Why silicon could scale

3:26:28100,000 cubit trapped ion machine, you're going to have to invent a 100,000 laser optical miracle. >> Yeah. All right. Um, but if you want a million superconducting cubits, you're going to have to build a warehouse style sized cryostat. >> Boo. >> But if you want a million spin cubits, you just put it on a standard 300 mm silicon wafer. You run it through the exact same photoiththography machines at TSMC, ASML, Intel um that made the processor in your iPhone and there you'll have it. >> Mhm. >> Right. Scaling is the key. >> Yeah. >> And scaling is the future. >> Yeah. >> Um yeah,

3:27:08>> HRL is not the only one that is pursuing this stuff. So I want to give a shout out to some of the um other players in the space. Intel had a really amazing talk after Thaddius's talk at the APS March meeting that showed um like uniformity in a lot of their fab. I mean they're really good at fab right? Um and they could make their chips along with like 16 metal layers of backend >> which is kind of crazy. And the robot they had a road map to like scale up to larger cubits. So there's already like scaling to larger numbers of cubits coming in from Intel. >> And then of course there is DRock. >> Yes. um which is where I am at right now. This is an Australian startup that is trying to make millions of spin cubits on a single silicon chip. Um it's

3:27:52it's a great place to work to be honest and DAC also publishes in nature on the regular. So on the next on the on the next slide we've got just a few of the ones that came out in the last 2 years. Um spin cubit control with um a millichelvin CMOS chip. So they're getting into the cryosimos type of stuff. um they've got really high fidelity. They're getting into that and they've got high fidelity spin cubid operation and initialization above one Kelvin. So they're trying to do things without going even into the millichelvin stage. It's an open problem, right? Like do you even need um you could do LD cubits lost even cubits but the energy

3:28:33split is big enough that even at 1 Kelvin the temperature is lower than that energy split. So spin cubits are really making a resurgence I think and um I think you know you don't have to invent a supply chain is the point. >> Yeah. Yeah. >> The supply chain already exists. We're piggybacking off of 60 years of Moore's law >> y >> and trillions of dollars of cos and silicon manufacturing infrastructure. >> Um there's a reason why your laptop is a miracle of engineering and yet it's still actually kind of cheap. >> Yeah. to if you think about it like people who build computers they're do they have to do the same drastic like

3:29:13the people who are who are at Apple and like Dell and they have the same level of like crazy specific knowledge right but they're making laptops on the chief because they can scale right >> 100% >> and the point is that when you're manufacturing that first wafer that's going to get you that first silicon quantum computer at scale that is fault tolerant and all all that other stuff. That first wafer is going to be hella expensive. >> Yeah. >> Okay. And it's still not there yet. >> Yep. >> Um >> but once you get that one wafer >> But once you get that one wafer, the second wafer it's going to be a joke. >> The the the path of acceleration is going to be so much faster if you can do it on a silicon wafer. >> Yeah. >> Because we already it's already all

3:29:54there, which is I I I can't overstate that as a part of this. >> Yeah. Um, it's part of the reason why the acceleration of AI has been so quick because Nvidia has already been building GPUs which were the substrate that's really good for a lot of these transformer algorith matrix multiplication and so imagine that we did not have GPUs at the level that Nvidia was today. >> Good point, >> right? We would not have seen the acceleration of AI that quickly and it wouldn't have been that big a deal. But they already it's it's global. >> It's already been they have the distribution partners all. Anyway, you get the idea. So that's that's the that's how I make the connection here as someone coming from more of the technology and like operational context

3:30:38in the real world. It's like as soon as you cross that Rubicon um again there's going to be the battle at the chip makers with their other business lines for time >> but >> good point. you know, a quantum chip is gonna it's going to be hard to Yeah. argue Yeah. why that shouldn't be at the front of the line. >> Exactly. And I mean, there's a So, IBM has its own like chipm facilities, which is I think one of the reasons why it probably acquired HRL. It also probably I'm not going to speak for IBM, but maybe I am a little in saying that they may see the writing on the wall when it comes to superconducting cubits. I mean there was you know at APS actually I

3:31:19should mention that um Northrup Grumman had a talk where they showed um they used the sort of same trick that these guys are using with exchange only where they had superconducting cubits but you could rig them up >> to create cubits where there were singlet triplets >> made out of transmons >> but now I can only I only have to communicate with them using DC. >> Now that's all fine but it's still not in silicon right and it's still massive still big. So you still have that scaling problem even though maybe you don't have the wiring problem anymore. There's still an advantage in using silicon. Um and because silicon is just the the bread and butter of our economy,

3:31:59right? It is the best. Um so finally we do have our FFP audit that we are going to um