical end to romantic eras.
EW (36:38):
But the fashion part, when did your art turn to fashion?
KY (36:44):
That was a few years ago, I guess when I was finishing my PhD. I finished all the hands-on experimental parts and I was just writing my thesis then. And I really wanted to make something by hand and learn some new skills. I decided to buy a sewing machine and some books and learn some classes from YouTube and started sewing.
KY (37:11):
Even my first piece was a design that I draw on the paper. I've always been designing, for my graphic novel characters, especially. So I wanted to turn those ideas into reality. I also paint a lot of nature scenes, astronomical scenes. I have a set of digital paintings that I have on my website.
KY (37:41):
So I started looking at places where I can print them into very large fabrics. Then I started to making dresses that have my paintings on them that are really large pieces. That a whole dress is showing the earth or showing Saturn, the planet. And on the side I was playing with these Open-source hardware. There's some robotics projects with friends.
KY (38:08):
So I thought, why can't I combine the two? I can put the electronic scene into clothes and why not? So that's when I started merging different areas.
EW (38:19):
And so now you have dresses that light up.
KY (38:23):
Yeah, it was fun. It was quite natural, when you're a maker, you do things by hand and you can put something very quickly together when you have idea. But the hard part was actually turning those ideas, prototypes into products. And that really triggered my curiosity when people ask me where to buy my designs, I really didn't know how that whole design to manufacturing process worked.
KY (38:51):
Then I started looking into manufacturing and there are a lot of problems and crazy problems in the fashion industry. So turning my original handmade thing into a product took quite a while.
EW (39:06):
What kind of problems? I mean, thinking about moving something from a maker to a production system, that's... I believe Alan wrote a book about that. But how is it different for fashion and manufacturing, or how is it the same?
KY (39:27):
Yeah. Fashion industry is very, very old and we've been making clothes for thousands of years. And we have been making clothes pretty much the same way in the past hundred, 200 years after the first industrial revolution. When it helped the industry do things, mass scale, mass production of repeated units.
KY (39:53):
So if you're a new designer coming to this space, it's very difficult to find manufacturers who can support small scale. That can allow you to test the market first to build your maybe crazy handmades, interesting designs into products. That was the first hurdle that I came across.
KY (40:15):
And then I also found out that how pollutive that whole mass production method is, because the manufacturing is forcing everyone to mass produce. You basically have to have a really large quantity in order to build a brand, but then brands never know how much they can sell anything.
KY (40:37):
There's not really any good prediction of the market. So they would try to guess how much something could sell, but they don't want to lose the profit. Then they would overproduce. And it turned out that the clothes that's over produced every year that's never sold is 30% globally.
EW (40:59):
Wow.
KY (41:00):
Yeah. What do those brands do? They may donate it. They may sell them at lower prices, but we don't actually know how much they would send to landfill or each brands, we don't know how much they would send to landfill or burn them. But we know that it's globally, 10% of carbon footprint comes from the fashion industry.
KY (41:24):
So each brand would spend tens of billions of dollars making their new designs this season, and then they need to try very hard to get rid of them. So, yeah. It's quite sad to find out how all of this. As a engineer, I think there are solutions, it is quite shocking to be honest.
KY (41:48):
That as an engineer coming to fashion industry and seeing all these problems, you think that they're actually solutions, there are ways that we can solve them. We need to support creative designers to turn their ideas into reality. We also need to get rid of the waste and pollution.
EW (42:07):
Yeah. I mean, we almost need to make on demand so that you don't end up with extra stuff.
KY (42:13):
Exactly.
EW (42:15):
And we need to stop convincing people that they need to buy things just to buy them.
KY (42:19):
Exactly. It has to go to this. We need to go back to make to order, where before it was all mass produced, everyone had to go through a tailor and get something custom made for them. But it's very, very slow.
EW (42:34):
And expensive.
KY (42:35):
And we still have that. Yeah, expensive. We still have that system. So only if you want for special occasions, you may wear something like that. But for everyday wear, we need to change this date, this mass produce model. We have the technology now that, 21st century, we have all these front-end, back-end technologies.
KY (43:00):
We need to connect together to not just predict the market but also, allowing consumers to directly tell designers and fashion brands what they want. Then the manufacturer can just make them for the particular customer. And we have to build it in a scalable way that's able to reduce the cost.
KY (43:27):
Because at the beginning, if you're making one piece for one person that you will be expensive. But if you build a whole supply chain, when it's mature is not going to be that expensive.
EW (43:37):
And I know that there are some vendors that do this now.
KY (43:41):
Slowly, slowly is I think it has to be everyone has to do it. Everyone should use technology in their design and manufacturing process, shorten the development time so that they can allow creative designers turn their ideas into real products quickly. So actually I would use 3D printing as the example.
KY (44:07):
Like this is an industry that was very new and only took a few years to get to this mature stage. Now everyone can buy a 3D printer, or they can send it to some service online that can do design on a computer software. Then they can send any model online to get it produced.
KY (44:28):
And they can just pay for materials and shipping. Clothing needs to get there like 3D printing. If designers can design everything digitally, that means we need to have a standard. And we do to capture all of these materials, trains, all the details does in tech pack digitally.
KY (44:51):
Then the designers can do everything on online and through the cloud. They can submit their designs. And find the manufacturers that is closest to their consumers. So you can get things created more locally.
EW (45:07):
This sounds like a huge problem. I mean, this sounds like there are so many... Yeah. Okay.
KY (45:15):
It'll take decades, I think... Yeah. It's not just the technology. I will say the technology is pretty much there. We just have to connect them. And a lot of our existing technologies that will help computer vision, 3D simulation, they need to be applied in fashion industry and they need to be connected to the physical manufacturing.
KY (45:41):
So we need an infrastructure and network to do that. But the tech technically I think is totally doable. If one of the big places decides to completely do it they can, and they need... But then is also called a culture change, culture shift. We need to convince the traditional fashion industry to adopt the technology, and also consumers to understand the problem. And they can drive the demand for this may to order.
EW (46:16):
Is your fashion career going to become your day job?
KY (46:19):
Definitely not completely fashion. It has to be fashion tech.
EW (46:24):
Yeah.
KY (46:24):
Without technology, I don't think fashion... Fashion. Yeah, is there for a long time and I don't think I need to do a pure fashion. But fashion tech has a lot of potential.
EW (46:41):
Do you worry about being pigeonholed in social media or in real life as a fashion person and not a quote "real engineer"?
KY (46:52):
Maybe the opposite. Perhaps I think in my earlier career, I might be pigeonholed as a scientist and someone who just do their research and do their experiments, but not creative enough. But I want to do both. I want to use both my technical skills and creative skills, and I'm integrating the two through everything I do now.
EW (47:28):
You have a shop where you do sell your fashions and paintings. Can you tell us the name of it?
KY (47:36):
Yeah. The brand is called Art by Physicist. So your is shop.kittyyeung.com. So basically if you just type Kitty Yeung, my name.com, it would pop up.
EW (47:51):
And of course that will be in the show notes.
KY (47:54):
Great.
EW (47:55):
You have dresses that light up, you have some dresses that don't, you have some dresses that are just... You send fabric and instructions. How do you decide whether something is a, do it yourself dress or one that you create fully?
KY (48:15):
Yeah. I am a proponent of open source, so I want to make fashion also part of the open source ecosystem. I want it to be as open as possible and modularize them. For creative people, they can get a piece of fabric with the patterns and the graphics already printed on the fabrics so they can sell themselves.
KY (48:41):
If it's a simple piece, I would do that and let creative people sow and do the... If they enjoy sowing, they can buy those fabrics. And for some more complicated ones, it's harder for people to do it by hand. So I would develop them into a full product where people can purchase, ready to wear.
KY (49:08):
So yeah, I try to make them as modular and open source as possible. All of the clothes are my own paintings. My hand painted graphics are printed on the fabrics, and then I would overlay the patterns on them. So they have the correctly out. So I'm really engineering clothing like you would design a piece of hardware, a chip say.
KY (49:38):
And that's actually what I used to do was designing components on the Silicon photonic chips. So there's a lot of similarity to me. I treat a piece of fabric, like is substrate and then I lay things on top of it. I print my paintings and then eventually for some designs that make sense to add the electronics I would add.
KY (50:02):
Say this starry night dress is a painting of the constellations and they make sense to add some LEDs. So it lights up nicely. And that creates it. I recently launched just a couple of days ago.
EW (50:16):
Yeah.
KY (50:17):
[inaudible 00:50:17]. Yeah. Thanks. This new dress is inspired by astronomical images of earth in space. Where you can see sunrise and the moon going around earth, those beautiful NASA images. You can use easily find online. I'm always drawn into this beautiful space, starry nights and nature.
KY (50:44):
So I wanted to design a dress that represents that. So it has a piece of LED matrix panel inside the dress. This is a collaboration between my brand and Lumen Couture, which is my friend Chelsea Klukas's brand. We put this together using the LEDs to allow you to actually draw and upload any videos, images or gifts.
KY (51:16):
And then I simulated this moon going around the earth on the dress. You can see city lights on the earth area and also see sunrise gradually lighting up the earth. So I think the effect is quite nice. So I'm very happy about this new release.
EW (51:40):
And that one is a ready to wear, isn't it?
KY (51:44):
Yes. This one is a ready to wear.
EW (51:47):
And it has an LED panel.
KY (51:49):
Mm-hmm (affirmative).
EW (51:51):
Does it... I guess it's just removable for washing or how does... Okay.
KY (51:56):
Yeah. You have to design things based on the hardware and the electronic steps available. There is a industry that's developing more wearable electronics is still being developed is not quite mature there. There are companies that are making flexible electronics, you have washable electronics, flexible washable batteries.
KY (52:26):
There is a quite nice industry that's working on those. But they're not still not quite ready for the complete integration with fabrics. So this I think is a very interesting research area.
EW (52:41):
How do you decide whether to manufacture these yourself or just put them up online for other people to make?
KY (52:53):
I actually make all of them open source. A lot of these that you see that are already ready to wear, a couple of years ago, they are just open source projects. I would first make them myself by hand and then I would write tutorials to teach people how to make something similar.
KY (53:13):
So on websites like Hackster.io, Hackaday.io, Instructables, you can find my projects. For anyone who's maker and interested in building something similar, they can find all the components that's needed, the construction, instructions and the code that you can download.
KY (53:34):
And even 3D models, sometimes I use 3D printing for accessories and designs. So people can download that and make them themselves. And then converting them into actual products is a whole set of work. And I am intrigued by the whole process, and I really like seeing things come to fruition, come to life as a product that maybe people other than makers want to have.
KY (54:08):
And that can also inspire people, what's possible in the industry. So my designs are three collections, nature, science and future. Nature are all the paintings of beauty for places I've been and thought the flowers and fish, all these nice sceneries that I really love. So I'd go somewhere and I see them, I will paint them.
KY (54:38):
Then I would turn them into designs. People can find those. And then I have the science ones that are astronomy, science. I have a Schrödinger's cat earring. So some of these have electronics that you call people can buy, or they can find those DIY instructions to build some themselves.
KY (55:04):
And the future one, are the ones that are really elaborately, futuristic. So they are not... The manufacturers are not ready to make them because a lot of these are hands on. I had to touch each piece by hand and then sow them together, and soldered the LEDs piece by piece and programmed them.
KY (55:26):
So those are the ones that are really made for makers that they can look at the free tutorials if they want to build something similar, they can do that. So they're called future. I hope that in the future, the industry would... The manufacturers would look at those creative designs, then they can support creative designers to make them into products.
EW (55:50):
I am just... I would be blown away by either your quantum computing career or your fashion career. And it is just...
KY (56:00):
Thank you.
EW (56:00):
... it's so much more that you're doing both.
CW (56:03):
I'm just looking forward to quantum fashion. I don't know what that is.
KY (56:06):
Ah, yes. It is possible. I do have one, I mentioned earlier that Schrödinger's cat earring, is 3D designed. One side is of that cat, the skeleton, the other side is...
CW (56:22):
Okay. I can see that. That's cool.
KY (56:24):
Yeah. So also, I think the point here is all made to order. Like 3D printed accessories, they're so wonderful that you don't have any inventory, you don't have any waste. You produce them when your customer orders it online. I think clothing has to go that way.
EW (56:44):
Let's see. One more question. Do you have a book coming out?
KY (56:49):
I have my comics, the quantum computing comics that I'm putting together like a little book is also a notebook so people can order it from Amazon, very very soon. I should probably launch it on my website and also tell people about it through Hackaday. Then people can order the book with all the comics, so every page has a little comic.
KY (57:15):
They can learn something, on the other side is empty. They can write notes on. People should watch and stay tuned on the Hackaday Quantum Computing with Comics, through Comics project. I would announce some exciting new releases.
CW (57:34):
Cool.
EW (57:35):
Cool. Kitty, do you have any thoughts you'd like to leave us with?
KY (57:39):
Thank you guys so much for inviting to speak on your podcast. This is a very nice platform.
EW (57:48):
It has been great talking with you. It's nice to meet you.
KY (57:52):
Thank you so much.
EW (57:54):
Our guest has been Dr. Kitty Yeung. Senior program manager at Microsoft quantum systems, producer of MS Learn quantum modules, creator of the comic series, Quantum Computing through Comics soon to be a book. Lecturer at Hackaday and Microsoft Reactor, founder and designer of sustainable and steam fashion brand, Art by Physicist. And creative technologist and lead of the fashion hack at Microsoft.
EW (58:25):
Kitty has created a 10% discount code for Embedded FM listeners. You can use [Contact us for the code] on www.kittyyeung.com for any order over $50, one per customer.
CW (58:39):
Thanks Kitty. This was absolutely fascinating.
KY (58:42):
Thank you so much.
EW (58:43):
Thank you too Christopher for producing and co-hosting. Thank you to Helen and Sophi for recommending Kitty, and thank you for listening. You can always contact us. It's show at embedded.fm or at the contact link on embedded.fm. Remember if you heard something but you're not quite sure what it was, you can now get a transcript.
EW (59:05):
And a quote to leave you with. This comes from the amorphous internet. Don't compare your inside to someone else's outside.
New Speaker (59:18):
Embedded is an independently produced radio show that focuses on the many aspects of engineering. It is a production of Logical Elegance, an Embedded software consulting company in California.
EW (59:30):
If there are advertisements in the show, we did not put them there and do not receive money from them. At this time, our sponsors are Logical Elegance and listeners like you.