Quantum computing with Chad Rigetti

It was a very interesting conversation. Is that like a really nice you can say yes. I didn't think you're crazy, but I had just moved to San Francisco into Silicon Valley from New York City, and that is not a conversation you can have in New York City without people thinking you're crazy. Probably.

But I'm an open person, and I, you know, I like to learn, and so I was very interested in this hypothesis. It was an amazing conversation, and it was very fun.

Alright. Well, I hope the company works, and I hope the simulation does not shut down. Great. Thank you. That will help. Alright. So Chad is going to talk to us about Bregetti. Thank you for coming, Chad.

Awesome. Thank you so much, Sam.

Alright. I'm incredibly excited to be here today and to talk with you guys. I'm also incredibly honored. So thank you very much Sam and Kat and YC for having me giving me the opportunity to talk with you guys. So this as Sam mentioned, when we joined Y Combinator in summer twenty fourteen, we had nothing. We had not built a single qubit, the fundamental like building block of a quantum computer.

We did not know how we were going to build qubits. I knew what they needed to look like and I knew what the fundamental requirements were. In fact, I'd been working in the field for already about ten or twelve years in quantum computing. And this is a five qubit quantum computer that we have built at Rigetti Computing.

It's less than two years later, and we're about 35 people in a warehouse in Berkeley, about 20 some PhDs, and we're building quantum computers. And we're in a race to define this technology for the next twenty, thirty, forty years. And it's incredibly fun. It is the kind of thing that gets you up in the morning and is worth spending your life on.

Humans have been building tools and technology to store and process information for millennia. I like to think of the sundial as the original computer. It takes an input and it tells does something useful with it and tells you the time.

From the sundial to the abacus and then things like the Babbage Difference Engine, which you can go see at the Computer History Museum, it's amazing and you should do it, to punch cards. Those are all systems based on Newtonian mechanics. And every time our understanding of nature evolves and develops further, we add a deeper level of understanding, our technology progresses as well.

So many great companies were born of this first transition that I'm talking about on the slide. IBM started as a computing tabulated and recording company. They made punch cards and time clocks. They were kind of born out of this first transition into the microchip era and they blossomed and evolved and survived through this time to grow into a very, very large company.

Other companies that drove that first transition, who was it? Fairchild? Intel? And then what's been born in the era of the microchip? Well, almost everything we see around us has driven the global economy for the past fifty or sixty years. That's incredible. The amount of leverage you can get from a computing technology is massive. And you know what?

We've known since 1905 that beneath there is Newton's laws on one hand and then beneath that there is kind of Maxwell's equations. And we've known since 1905 that there is a more fundamental description of nature and that's quantum mechanics.

At Rigetti Computing, we're driving this next transition from microchips to the systems based on individual atoms or artificial atoms that we build in in in the lab. And that that's a very exciting opportunity for for us. So why is it worth doing this? This sounds incredibly hard. Why is it worth trying to build quantum computers in the first place?

Well, the kind of problems that these machines will solve are incredibly impactful. They fall into two broad categories. We think of them in in kind of two broad categories. On the one hand, you have a class of applications that we think of as quantum chemistry.

So what you're doing in this case is using the quantum mechanical the quantum computer as a tool to investigate other quantum mechanical systems. It turns out that that's almost everything in science, medicine, material science. This is stuff that's going to lead to better drugs, better materials, better nuclear reactors, highly impactful technology. Why are we doing this?

Because if you can you you build a quantum computer, you can do simulation driven design of new catalysts, catalysts to capture carbon or nitrogen from the atmosphere. It can help solve global warming. This is an incredible, incredibly broad technology. The other bucket of applications is machine learning and artificial intelligence.

So in this case, what you do is learn to embed a learning problem on a classically intractable physical model that you can simulate on a quantum computer. That's a mouthful. What it means is quantum computers are going to lead to fundamentally more powerful forms of artificial intelligence. So when I say more powerful, what do I mean? Does anyone recognize this? It's on the slide.

So this is Tianhei two. This is until about three months ago was the most powerful computer on the planet. It cost about $400,000,000. It burns about 20 megawatts of electricity. Do you guys know how much electricity that is? It's enough to it's enough to power about it's enough to power the town I grew up in, about 20,000 households. It's about half the size of a football field.

It's based on 3,200,000 Intel cores. So there's two problems with this. Ultimately, our approach to building large scale computers is starting to break, and there's two problems. The first is that Moore's law is ending. That's been happening for a long time. Lateral transistor scaling, the fundamental measure of Moore's law, has of leveled off for the past eight years.

The other thing is something that I hope you've all heard about in your computer science class is called Amdahl's law. Amdahl's law talks about the limiting benefits or the diminishing returns of parallelization. These are massively parallel machines, 3,200,000 cores running in parallel. Only problems that can be parallelized run fast on these kinds of machines. There's a fundamentally better way.

Now, President Obama has shown some significant vision in sort of driving a return of American leadership in high performance computing, and he has said that America is going to build an exascale computer, something about 30 times more powerful than Tianhei two by 2020. That machine will cost about a billion dollars with current technology, and it would require a nuclear power plant to run it.

We're going to do it, and we need to, but there's another path. Ultimately, when you can compute with quantum physics, you have a faster and cheaper path to that level of computing power. How is that possible? Well, these are two developmental systems in our lab in Berkeley. These are what you see in the big white cans are cooling systems. Every high performance computer has a cooling system.

These ones are very powerful. These run at low temperature. Inside each of those cooling systems is a single chip. When this picture was taken, we had a five qubit processor in that machine. A single chip with about 60 or 70 qubits on it would be more powerful than that entire half a football field size machine. That's what quantum computing unlocks.

So this is a true hard tech startup, and one of the challenges that hard tech companies, I'll talk about this more in a moment, brings is this challenge of operating in an arena that is not well defined, that does not have a well developed supply chain. You know what you want to do, but the capabilities to do it do not exist or not commercially or easily accessible.

We've had to develop all of the building blocks, the entire supply chain for this technology. What does that mean for us? We have developed new simulation driven design methods to actually design these quantum chips. We've had to develop our own fab, our own microfabrication capability. We've developed advanced electronics that allow you to control these chips.

You can think of a quantum computer something like a nuclear reactor where you have the core where the reaction's happening that generates all the power, But then there's this really complex traditional engineering system around it that stabilizes it and extracts the computational capability. And that thing is very expensive and it requires very advanced control electronics.

And then ultimately, we serve access to these machines over the cloud. And so we have to have cloud software and applications. And that's a lot of work. There's a lot of different things you've got to tie together in one organization to do this. This slide is frankly a synthesis of the past fifteen years of my life. I've been working on this problem my entire adult life.

I was a junior in college in Saskatchewan, Canada. And really? That's amazing. Where are you all from? Oh, wow. Moose Jaw here. Moose Jaw. I was I was a junior at the University of Regina in Saskatchewan, Canada and a physics major.

I was incredibly frustrated. I was very, very frustrated because I didn't understand two basic things that I thought every human on the planet should understand. What's quantum physics and how do computers actually work? How do they actually store process represent information? About the same time, I read about a field called quantum computing. I like to synthesize things.

I thought this was amazing. There's one field that I can learn instead of having to learn two? This makes life so much easier. I've been working on that ever since, and that was in 02/2001. I heard about these people at Yale University that had an idea for building quantum computers. You can build these things out of real individual atoms or ions.

That's really hard because individual atoms or ions are extremely tiny and very, very hard to control. They said, why don't we build these things out of special electrical circuits based on superconductors that have no dissipation and build them in such a manner that they mimic real atoms, build an artificial atom out of an electrical circuit. I was like, that's amazing.

That's such a great idea because what's going to happen is you're going be able to leverage all of traditional semiconductor manufacturing capabilities. You're going be able to build a scalable chip technology someday based on those superconducting qubits. I spent about seven years with that group at Yale. I was a PhD student, a postdoc.

I spent about three years in doing further research at IBM in quantum computing. And in 2013, I started Rigetti Computing to develop quantum integrated circuits. And that's what we've done. So this is the jump on my second slide.

This is the leap from Newtonian plus Maxwell's equations to Newtonian plus Maxwell's equations plus Schrodinger's equations quantum physics, And ultimately, I want to offer you a working definition. If there's any physics majors in audience, I want to give you a working definition of a quantum computer. Quantum computers store and process information in individual photons. That's it.

Your iPhone, the iPhone seven, uses about a hundred billion photons per bit processed. It may be as much as 10 to the 17 and a hundred billion photons per bit transmitted. This is far more efficient technology. Okay. So I wanna talk for a moment about the distinction between a hard tech company and a tech company.

First of all, when I say hard tech, I don't mean it's harder, although it feels harder. What we mean is every company and look at the companies on this slide. These are incredible organizations, incredible incredible organizations, incredible companies, incredible products, incredible founders. These are all incredibly hard things. There's one distinction.

A hard tech company has to deal with in addition to all of the tech, execution, market risk, all the standard things, all the gauntlet that you have to steer your organization through to survive. Fundamental questions of possibility. You have to deal with that when you're a hard tech company. That is the signature of a hard tech organization.

Now, there's two things I want you to take away from this. The first is that, well, with all of that risk, we're saying it might not even be possible. Why the hell are you going to do that? Why the hell is anyone going to invest in your company if it might not be possible to even do it? Why is it worth it if you're not sure it's possible? Well, there's two things you get from my perspective.

The first is if and when you are successful, you create monumental leverage and defensibility. I think of the Manhattan Project as a canonical hard tech organization. Look at the fucking leverage they created. That's incredible. The Apollo missions.

When President Kennedy said in 1961, As a nation, we're going to put an American on the surface of the moon and return him safely to Earth by the close of this decade, That was an epochal moment for mankind. That's the kind of story that isn't written in quarterly reports and spreadsheets. That's written in hieroglyphs on cave walls. That's the kind of stuff that stirs the heart.

That's what you get when you do a hard tech company, and that is so powerful. Now I want you to notice something on this slide. Look at these amazing companies.

At some point, the defensibility and leverage that hard tech provides and the incredible passion that you engender by working on problems of that scope and impact leads organizations on the left to pushing into hard tech in order to access those things. Think of Uber moving into self driving cars. Think of Google with now a hundred seedlings hoping to turn something into a long term defensibility.

Microsoft built software and has started working on quantum computing. That's what you get with a hard tech company. Now there's also significant challenges, and I wanna talk about three of them for a moment. Team, communication, and integration.

So first of all, building an organisation that has world's experts in x, y, z, all of the things that you need to master as an organisation is incredibly hard. It comes with its own set of challenges. You're going to have to interface to the best scientists and engineers on the planet in those various fields. You're going to hire them.

You're going to have to bring them all into one company, and you're going to have to find a way to impedance match them, to allow them to talk to each other under the roof of one organization. And that leads into this integration challenge, integrating an organization that does all these disparate things. We have people on the team.

We have a Rhodes Scholar who's been doing research in quantum computing for ten years and is 27 years old. We have tenured physics faculty. We have someone teaching a course at Caltech who built the communication systems on the Mars rover missions.

We have an incredible organization, and one of the problems we've solved is that we have people who can all have a conversation together because they all have developed a shared language. That level of integration becomes a long term weapon for your organization. Huge amount of value can be created by it. Now communication. We're not doing this because quantum computing is interesting.

We're doing this to cure cancer and to solve global warming. How you talk about what you do as an organization is incredibly impactful. I encourage you to spend a lot of time thinking about it. I did this a few years ago, and I decided that our mission as an organization, when there were three people in the company, was we're on a mission to build the world's most powerful computer.

It gives you something to sink your teeth into. It's a little more tangible than photons. We did this exercise again in the past month with the team fully built out, well, partially built out at this stage, and we got to the same thing. It's really amazing. Why are we doing it? We're building the most powerful computers in the world to solve humanity's most important and pressing problems.

That's a rallying cry. That can be very impactful for your organization. Now the other thing you get with integration is the opportunity to create all this defensibility. So the chip, the quantum integrated circuit is one part of it. That gives you an intel kind of business for the quantum computing era.

We're not stopping at that because no one is competing at all these different levels today and we have an opportunity to build moats around the entire thing. The next layer up is to build the system, become master system integration. That's an IBM style business. And then ultimately, to own the software and platform, add in the Microsoft style business.

Ultimately, I want to go full stack and also include the Google style business of applications and designing new drugs to save people's lives. All right. So before I move on to this, I want you all to do something for me. I want you to do this one thing for me. I want you to take ten minutes today.

After this, at the break, when you go home today, during your meditation, whatever you want to do, I want you to take ten minutes and look in your heart, and I want you to ask yourself the question, what kind of company do I want to join or found? What kind of organization resonates with me?

And when you do that, spend that ten minutes, when you do that, some small fraction of you, it won't be many, some small fraction of you will say, you know what? I want to do the thing that stirs my heart. I want to do the thing that calls to me, that is worth spending your life on. One last thing.

So one of the special challenges that a hard tech organization faces is the capabilities to do what you need to do don't exist. If they existed, it wouldn't be a hard tech organization.

So there's this tension that exists in all companies but is especially accentuated in hard tech, Attention between developing the product, take your product from concept to market, get the product built, ship the product, with the things you need to do to enable that at each successive stage of evolution. Company development, build the capabilities and create organizational clarity.

That's your job as a founder and a leader. What should you work on? Well, I found that there's a useful framework. I thought about this problem for a really long time because I was spending every day trying to balance these two competing tensions. Ultimately, these are both processes of pumping entropy out of the system. You have an idea for the product.

I know what this quantum computer wants to look like. It's all but it doesn't exist. It doesn't exist yet. There's all these questions we have to answer. Think of when Elon started SpaceX. He had an idea for what this rocket was going to look like. There's a gazillion micro decisions that have to be made to actually manifest that thing in the real world.

That is a process of pumping entropy out of the vision. Same with company development, creating this organizational clarity, building the capabilities, answering the question, are we going to do our own fab? Are we going to outsource fab? Are we going to partner with IBM to do the fab? How are we going to do the fab? We have to answer that question.

Ultimately, that is a process of pumping entry out of the system. There's a lot of things that this leads you to. One is it tells you who you should hire. Some people create order and clarity in their wake. They create systems. They execute systems. They reinforce systems. They train other people how to use those systems.

Other people generate entropy. Know what you're looking for. Hire people who pump entropy out of your vision for your organization. It's incredibly powerful. So this is one of my favorite pictures I've ever seen. This is a picture of the Control Data Corporation six thousand six hundred machine. What I love about it is look at how kludgy it is. There's wires hanging out of this thing everywhere.

You can see the pumps down in the corner. This machine was the is widely considered the first supercomputer. The United States blocked the export of one of these things to our allies in France. It was incredibly impactful at a geopolitical level. And who built it? A group of 34 folks in the woods of Wisconsin. Thirty four people built the world's most powerful computer. I can't even read the memo.

It's too powerful. Ultimately, 34 people outcompete in a giant behemoth. That is what happens in high performance computing. That is what happens with a lot of hard tech organizations. And it's an incredible opportunity for you if this pulls at your heartstrings. Thank you very much.