June 11, 2026
WHEN: Today, Thursday, June 11
WHERE: CNBC's "Squawk on the Street"
Following is the unofficial transcript of a CNBC exclusive interview with Prometheus Co-Founders and Co-CEOs Jeff Bezos and Vik Bajaj on "Squawk on the Street" (M-F, 9AM-12PM ET) today, Thursday, June 11. Video clips are available on CNBC.com.
All references must be sourced to CNBC.
DAVID FABER: Prometheus is a startup co-founded by Jeff Bezos and Vik Bajaj. It is raising its Series B round to $12 billion and it does value the company now at roughly $41 billion. That's new news. The company has been largely quiet until now. Its ambitions, though, are broad, using AI to accelerate engineering across the physical economy, from chips to jet engines to batteries, solar manufacturing. Joining us now on CNBC exclusive is Prometheus Co-Founders and co-CEOs Jeff Bezos and Vik Bajaj. Guys, thanks for having us here.
JEFF BEZOS: Good morning, David.
FABER: Good morning to you as well. Jeff, let me just start with you. You know, we say physical AI I just read that. I don't know how many people even understand what your ambitions are. So, briefly explain sort of what Prometheus is trying to do.
BEZOS: Well, it should back up and think about, you know, draw the box really big around all of civilization. What drives the wealth of nations? What drives civilizational wealth? And the answer is invention. It's what really is driving it. Six thousand years ago, somebody invented the plow and we all got wealthier. Much later, somebody invented the steam engine and we all got wealthier. These things drive productivity. It's true that somebody invented the solar cell and it's continued to get better and better and better. We all got wealthier. And so, what, you know, our goal at Prometheus, what we're working on is building a set of tools that accelerate that invention loop. So, how long does it take to improve something? How long does it take to – from idea to actually manufacturing, seeing it rate and have a useful object? And so, that's really what's going on. And this is an age-old dream, the idea that you might build a set of tools that could actually do engineering, an artificial engineer. An artificial general engineer it's a dream that we've had is that people have thought about for decades, but it's never really been possible. But now it is. And that's what we've been working on since late 2024.
FABER: Right.
BEZOS: It's very exciting. We have a team of about 150 people. They've already done remarkable work. You know, it's hard work. We're grinding, but it's also very interesting.
FABER: Well, Vik, Jeff mentions things have changed. So, put in perspective what has. Obviously, we all know the introduction of ChatGPT a number of years ago and what we're seeing and reporting on every day. But specifically, the applications you're looking for, what has changed that allows you to pursue them in the way you are?
VIK BAJAJ: Well, let's discuss those applications for a minute, because what we would like to do is serve the needs of engineers who are kind of unsung heroes. You know, they build the entire world around us. Everything you see outside this window, the ships, the civil engineering structures --
FABER: Not software engineers in this case?
BAJAJ: Not software engineers only. They have a role. But all of that must come together. All of the things on which our lives really depend. Some of the most complex systems, they take many, many thousands of people a decade to make them. Like consider a jet engine. What it takes to make something so complicated takes teams of engineers just to come up with the design, just coming up with that design is one of the most technically sophisticated and creative acts that humankind accomplishes. And then when they come up with that design, they have to prove does that design work, which usually involves years of building prototypes. And then finally, to manufacture something, it's very complicated, many hundreds of thousands of processes. So, what has changed in the last few years is the ability to formulate even something as complicated as that from design to manufacturing as an end-to-end A.I. problem. The result will be what Jeff called the artificial general engineer. But it's really a set of tools that will give those engineers the ability to turn their dreams into reality much, much more quickly than is possible.
FABER: Right. So, truncating the amount of time, obviously, that's currently exists. I mean, we had solar panels on the White House back in –
BAJAJ: That's right.
FABER: Back in the mid to late 70s with Jimmy Carter.
BEZOS: Yes, Carter put solar panels on –
FABER: 40 years, 50 years later, we've advanced a lot.
BEZOS: Yeah.
FABER: But I'm just trying to understand if you are successful, what that would look like in terms of even something where we think we've had a lot of advancement, solar for example.
BEZOS: If you think about anything, you know, Vik brought up the example of a jet engine. What if you could instead of a team of a thousand people working for 10 plus years to build a next generation of jet engine, what if they could do that in five years or two years or one year and then extrapolate that through all kinds of technologies? You know, we build these incredibly sophisticated microprocessors and GPUs today with these exotic techniques, ultraviolet lithography and so on, and these exquisite tools that make these chips. You know, there's a company called ASML that makes a lot of these tools, and these are incredibly complex tools. What if ASML could use the kinds of tools that Prometheus is developing so that their next generation of tools could come faster? It's about accelerating that loop. So, the kind of dream build loop. Somebody thinks of an idea and they want to go to the next level of technology, whatever it is. If you're talking about lithography, maybe it's helium beams or something like this, but there's some next idea. And then you need to do – to actually build that thing. If you want to do it faster, you need to be able to simulate all of the physics and all of the things that would even down the manufacturing processes inside a computer. And that's very difficult to do, but it's possible.
FABER: I would assume so, but are you – what gives you the confidence that it is possible? What signs of progress, conceivably can you already point to it, Prometheus, Jeff, that, you know, that account for the fact of bringing in all this capital to pursue this?
BEZOS: Yeah, we've already done internally certain benchmarks where we can do things, some of these simulations, much faster than you would do with traditional techniques. It's a little premature to talk too much about what the team has accomplished so far, but it's really quite remarkable. And, you know, again, this team is just so impressive and, you know, the work they're doing is as challenging as it is, it's also really important work and it's intellectually interesting and of great value.
FABER: Right. And, you know, Vik, what do you think is going to distinguish Prometheus and give – and bring success? I say that because I can think of simulations, the likes of a Tesla, for example, and what they can do conceivably also to try to truncate the manufacturing process for automobiles. It's not as though others aren't pursuing similar things and using the compute that is now available to do it.
BAJAJ: Well, so first of all, the kinds of tasks that we're talking about that an artificial general engineer can accomplish, they're not things that human beings do today through words alone. You don't build a bridge or a jet engine through words, even the words that relate to mathematics. It's about shapes, assemblies, and to understand how something like that works inside the object, you have to understand the physics, which is very complicated, three-dimensional forces and fields and how they change over time. So, all of that has required us to develop new approaches to those kinds of AI problems, and we've made a lot of progress there. The other thing that distinguishes us, and this is really fundamental, Jeff mentioned it also, is the incredible team that we've assembled to work on this idea, which includes some of the most mission-oriented AI researchers and engineers in the world, but because we're engaged in the physical economy, also includes people who build things, who would use these tools, who teach us what are the most important problems and how can the solutions be judged.
FABER: Right. You know, Jeff, we spent a lot of time, of course, talking about Codex from OpenAI, Claude Code, Mythos, the incredible power and the exponential that we're in right now in terms of the power of these models. What gives you the confidence that at some point one of these large LLMs is not going to be able to conceivably come up with the similar approach that you're talking about, given they do seem to be, I mean, we're already at recursive self-improvement to a certain extent, so it's hard to – you can imagine anything.
BEZOS: Yeah. Well, as Vik was just saying, part of what's going on is you can't do this engineering with simple manipulation alone. The current – what LLMs really do well today is knowledge work. This is why they're very good at coding, for example, very good at math and a bunch of things like that. But this is operating in a different level of detail. It's a little bit like if I said to you, you know, if I read a thousand books on how to be a gymnast, I still wouldn't be a good gymnast. And there are –
FABER: You look like you would be pretty good.
BEZOS: No, trust me –
FABER: On the rings right now with those, Jeff.
BEZOS: Thank you. Very bad – I'd be a very bad gymnast.
FABER: OK. Yeah.
BEZOS: And so this – there are different kinds of knowledge that you need and you need to train these models on the right kinds of data. And the LLMs, as impressive as they are and as useful as they are, and they've been trained on this giant corpus of humanities knowledge that was already preexisting on the internet. What we're doing is very different because we have to create our data sets. We have to create our data sets and access data sets that are very hard to access. And so, even the training data is completely different from what the LLMs that you're accustomed to have access to.
FABER: So, you feel like that gives you a moat at this point.
BEZOS: It's very differentiated because you just need – you need access to that kind of data to be able to build a model like this.
FABER: Right. Something else you need access to is compute, I would assume.
BEZOS: Yeah.
FABER: I don't know what percentage of the money I just talked about goes to that, but I would imagine a large part. Do you have enough compute?
BEZOS: We do have enough compute. We've acquired a lot of compute. It will be – we will actually be needing more too. And you're right. That is a big chunk of the funding we've raised. And one of the reasons we've had to raise a significant amount of funding is because this is a very compute – what we're doing is very compute intensive. And we need to, you know, create that data, the data set that we were just talking about. That's also a very expensive investment.
FABER: Right. So, capital raises you see going on for some time?
BEZOS: Well, we'll see what happens there. You know, we just concluded our Series B. And so we're really not, we're not thinking about Series C quite yet.
FABER: But this was obviously outside capital. You contributed much of the first round of capital, correct?
BEZOS: Yeah. Yes, I was – I did, but I also participated in the Series B as well.
FABER: Right. Is Amazon, you know, I think about compute and AWS. What is the relationship, if any, between this company and Amazon, both on leasing compute, but also on sort of the real-world possibilities, given I can imagine a company like Amazon, for example, would also benefit from some of the technology that you're discussing?
BEZOS: Well, absolutely. You know, anybody with – setting up data centers is a kind of manufacturing process. And it's easy to imagine Amazon or any hyperscaler using the kinds of tools that Prometheus builds to improve their data centers. So, that's certainly a possibility. At the same time, of course, you know, it's easy to imagine Prometheus being a customer of AWS on the compute side.
FABER: Right, but is it at arm's length? I mean, I know you're a separate independent company –
BEZOS: Yeah.
FABER: – but there may be assumptions that, well, you'd be very tied into Amazon for obvious reasons.
BEZOS: Well, we – and it would be arm's length. And we actually have compute from a multitude of sources. So, we need to. Right now, compute is scarce enough that you get it where you can.
FABER: You get it where you can. Yeah.
BEZOS: Yeah.
BAJAJ: Including AWS.
FABER: Right. All right, you guys are co-CEOs. You know, how do you divide responsibilities?
BEZOS: We don't really divide responsibilities. So, we're talking to each other multiple times a day. And, you know, we're actually – we're both involved in the, you know, all of the decisions really. It's not like you say, OK, you handle this half of the company and I'll handle this half.
FABER: Right.
BEZOS: We're tight at the hip. We're both jacks of all trades.
FABER: You are. So, you're doing --
BEZOS: Which you need to be at this stage of a company.
FABER: Well, you were never a co-CEO at Amazon. You were always the CEO.
BEZOS: No, but I was a jack of all trades.
FABER: Why the decision to take the CEO role again, Jeff? Your first, since obviously resigning as CEO at Amazon, I think five years ago.
BEZOS: Well, I started out in late 24 with Vik as an investor in Prometheus, and so I was a founding investor, and as I saw what we were doing, and as I was like, I became so impressed by what was happening, and the potential, that I decided I couldn't sit on the sidelines, and I needed to jump in with both feet. So here I am, and it is a grind, but it's a good grind. It's type two fun, you know, it's that fun where after you finish climbing the mountain, you're like, oh boy, that was fun climbing the mountain.
FABER: Feel good.
BEZOS: Yeah.
FABER: Right. So, are you spending most of your time I mean –
BEZOS: Prometheus is the bulk of my time. I'm also spending a lot of time on Blue. I'm spending a lot of time on AI at Amazon. So the common thread in my time spent is mostly AI.
FABER: Right. And it's working, okay, Vik?
BAJAJ: Oh yes.
FABER: I mean, you know –
BAJAJ: Yes. Of course, I love working with Jeff –
BEZOS: I could leave for a minute if you want, if I want to get –
FABER: If I want to get the truth?
BEZOS: A candid answer.
BAJAJ: Yes. No. As Jeff mentioned, it's something that we have both been thinking about for a long time from different perspectives. And you know, one thing that we really share – everyone in the company – is Jeff's devotion to obsession with the customer, which in our form, our variant of that, requires us to really understand end to end who are these engineers that we serve, what are their problems, what are their aspirations, their dreams, how do they work, what do they want to accomplish, how to make their lives better.
FABER: Right.
BEZOS: To unleash their imagination.
BAJAJ: Yes.
BEZOS: So these engine – you know, for Prometheus, the engineer is the customer.
FABER: Yeah.
BEZOS: And so, how do we make their life better in every way? How do we give them tools that unleash their imagination? Right now, if you imagine something, everybody has this experience. You are, you know, sitting down to dinner, and you're having a conversations. I wish there was something that could do this or that. We all are inventors in our own way. Those ideas 99.9% of the time never leave somebody's head because they're too hard to do. And so, if you can –
FABER: Do you imagine a world in which that would not be the case?
BEZOS: Yes.
FABER: How far away are we from that? I mean, this sounds as though it's quite early.
BEZOS: It's hard – yeah, it's hard to say, and you're right, it's early. We have many miles to go. You know, there's so much hard work ahead of us at Prometheus. We're at the very early stages, even though we've made a lot of progress. There's still so much to – you have to remember that the surface area of this problem that we're talking about is gigantic, so you know, if you think of the manufacturing processes, you know, there are hundreds of kinds of welding, there's, you know, there's stamping and forging and casting and 3D printing and CNC milling and lithography, and so on, and so on, and so on.
FABER: Yeah. There's endless applications –
BEZOS: Literally thousands of kinds of manufacturing processes.
FABER: Do you have to focus on a handful of them, though Jeff, or can you actually broaden your own ambition?
BEZOS: You can prioritize to some degree, but you would be surprised any complex object, if you look at your iPhone, how many of those processes are used in that supply chain.
BAJAJ: So, in your iPhone, for example, there are processes like casting that actually even date from the Bronze Age all the way to things that we've invented in the last few years. So, to make any object, as Jeff was saying, you need thousands of these manufacturing processes to come together.
FABER: But you mentioned the jet engine, for example, the 10 years. I mean, is there an idea that at some point, if you guys are successful, that process could be brought down to as little as a year? I don't know. I'm just –
BAJAJ: Absolutely.
BEZOS: Yes.
FABER: You think so?
BAJAJ: Yes. And imagine how much that would change the world. The world has become a lot smaller due to five, six generations of jet engines, each more efficient than the last. How much progress could we have made if that generational time was measured in months instead of a decade.
FABER: Right, Jeff. We're in a – I don't want to say perhaps a fraught moment. I mean, there's a lot of negative view of AI overall, a lot of it concerning job losses.
BEZOS: Yeah.
FABER: When I listen to you and the productivity gains that conceivably could come about as a result of success, I do wonder, do we lose jobs as a result of this, given you're going to be taking the manufacturing process and sort of doing it in a very different way?
BEZOS: No, I know there's a lot of concern in general about AI and job loss. I have a very different view. I think that what's – I think, what's actually going to happen is we're going to have labor scarcity as a result. People are going to have to work hard –
FABER: You said that with Andrew a few weeks ago when you talked to him –
BEZOS: Yeah and I really believe that.
FABER: Why do you believe that?
BEZOS: I know why people are pessimistic. They're pessimistic because a bunch of smart people are telling them to be pessimistic. But those people are wrong. This is going to be –when you have productivity and this could be very significant productivity in the economy – and that is going to raise the standard of living, so that a lot of people who, for example, today have two earner households, perhaps one of those earners will decide not to be in the job market, so they will become a one earner household. Maybe some people who are working overtime will stop working overtime because they don't want to work overtime. So there is going to be – when you have that much productivity in the economy, that is the basket of goods that people can afford on less money goes very –
FABER: And you think the rewards will be shared in that way? I don't want to get into the wealth discussion you've already had that, so –
BEZOS: No, of course this is – if they take you back to the plow, they can't help but be shared that way. These inventions drive fundamental progress, you know. Somebody invents penicillin, and it does help everyone. Somebody invents, you know, solar cells, and it does help everyone. Some – and so on. You know, the iPhone doesn't get reserved for just a few people, that's not how it works. It's the inventions themselves that spread throughout society and improve life.
FABER: And you share this optimism?
BAJAJ: I do. I do. This is really important, right? What creates jobs? Companies occasionally create jobs, but what really creates jobs is invention. Inventions are based on dreams, but invention means that you actually make the dream a reality. The more that we invent new objects, new industries, all the examples –
FABER: The proliferation of engineers everywhere –
BAJAJ: Yes.
FABER: Because conceivably my dreams can now come true.
BAJAJ: Absolutely.
FABER: I mean –
BAJAJ: Yes, we will create more –
FABER: Because we're not going to have workers in manufacturing plants, that's already being automated, isn't it? I mean –
BAJAJ: A lot of it is automated already, but we will have more engineers, we will have more jobs in engineering and manufacturing as a result of inventing more.
FABER: As a result of inventing more. I'm always –
BEZOS: Unleashing imagination.
FABER: How many years? When are we going to be sitting here and I'm going to be talking about, you know –
BEZOS: Well, it's going to happen – it will happen piece by piece, so there won't be anything that happens suddenly. It won't be, you know, a moment. But you will see very significant change, progress in, you know, in a kind of 10 year time frame for sure.
FABER: Back to Prometheus, the company, for – there's been some reporting on it, and again, I think this is the first opportunity you've had to actually discuss it. There's this idea that you're also going to be buying companies to benefit from the use of your technology for those companies. Is that the case and if so, is it part of Prometheus? Is it a separate vehicle that will do that investing, Jeff?
BEZOS: We – yes, we may buy parts of companies and so on who could benefit from this technology, and then help them improve their processes, their manufacturing process, or what have you. It's premature to say too much about that, that, you know, that plan is still in work.
FABER: Okay, but sort of what a private equity approach, in the sense of having a portfolio of companies that you're then deploying the technology for and increasing the value of?
BEZOS: I'm not sure I would frame it that way, but it is – it's just a little premature to talk about.
FABER: Okay. Vik, when I hear you guys talking, I do wonder about AutoCAD, you know, for example. I mean, just computer-aided design, is this the death of that if you succeed?
BAJAJ: No. it's not going to be the death of that. There are products today, big ones, airplanes, jet engines, where CAD systems are the system of record. At the same time, for decades, engineers have worked with tools that dissent for drafting, and for the next generation of invention, there are probably better ways to design things, better ways to interact with designs, better ways to predict whether the designs work in a computer, and better ways to make designs from the beginning that are buildable, that are manufacturable. And that requires us to reimagine that process end to end.
FABER: Right. You know, so you, I mean, you're obviously – you're identifying and creating data sets that don't exist –
BAJAJ: Yes.
FABER: You've got to come up with an interface, I guess, ultimately, that engineers are going to be able to use, you, I mean, you guys have a lot of work ahead of you, right?
BAJAJ: Yes. Oh, yes, yes.
FABER: So, again, I come back to signposts. You know, when you're not a public company, we don't have to hold you accountable. But I am curious, as I hope we do, we sit down in some period of time again, what will I be asking you about, or what will you be able to say? Hey, David, look what we're able to do now. What would be a manifestation of success?
BEZOS: Well, we will have early product rollouts. It's too early to lay out a timetable for that, so you'll just have to stay tuned. But you will see products roll out.
FABER: And in terms of the time line of Prometheus, and you know what I would imagine would be the continued need for capital, no time soon, given you're just closing a $12 billion round. Is there a day that you go public?
BEZOS: You know, I guess it's just too early to think about that. We've got a lot of work ahead of us, and right now, we're just heads down doing the work.
FABER: How many people do you think you ultimately will need to do that work? You have 100 – you said 150 now.
BEZOS: 150 now.
FABER: Does that continue to grow over time?
BEZOS: It'll continue to grow.
FABER: It will.
BEZOS: Yeah.
FABER: Any ambition or idea of how large the company might be?
BEZOS: No, I don't think – it'll be more – that's more of an output, you know. We have certain needs on the data side, on the engineering side, on the research side, and so you know we'll keep growing the company as we kind – that's something we'll kind of evolve into.
BAJAJ: And small groups of people today can accomplish really large tasks, right –
FABER: Yeah.
BAJAJ: – in this space. So we have 150 people in here in London and Zurich, and those teams continue to grow.
FABER: Does this become a capital gain, so to speak, though Jeff, where you just got to continue to have more capital before you can obviously get to anything approaching cash flow positive?
BEZOS: There's certainly – there's a lot of investment required in a company, and what we're doing, because you do have to build these big datasets, which is expensive, and you do have to do a lot of compute, which is expensive. So this is a capital-intensive start-up. There's no question about that.
FABER: Right. What's your approach to that? I notice you had the presence of very well-known institutional investors amongst the investing group here. Is that the road you would continue to go down in terms of trying to raise capital in the future?
BEZOS: Well, I think we'd always been looking for investors who are interested in manufacturing and improving the manufacturing world, and who can help in that regard?
FABER: Right. I guess from an investment perspective, Vik, I'm always trying to think, well, who will be disintermediated? Who will be benefited over time 5, 10 years from now? Will the drug industry be able to create more things, or do more things? Jeff mentioned lithography. Will ASML be able to create things more quickly that will then enable more chip manufacturing. I don't know. Puts in some perspective for our viewers, if you're successful, what that will mean for the corporate landscape that we talk about all the time on CNBC.
BAJAJ: So one thing is that innovation and change is constant. We're going to increase the pace of that innovation and change, but we are one small company operating in a physical economy, which amounts to 60% of the world's GDP. It's very large, it's $70 trillion the entire physical economy. And so the way our tools will be deployed throughout that, how things will change, you know, that's a story that will be told over the next decade.
FABER: Yeah.
BAJAJ: And we're at the very early stages.
BEZOS: And we need to be very humble about this. This is very early. We're working very hard. This is not a done deal. We've raised money, we have a brilliant team, we have tremendous work ahead of us.
FABER: Right.
BEZOS: So, you know, just –
FABER: But you did choose to communicate a bit today.
BEZOS: Yeah.
FABER: And I am curious as to why.
BEZOS: Well, because the story is kind of leaking out, and so we decided we would, you know, we heard, for example, that people thought we were building robots and doing world models and things like this, which isn't correct. And so there's been some speculation. We thought, look, we're not being secretive –
FABER: Right.
BEZOS: – we're just being heads down and trying to do the work. But there's a certain amount, when you raise this much money, people do get curious. If you'd let that just be a complete void, they'll fill it with nonsense. So we figured we'd at least say what we're actually working on.
FABER: Well, I'm happy you've obviously done that. As you said, a $41 billion private company at this point. You know, guys, in the brief time we have left, just, you know, you are both so positive on the future for AI, and I do want to come back to this moment we're in, where, you know, not a data center in my backyard, I'm going to lose my job, this technology is moving way more quickly than I can. Why – and then you mentioned and you didn't say names, but you know, Dario Mode is out with another piece today. I don't know if you guys have seen it, you probably haven't, talking about the need really for government to get more involved, I think, is fair to say in terms of policymakers, increased openness to action, in terms of at least providing safeguards or something around it. How do you view that?
BEZOS: Well, look, government regulation has a lot of reasonable purposes. I mean, you know, I'm glad when – I don't know if your viewers can see that bridge over there, but probably there were certain engineering standards that are written into the rules of municipalities and states –
FABER: There it is. A nice view of it, yes.
BEZOS: – and so on, that make sure that that bridge is built to a standard where it's unlikely to fall down, and I think we all like that. So there are certain regulations in the world that are, you know, you get on an airplane that's – and you feel comfortable, you take a drug that's been through a certain FDA process to make sure it's not toxic. There are – there's a lot to be said for healthy government regulation to improve safety and products, and so on. And I don't see why, you know, that won't be applied at some point to the kinds of new tools that are being built by AI. But you want to – if you do, when you do that, you have to do – you want to regulate the application level. You don't want to accidentally outlaw the knife, because it can be used in a bad way, right? Knives are important tools, and yes, every once in a while they get misused by someone. But you don't say the solution to that isn't to say, okay, no more data centers, right? No more knives. That's not a smart approach to regulation. So, and by the way, on this data center thing, there will be many municipalities who say we don't want data centers in our neighborhood. That's okay, because there will be many areas that will say yes.
FABER: And then, of course, there is the possibility they'll be in space. I know you believe that will be the case.
BEZOS: Yeah. They will.
FABER: You discussed that a lot with Andrew. I did, Jeff, because we haven't heard from you since the new Glenn Rocket explosion.
BEZOS: Yeah.
FABER: And I am just curious if there's a brief update here in terms of, I think the NASA administrator, Jared Isaacman, on Monday told CNBC it could take some serious time to restore the launch pad. Any updates you can give us?
BEZOS: Yeah, we, you know, it was very difficult to vet, very bad day for Blue Origin, very tough on the whole team. We've rallied, we're rebuilding the launch site, we got lucky in a bunch of ways. The longest lead items at the launch site were undamaged by the event, so that's just a good piece of luck. And we'll be flying again before the end of this year.
FABER: Okay, and you're going to be keeping an eye at all on that other IPO that may be happening tomorrow?
BEZOS: Well, I'll be watching along with the rest of you.
FABER: Yeah, well, we look forward to future updates on Prometheus as well. And, guys, I just want to thank you for having us here as well.
BEZOS: Thank you, David.
BAJAJ: Thank you for joining us.
FABER: Very, very happy to have been here. Vik Bajaj, Jeff Bezos, right here from HQ for Prometheus. Let me send out over back to you, Carl.
