1 00:00:15,356 --> 00:00:33,876 Speaker 1: Pushkin. I'm Jacob Goldstein, and this is What's Your Problem, 2 00:00:34,156 --> 00:00:37,996 Speaker 1: a show about people using technology to solve problems that matter. 3 00:00:38,676 --> 00:00:42,116 Speaker 1: My guest today is Ben Bloom. He's the co founder 4 00:00:42,116 --> 00:00:45,756 Speaker 1: and CEO of a company called Atom Computing, and his 5 00:00:45,876 --> 00:00:50,796 Speaker 1: problem is this, how do you build a useful quantum computer? 6 00:00:51,476 --> 00:00:54,516 Speaker 1: If Ben succeeds, or if one of the other companies 7 00:00:54,556 --> 00:00:59,116 Speaker 1: working on quantum computers succeeds, quantum computers could make profound 8 00:00:59,116 --> 00:01:03,676 Speaker 1: improvements in everything from discovering new medicines to building cheaper 9 00:01:03,716 --> 00:01:07,516 Speaker 1: ways to store energy. Quantum computing today kind of reminds 10 00:01:07,556 --> 00:01:11,156 Speaker 1: me of where AI was, say, ten or fifteen years ago. 11 00:01:11,356 --> 00:01:15,836 Speaker 1: Huge possibility, lots of people working on it. Still not mainstream, 12 00:01:16,276 --> 00:01:18,716 Speaker 1: but it's worth talking about now for a few reasons. 13 00:01:19,436 --> 00:01:23,316 Speaker 1: For one thing, if or when quantum computers do work, 14 00:01:23,476 --> 00:01:27,476 Speaker 1: they will be an extremely big deal. The science is 15 00:01:27,516 --> 00:01:30,436 Speaker 1: clear that they can solve problems that are just too 16 00:01:30,556 --> 00:01:35,156 Speaker 1: complex for traditional computers or even AI to ever solve. 17 00:01:35,756 --> 00:01:39,996 Speaker 1: There are the potential energy and medical breakthroughs I mentioned before. Also, 18 00:01:40,236 --> 00:01:44,076 Speaker 1: quantum computers can crack a common, widely used form of encryption. 19 00:01:44,956 --> 00:01:48,396 Speaker 1: At the moment, giant tech companies like Google and IBM 20 00:01:48,476 --> 00:01:51,516 Speaker 1: and Amazon are spending billions of dollars on their own 21 00:01:51,636 --> 00:01:57,356 Speaker 1: quantum computing projects. Several smaller companies, including Ben Bloom's Atom Computing, 22 00:01:57,716 --> 00:02:01,236 Speaker 1: have had money pour in from venture capitalists and public markets, 23 00:02:01,876 --> 00:02:04,956 Speaker 1: and the Chinese government is spending billions more on its 24 00:02:04,956 --> 00:02:08,396 Speaker 1: own quantum computing project. A lot of money and a 25 00:02:08,396 --> 00:02:10,876 Speaker 1: lot of smart peace people and a high stakes outcome 26 00:02:10,916 --> 00:02:14,476 Speaker 1: if it works. That's why quantum computing is worth talking about. Now, 27 00:02:15,076 --> 00:02:17,356 Speaker 1: before we get to the interview, here's the basic idea 28 00:02:17,356 --> 00:02:20,516 Speaker 1: of how a quantum computer is different than a traditional computer, 29 00:02:20,676 --> 00:02:24,236 Speaker 1: a classical computer. In a classical computer, as you probably know, 30 00:02:24,716 --> 00:02:28,516 Speaker 1: the basic unit of information is a bit. A bit 31 00:02:28,556 --> 00:02:29,996 Speaker 1: can only be one of two. 32 00:02:29,836 --> 00:02:36,236 Speaker 2: Things, zero or one off or on. Amazingly, everything that 33 00:02:36,276 --> 00:02:39,276 Speaker 2: computers do is just built on lots and lots and 34 00:02:39,356 --> 00:02:42,036 Speaker 2: lots of zeros in ones. And you can do a 35 00:02:42,076 --> 00:02:45,196 Speaker 2: lot with zeros and ones. But you cannot do everything. 36 00:02:45,956 --> 00:02:49,996 Speaker 2: For one thing, you can't crack standard methods of online encryption. 37 00:02:50,676 --> 00:02:54,836 Speaker 2: For another, you can't build a complete model of even 38 00:02:54,876 --> 00:02:58,156 Speaker 2: a simple molecule, say the kind of molecule you would 39 00:02:58,276 --> 00:03:01,476 Speaker 2: use as a drug. This is where quantum computers come 40 00:03:01,516 --> 00:03:04,716 Speaker 2: in quantum computers are not built out of bits, out 41 00:03:04,716 --> 00:03:07,156 Speaker 2: of zeros and ones. They're built out of what are 42 00:03:07,196 --> 00:03:12,356 Speaker 2: called cubitsum bits. To build a quantum bit, you use 43 00:03:12,436 --> 00:03:13,436 Speaker 2: a quantum particle. 44 00:03:14,076 --> 00:03:14,236 Speaker 3: Then. 45 00:03:14,276 --> 00:03:18,316 Speaker 1: Bloom's company is called Atom Computing because they build each 46 00:03:18,396 --> 00:03:21,636 Speaker 1: cubit with a single atom, and when the quantum computer 47 00:03:21,756 --> 00:03:25,076 Speaker 1: is working, each atom, each cubit is not limited to 48 00:03:25,156 --> 00:03:27,556 Speaker 1: being in a single state, to being just a one 49 00:03:27,676 --> 00:03:32,116 Speaker 1: or zero in a weird quantumy way, a single cubit 50 00:03:32,356 --> 00:03:35,916 Speaker 1: can be in many different states at once. And on 51 00:03:35,956 --> 00:03:39,076 Speaker 1: top of that, when you combine cubits, what happens to 52 00:03:39,116 --> 00:03:42,996 Speaker 1: each one instantly affects the others. What this means in 53 00:03:43,076 --> 00:03:46,916 Speaker 1: practice is that a quantum computer with enough cubits could 54 00:03:46,956 --> 00:03:51,716 Speaker 1: solve some problems that the most powerful classical computers literally 55 00:03:51,796 --> 00:03:56,316 Speaker 1: could not solve in a million years. But quantum computers 56 00:03:56,316 --> 00:03:58,956 Speaker 1: today are too small to do that, or at least 57 00:03:59,076 --> 00:04:02,276 Speaker 1: they can't do it for any practical worldly problems. They 58 00:04:02,316 --> 00:04:05,316 Speaker 1: just don't have enough cubits, and as Ben and I 59 00:04:05,356 --> 00:04:08,996 Speaker 1: discuss in our conversation, building a function in quantum computer 60 00:04:09,196 --> 00:04:11,596 Speaker 1: with lots of cubas is in fact a very hard 61 00:04:11,676 --> 00:04:15,076 Speaker 1: engineering problem. So to start, I asked Ben to tell 62 00:04:15,116 --> 00:04:17,116 Speaker 1: me how the field of quantum computing will look in 63 00:04:17,156 --> 00:04:20,876 Speaker 1: a few years, when, if things go well, those engineering 64 00:04:20,916 --> 00:04:22,596 Speaker 1: problems will have been solved. 65 00:04:23,436 --> 00:04:27,636 Speaker 3: So I think in five years what you'll see is 66 00:04:28,596 --> 00:04:34,956 Speaker 3: quantum computers attacking problems for national labs, for defense, for 67 00:04:35,036 --> 00:04:38,556 Speaker 3: all these kind of esoteric industries who could call them 68 00:04:39,716 --> 00:04:44,076 Speaker 3: that want calculations done that cannot be done on classical computers. 69 00:04:44,436 --> 00:04:47,676 Speaker 3: It's probably going to be something like materials simulations. So 70 00:04:47,796 --> 00:04:49,836 Speaker 3: how electrons behave in materials? 71 00:04:49,996 --> 00:04:53,956 Speaker 4: And why are national labs interested in that? Ooh? 72 00:04:54,276 --> 00:04:57,636 Speaker 3: I think that's a funny question. I think the Department 73 00:04:57,636 --> 00:05:03,076 Speaker 3: of Energy is really interested in understanding materials at their extremes. 74 00:05:03,116 --> 00:05:03,276 Speaker 4: OK. 75 00:05:04,036 --> 00:05:07,796 Speaker 3: And I think that's true to both make it more 76 00:05:07,796 --> 00:05:11,596 Speaker 3: efficient for the USA government to deal with all of 77 00:05:11,596 --> 00:05:15,396 Speaker 3: the equipment they have, and also really true I mean, 78 00:05:15,516 --> 00:05:18,596 Speaker 3: obviously for the Department of Energy main mission, which is 79 00:05:19,076 --> 00:05:21,996 Speaker 3: understanding nuclear weapons and doing that without having to test 80 00:05:22,076 --> 00:05:22,876 Speaker 3: nuclear weapons. 81 00:05:23,436 --> 00:05:27,316 Speaker 1: So five years from now, quantum computers are where classical 82 00:05:27,356 --> 00:05:31,276 Speaker 1: computers were in the nineteen forties, right, A few giant, 83 00:05:31,396 --> 00:05:35,276 Speaker 1: crazy expensive ones being used by the government or a 84 00:05:35,276 --> 00:05:38,356 Speaker 1: couple governments. Two things people talk a lot about with 85 00:05:38,436 --> 00:05:43,756 Speaker 1: quantum computing are drug discovery, discovery of new drugs, and energy. 86 00:05:43,796 --> 00:05:46,396 Speaker 1: For some reason, people talk about energy, they talk about batteries, 87 00:05:46,476 --> 00:05:49,076 Speaker 1: that kind of thing. So if things go relatively well 88 00:05:49,076 --> 00:05:51,316 Speaker 1: in quantum computing, like, are we going to be seeing 89 00:05:51,876 --> 00:05:54,796 Speaker 1: meaningful impacts on those fields and what in ten years 90 00:05:54,836 --> 00:05:57,116 Speaker 1: and if so, how will they be different? 91 00:05:58,036 --> 00:05:59,636 Speaker 3: Yeah? I do think we will. I mean, I think 92 00:05:59,676 --> 00:06:02,156 Speaker 3: ten fifteen years we will see new drugs on the 93 00:06:02,196 --> 00:06:05,556 Speaker 3: market that we're designed on a quantic computer. I think 94 00:06:05,596 --> 00:06:08,916 Speaker 3: we will see batteries they can do more recharge cycles 95 00:06:09,116 --> 00:06:12,556 Speaker 3: because we understand the materials and understand the various properties 96 00:06:12,596 --> 00:06:16,636 Speaker 3: that you know, cause them to lose charge over recharge cycles, and. 97 00:06:16,916 --> 00:06:20,836 Speaker 1: More recharge cycles means cheaper in the long run importantly, right, 98 00:06:20,916 --> 00:06:23,116 Speaker 1: Like batteries are constrained by cost now, and if one 99 00:06:23,156 --> 00:06:27,076 Speaker 1: battery can last longer, that effectively means you it's cheaper 100 00:06:27,116 --> 00:06:27,756 Speaker 1: per cycle. 101 00:06:28,476 --> 00:06:28,676 Speaker 4: Yeah. 102 00:06:28,716 --> 00:06:30,396 Speaker 3: And I think another example of this is, you know, 103 00:06:30,476 --> 00:06:33,316 Speaker 3: the one that people throw out a lot is kind 104 00:06:33,316 --> 00:06:37,596 Speaker 3: of understanding, you know, how you actually do fertilizer production. Like, 105 00:06:37,636 --> 00:06:40,116 Speaker 3: it turns out a few percent of the world's energy 106 00:06:40,276 --> 00:06:42,836 Speaker 3: is spent on fertilizer production. And so if you can 107 00:06:42,876 --> 00:06:47,116 Speaker 3: find a new catalyst that could do that same process 108 00:06:47,356 --> 00:06:51,676 Speaker 3: with slightly lower temperature or slightly less pressure, you know, 109 00:06:52,396 --> 00:06:58,076 Speaker 3: marginal savings in that process turn into gigantic global savings 110 00:06:58,156 --> 00:07:00,716 Speaker 3: in an energy budget sense. And so all of these 111 00:07:00,756 --> 00:07:03,396 Speaker 3: problems kind of have this general idea behind them, which 112 00:07:03,436 --> 00:07:07,636 Speaker 3: is that chemicals and materials and understanding the physical processes 113 00:07:07,676 --> 00:07:09,796 Speaker 3: which we kind of have built our old on top 114 00:07:09,836 --> 00:07:13,556 Speaker 3: of understanding them to a point where you could engineer 115 00:07:13,596 --> 00:07:16,996 Speaker 3: around them or engineer them to work better, could have 116 00:07:17,156 --> 00:07:19,116 Speaker 3: these you know, giant lever arm effects. 117 00:07:19,356 --> 00:07:23,036 Speaker 1: So it's basically, I mean a more and better drugs 118 00:07:23,076 --> 00:07:27,076 Speaker 1: and then be just efficiency gains. So that's fewer emissions, 119 00:07:27,116 --> 00:07:30,996 Speaker 1: more power, lower costs. Like those are the dreams broadly. 120 00:07:31,076 --> 00:07:35,836 Speaker 4: Yeah, okay, so where are we today? 121 00:07:36,556 --> 00:07:40,916 Speaker 3: Yeah, we're building toy systems. I mean, there's no question 122 00:07:41,156 --> 00:07:44,396 Speaker 3: I think that over the past I would say two years, 123 00:07:45,236 --> 00:07:47,436 Speaker 3: a lot of technologies, including the one I work on, 124 00:07:47,476 --> 00:07:50,116 Speaker 3: neutral atoms, have kind of crossed a threshold where you 125 00:07:50,156 --> 00:07:54,676 Speaker 3: can build better and better cubits by taking that quantum information, 126 00:07:55,276 --> 00:07:58,556 Speaker 3: spreading it around and doing error correction. And one of 127 00:07:58,556 --> 00:08:01,756 Speaker 3: the examples that you know is probably what some sense 128 00:08:01,796 --> 00:08:04,276 Speaker 3: started this entire race is it turns out you can 129 00:08:04,356 --> 00:08:07,196 Speaker 3: factor numbers on a quantum computer efficiently. 130 00:08:06,836 --> 00:08:10,596 Speaker 1: Which sounds trivial to the initiated, but it turns out, 131 00:08:10,636 --> 00:08:13,356 Speaker 1: among other things, if I have this right to allow 132 00:08:13,396 --> 00:08:16,516 Speaker 1: you to crack most of the encryption on the Internet, 133 00:08:16,556 --> 00:08:17,916 Speaker 1: true or not true, It's true. 134 00:08:18,036 --> 00:08:21,356 Speaker 3: The kind of encryption we have now was was a choice, 135 00:08:21,516 --> 00:08:23,716 Speaker 3: and in some sense right now it's even a choice 136 00:08:23,756 --> 00:08:27,676 Speaker 3: in your browser or in your operating system. And the 137 00:08:27,876 --> 00:08:31,236 Speaker 3: likes of you know, Apple or you know, the Linux 138 00:08:31,236 --> 00:08:35,596 Speaker 3: maintainers or Microsoft, they can literally just you know, quote 139 00:08:35,636 --> 00:08:38,036 Speaker 3: unquote flip a switch and it can switch to what 140 00:08:38,076 --> 00:08:39,876 Speaker 3: they call is post quantum cryptography. 141 00:08:39,956 --> 00:08:42,556 Speaker 1: So people have come up with new systems that are 142 00:08:42,716 --> 00:08:47,076 Speaker 1: quantum resistant that can work to secure our data in 143 00:08:47,116 --> 00:08:48,156 Speaker 1: the post quantum world. 144 00:08:48,676 --> 00:08:51,076 Speaker 3: Exactly. Yeah, and so I think that the future is 145 00:08:51,116 --> 00:08:53,476 Speaker 3: bright in that sense. Now. The funny thing that you know, 146 00:08:53,756 --> 00:08:56,556 Speaker 3: governments around the world are a little probably freaked out 147 00:08:56,556 --> 00:09:00,516 Speaker 3: about is the past, which is that we've been using 148 00:09:00,876 --> 00:09:05,276 Speaker 3: for you know, decades upon decades, we've been transmitting information 149 00:09:05,396 --> 00:09:09,556 Speaker 3: between you know, people and businesses and government enter prizes 150 00:09:09,596 --> 00:09:13,596 Speaker 3: and stuff like that. That if someone stored it and 151 00:09:13,716 --> 00:09:16,436 Speaker 3: waited until they had a quantum computer. They can just 152 00:09:16,516 --> 00:09:19,316 Speaker 3: go and read in the future when quantic computers are available. 153 00:09:19,596 --> 00:09:22,276 Speaker 3: And so I think that is the kind of issue 154 00:09:22,276 --> 00:09:24,676 Speaker 3: that I think most people think of when they think, oh, 155 00:09:24,756 --> 00:09:26,836 Speaker 3: they're going to break encryption. How bad is that going 156 00:09:26,876 --> 00:09:28,676 Speaker 3: to be. It's not going to be, you know, five 157 00:09:28,756 --> 00:09:30,596 Speaker 3: years from now that people are worried about how do 158 00:09:30,596 --> 00:09:33,076 Speaker 3: you pay for something online? It's more going to be 159 00:09:33,156 --> 00:09:36,996 Speaker 3: these kind of you know, big government issues of Okay, 160 00:09:37,036 --> 00:09:39,196 Speaker 3: you know, twenty years ago we sent a cable to 161 00:09:39,276 --> 00:09:40,396 Speaker 3: so and so and it said this. 162 00:09:41,516 --> 00:09:44,636 Speaker 1: I mean, we can let's talk about geopolitics here. Now, 163 00:09:44,636 --> 00:09:46,676 Speaker 1: when people say let's talk about geopolitics in the US, 164 00:09:46,756 --> 00:09:50,236 Speaker 1: they basically mean let's talk about China, and specifically, I. 165 00:09:50,196 --> 00:09:52,036 Speaker 4: Mean, what happens if China gets there first? 166 00:09:52,196 --> 00:09:54,196 Speaker 1: Right? Like, I do feel like, I know that's a 167 00:09:54,236 --> 00:09:56,076 Speaker 1: crude way to ask the question, but I also know 168 00:09:56,156 --> 00:09:58,396 Speaker 1: China is putting a lot of money into quantum computing, 169 00:09:58,556 --> 00:10:01,236 Speaker 1: right Like? Is there something of a race here? Is 170 00:10:01,276 --> 00:10:02,396 Speaker 1: that a way to think about it? 171 00:10:03,156 --> 00:10:04,876 Speaker 3: I think it is a race. I mean, I think 172 00:10:04,916 --> 00:10:08,076 Speaker 3: that they're doing it differently than the US. I mean, 173 00:10:08,076 --> 00:10:10,556 Speaker 3: at the US. You know, my company out in Computing 174 00:10:10,636 --> 00:10:13,636 Speaker 3: is one of many companies in the United States who 175 00:10:13,636 --> 00:10:16,676 Speaker 3: are pursuing quantic computing, are trying to build a quantic computer. 176 00:10:18,156 --> 00:10:20,116 Speaker 3: I think it's all private. You know, there is some 177 00:10:20,236 --> 00:10:23,756 Speaker 3: public funding which we're accessing. There's Darper programs and things 178 00:10:23,796 --> 00:10:27,276 Speaker 3: like that, but it's mostly private funding. Whereas you talk 179 00:10:27,316 --> 00:10:29,636 Speaker 3: about what's going on in China, and I think there 180 00:10:29,676 --> 00:10:33,796 Speaker 3: are big governmental initiatives, and I also think there are 181 00:10:33,916 --> 00:10:36,796 Speaker 3: in some sense state backed companies that exist. 182 00:10:36,836 --> 00:10:40,516 Speaker 1: This is very much in keeping with both of our countries, right, 183 00:10:40,836 --> 00:10:42,156 Speaker 1: exactly what you would expect. 184 00:10:42,316 --> 00:10:44,876 Speaker 4: Perhaps it's a test of our various systems. 185 00:10:45,316 --> 00:10:47,556 Speaker 3: Yeah, yeah, So, I mean I think that the question 186 00:10:47,676 --> 00:10:50,996 Speaker 3: of you know, is it bad if China, you know, 187 00:10:51,036 --> 00:10:53,916 Speaker 3: builds a quantum computer and we don't have one, I mean, potentially, 188 00:10:53,996 --> 00:10:56,116 Speaker 3: I mean, I think that a lot of the advances 189 00:10:56,156 --> 00:11:00,156 Speaker 3: we were talking about earlier. Yeah, there are performance gains, 190 00:11:00,156 --> 00:11:02,556 Speaker 3: efficiency gains and things like that, but those are the 191 00:11:02,676 --> 00:11:04,836 Speaker 3: kinds of things that really I would say, drive an 192 00:11:04,836 --> 00:11:08,716 Speaker 3: economy in the sense where the numbers associated with them 193 00:11:08,796 --> 00:11:12,236 Speaker 3: are so so large that it's hard for me to 194 00:11:12,236 --> 00:11:14,596 Speaker 3: wrap my head around. Like if you can decrease the 195 00:11:14,716 --> 00:11:19,356 Speaker 3: energy budget of your country by five percent. Uh, that's 196 00:11:19,356 --> 00:11:21,956 Speaker 3: a huge number, and I think it can actually make 197 00:11:22,116 --> 00:11:23,396 Speaker 3: big changes possible. 198 00:11:23,796 --> 00:11:25,596 Speaker 4: Yeah. I mean in a way, it makes you much richer. 199 00:11:25,836 --> 00:11:28,236 Speaker 1: Right, it allows you to do things you could otherwise 200 00:11:28,276 --> 00:11:30,596 Speaker 1: not afford to do, or you wouldn't otherwise have the 201 00:11:30,636 --> 00:11:36,916 Speaker 1: resources to do. Y. I mean, presumably it gives you 202 00:11:36,996 --> 00:11:39,636 Speaker 1: some kind of cryptographic power. 203 00:11:40,356 --> 00:11:42,116 Speaker 3: Well, I mean it goes back to this idea that 204 00:11:42,156 --> 00:11:47,556 Speaker 3: there's you know, there's this store now, decrypt later philosophy, 205 00:11:47,556 --> 00:11:50,876 Speaker 3: which I've heard, you know, espoused by various government officials 206 00:11:50,876 --> 00:11:53,436 Speaker 3: as you know, others are doing this and so on 207 00:11:53,516 --> 00:11:55,636 Speaker 3: and so forth, which is that they're you know, storing 208 00:11:55,676 --> 00:11:58,996 Speaker 3: all the communications and things like that. I think that 209 00:11:59,156 --> 00:12:01,556 Speaker 3: is a problem. There's no question if if you know, 210 00:12:01,596 --> 00:12:04,676 Speaker 3: we're successful and we build quantic computers, you will be 211 00:12:04,716 --> 00:12:08,116 Speaker 3: able to decrypt later. I guess the question is how 212 00:12:08,276 --> 00:12:11,356 Speaker 3: useful is old information? That would be the problem, And 213 00:12:11,396 --> 00:12:14,716 Speaker 3: the question is how how bad is that going to be? 214 00:12:14,756 --> 00:12:17,316 Speaker 3: Maybe it's not so so bad on individual scale, but 215 00:12:17,436 --> 00:12:20,756 Speaker 3: on a kind of company scale or a country scale, 216 00:12:20,756 --> 00:12:22,716 Speaker 3: maybe it could be quite quite problematic. 217 00:12:23,436 --> 00:12:26,396 Speaker 1: So let's talk a little more about the difference between 218 00:12:26,476 --> 00:12:30,996 Speaker 1: quantum computers and regular computers, classical computers. And maybe one 219 00:12:31,036 --> 00:12:33,356 Speaker 1: way to do that is to talk about classical computers, 220 00:12:33,356 --> 00:12:35,556 Speaker 1: the kind of computers we have now, the kind of 221 00:12:35,556 --> 00:12:39,596 Speaker 1: computers that underpin AI are bad at, like what is 222 00:12:39,636 --> 00:12:41,876 Speaker 1: their meaningful limitation in this context. 223 00:12:42,276 --> 00:12:45,636 Speaker 3: So, say you have an electron and you want to 224 00:12:45,876 --> 00:12:48,996 Speaker 3: understand the properties of that electron. And because you're designing 225 00:12:48,996 --> 00:12:50,996 Speaker 3: a drug, you're you're looking at a material, You're doing 226 00:12:51,036 --> 00:12:52,356 Speaker 3: something like that. 227 00:12:52,716 --> 00:12:55,556 Speaker 1: A particular electron on a particular molecule. 228 00:12:55,636 --> 00:12:58,276 Speaker 3: Yah, yeah, yeah, yeah, And all you want your classical 229 00:12:58,316 --> 00:13:01,716 Speaker 3: computer to do is write down the state of that electron, 230 00:13:01,876 --> 00:13:05,036 Speaker 3: very very precisely, where is it and what is it doing, 231 00:13:05,756 --> 00:13:09,356 Speaker 3: and it's spin and things like that. Yeah yeah, Now wow. 232 00:13:09,396 --> 00:13:11,476 Speaker 3: You try to write that down, and it turns out 233 00:13:11,516 --> 00:13:14,076 Speaker 3: you use a lot of binary data. You use a 234 00:13:14,076 --> 00:13:16,716 Speaker 3: lot of classical data to do that. Now, if you 235 00:13:16,796 --> 00:13:20,956 Speaker 3: want two electrons, you have to use more classical data 236 00:13:21,036 --> 00:13:24,276 Speaker 3: describe it. But it turns out, and this is where 237 00:13:24,636 --> 00:13:28,116 Speaker 3: quantum mechanics starts mattering. It turns out you don't just 238 00:13:28,196 --> 00:13:31,476 Speaker 3: care about the individual electrons in their states. You actually 239 00:13:31,556 --> 00:13:34,436 Speaker 3: care about all the correlations, all the ways the two 240 00:13:34,476 --> 00:13:37,556 Speaker 3: electrons are interacting with each other and are linked together, 241 00:13:38,156 --> 00:13:41,036 Speaker 3: and that turns out to require more classical data to 242 00:13:41,076 --> 00:13:45,516 Speaker 3: write down and very very quickly with tens to less 243 00:13:45,516 --> 00:13:48,316 Speaker 3: than one hundred electrons. If you tried to write down 244 00:13:48,636 --> 00:13:52,116 Speaker 3: all the classical data you needed to describe that situation 245 00:13:53,436 --> 00:13:57,276 Speaker 3: you would need, I think it was more bits of 246 00:13:57,356 --> 00:14:00,716 Speaker 3: information than there are, like atoms in our universe. 247 00:14:01,116 --> 00:14:03,676 Speaker 1: It would be impossible. It would just be impossible for 248 00:14:03,716 --> 00:14:06,956 Speaker 1: a classical computer yourself. And so it is the case 249 00:14:06,996 --> 00:14:12,036 Speaker 1: that like once you get to the really fundamental level 250 00:14:12,196 --> 00:14:14,756 Speaker 1: of what's going on with energy or what's going on 251 00:14:14,836 --> 00:14:18,476 Speaker 1: with matter, with materials, it behaves in a quantum way, 252 00:14:19,116 --> 00:14:23,556 Speaker 1: and classical computers can't understand what's going on once you 253 00:14:23,596 --> 00:14:27,516 Speaker 1: get to that level, and quantum computers, at least the 254 00:14:27,516 --> 00:14:31,116 Speaker 1: theoretical quantum computer, if you could solve the engineering problems, 255 00:14:31,556 --> 00:14:32,196 Speaker 1: could do it. 256 00:14:32,836 --> 00:14:36,156 Speaker 3: Yeah exactly. I mean, I think that the cool thing 257 00:14:37,636 --> 00:14:40,876 Speaker 3: about quantum computing we kind of do have Norse stars. 258 00:14:41,236 --> 00:14:43,076 Speaker 3: We know that if you can build a quantic computer, 259 00:14:43,276 --> 00:14:46,916 Speaker 3: you can factor large numforts. We know that if you 260 00:14:46,956 --> 00:14:49,316 Speaker 3: can build a quantic computer that you know, can deal 261 00:14:49,356 --> 00:14:52,436 Speaker 3: with billions of operations that you can find the you know, 262 00:14:52,516 --> 00:14:55,476 Speaker 3: structure of some molecule or something like that. And so 263 00:14:55,556 --> 00:14:58,876 Speaker 3: we know that the goal is go from the short 264 00:14:58,916 --> 00:15:02,236 Speaker 3: little calculations you can do now to longer and longer 265 00:15:02,276 --> 00:15:04,796 Speaker 3: and longer calculations to the point where you can reach 266 00:15:05,076 --> 00:15:05,636 Speaker 3: these goals. 267 00:15:05,716 --> 00:15:09,356 Speaker 4: Yes, and so maybe there's one. 268 00:15:09,636 --> 00:15:16,876 Speaker 1: There's one sort of problem broadly stated that seems particularly 269 00:15:17,196 --> 00:15:19,076 Speaker 1: interesting and worth discussing. 270 00:15:21,476 --> 00:15:23,156 Speaker 4: Let me see if I have this right? Is it 271 00:15:23,276 --> 00:15:24,076 Speaker 4: right that. 272 00:15:26,036 --> 00:15:30,516 Speaker 1: Each bit, each cubit of a quantum computer needs to 273 00:15:30,596 --> 00:15:34,596 Speaker 1: be entirely isolated. It needs to be sort of not 274 00:15:34,916 --> 00:15:37,916 Speaker 1: in touch with anything in the world. No, not a photon, 275 00:15:38,116 --> 00:15:41,396 Speaker 1: not another molecule, not anything, right, because it is sort 276 00:15:41,436 --> 00:15:46,916 Speaker 1: of sitting in this what a quantum superposition I'm reaching here, 277 00:15:47,636 --> 00:15:50,516 Speaker 1: and if anything, if anybody sees it, if any light 278 00:15:50,596 --> 00:15:52,676 Speaker 1: photon hits it, if anything happens to it, it kind 279 00:15:52,676 --> 00:15:56,316 Speaker 1: of breaks, it decoheres and it doesn't work right? And 280 00:15:56,436 --> 00:16:00,676 Speaker 1: is it fair that it's extremely hard for maybe obvious reasons, 281 00:16:00,956 --> 00:16:03,636 Speaker 1: everything is touching everything else all the time. Is that 282 00:16:03,756 --> 00:16:06,996 Speaker 1: like a central problem? Is that a problem worth talking about? 283 00:16:07,356 --> 00:16:11,036 Speaker 3: It is because I think it's actually that the fundamental 284 00:16:11,116 --> 00:16:14,396 Speaker 3: challenge of building a quantum computer is having that isolation, 285 00:16:15,156 --> 00:16:18,556 Speaker 3: but then making sure that you have complete control over 286 00:16:18,636 --> 00:16:20,236 Speaker 3: that quantum system. 287 00:16:19,996 --> 00:16:22,116 Speaker 4: Right, And like, how could you have both at once? 288 00:16:22,196 --> 00:16:22,316 Speaker 3: Right? 289 00:16:22,316 --> 00:16:26,036 Speaker 1: If it's completely isolated, how can you control it? So, 290 00:16:26,716 --> 00:16:29,196 Speaker 1: I mean, let's talk a little bit about your approach. 291 00:16:30,276 --> 00:16:35,236 Speaker 1: You are working with Microsoft to build a thing for 292 00:16:36,916 --> 00:16:39,476 Speaker 1: the Novo NORDESK foundation and what is part of the 293 00:16:39,556 --> 00:16:40,596 Speaker 1: Danish government? 294 00:16:41,036 --> 00:16:45,956 Speaker 4: Yeah? Yeah, so what are you building for the Danes? Yeah? 295 00:16:45,996 --> 00:16:50,716 Speaker 3: So it's a twelve hundred cubit system, okay, And that 296 00:16:50,876 --> 00:16:52,836 Speaker 3: is a kind of our part of this, which is 297 00:16:52,836 --> 00:16:54,996 Speaker 3: that we're building the hardware. So it's a system that 298 00:16:55,156 --> 00:16:58,316 Speaker 3: has all of the classical control around it, all the 299 00:16:58,436 --> 00:17:01,356 Speaker 3: quantum control around it, so that they can trap, cool, 300 00:17:02,196 --> 00:17:05,116 Speaker 3: manipulate twelve hundred physical cubits. 301 00:17:04,716 --> 00:17:06,836 Speaker 4: Okay, and each one of those is one atom. 302 00:17:07,156 --> 00:17:08,556 Speaker 3: Yes, each one of those is one atom. 303 00:17:08,636 --> 00:17:10,716 Speaker 4: Yeah, very small number of atoms. 304 00:17:10,796 --> 00:17:13,076 Speaker 3: Yeah. And actually the quantum part of our system is 305 00:17:13,156 --> 00:17:16,036 Speaker 3: very very small, Like it's like half a millimeter by 306 00:17:16,116 --> 00:17:17,876 Speaker 3: half a millimeter. It's very very. 307 00:17:17,796 --> 00:17:19,996 Speaker 4: There's like a box or something. What is it? What 308 00:17:20,516 --> 00:17:20,756 Speaker 4: is it? 309 00:17:20,876 --> 00:17:22,716 Speaker 3: Yeah? Yeah, No, it is pretty much. 310 00:17:22,596 --> 00:17:26,076 Speaker 1: A box half a millimeter by half a millimeter, which 311 00:17:26,116 --> 00:17:29,436 Speaker 1: is I don't know what, like a size of like 312 00:17:29,476 --> 00:17:30,876 Speaker 1: a hair or something like. 313 00:17:30,916 --> 00:17:31,596 Speaker 4: It's so small. 314 00:17:31,596 --> 00:17:32,436 Speaker 3: It's a little bigger than it. 315 00:17:32,516 --> 00:17:34,356 Speaker 4: Okay, but yeah, what is it like? But it's bigger 316 00:17:34,396 --> 00:17:36,356 Speaker 4: than like a little fingernail trimming. 317 00:17:36,076 --> 00:17:37,716 Speaker 3: Right, yeah, fingernail trimming. 318 00:17:37,716 --> 00:17:40,996 Speaker 1: That's a good bigernail trimming. And that's where all of 319 00:17:41,036 --> 00:17:43,356 Speaker 1: the action is. That's the that's it. That's all of 320 00:17:43,356 --> 00:17:48,876 Speaker 1: your Yeah, I guess twelve hundred atoms. Yeah, And what's 321 00:17:48,916 --> 00:17:52,036 Speaker 1: going on in that tiny box? What do you start with? 322 00:17:52,916 --> 00:17:54,276 Speaker 1: It's a metal, right, what's the element? 323 00:17:54,956 --> 00:17:55,796 Speaker 3: Uh? Uturbium? 324 00:17:55,836 --> 00:17:57,956 Speaker 1: Okay, so you start with this element, just a thing 325 00:17:57,996 --> 00:18:00,596 Speaker 1: that exists in the world called U turbium. You don't 326 00:18:00,596 --> 00:18:01,436 Speaker 1: need very much of it. 327 00:18:01,476 --> 00:18:02,076 Speaker 4: What do you do? 328 00:18:03,596 --> 00:18:03,716 Speaker 1: So? 329 00:18:03,836 --> 00:18:05,676 Speaker 3: First off, we have to take we have a chunk 330 00:18:05,676 --> 00:18:07,956 Speaker 3: of it, so we have to heat it up. So 331 00:18:08,036 --> 00:18:11,116 Speaker 3: you go from a solid gas. That gas kind of 332 00:18:11,156 --> 00:18:14,956 Speaker 3: streams down our system. We have lots of lasers kind 333 00:18:14,996 --> 00:18:17,796 Speaker 3: of hit that gas so that it goes from hundreds 334 00:18:17,836 --> 00:18:21,276 Speaker 3: of kelvin down to about a microkelvin, so ten to 335 00:18:21,316 --> 00:18:24,436 Speaker 3: the minus six kelvin, so very very cold. 336 00:18:24,236 --> 00:18:27,676 Speaker 1: And zero zero degrees kelvin is absolute zero. It's as 337 00:18:27,676 --> 00:18:29,996 Speaker 1: cold as anything in the universe can ever be. So 338 00:18:30,036 --> 00:18:33,676 Speaker 1: you're making it very, very very cold. And is that 339 00:18:33,716 --> 00:18:35,676 Speaker 1: because you don't want it moving around, because you want 340 00:18:35,676 --> 00:18:36,316 Speaker 1: it isolated? 341 00:18:36,356 --> 00:18:39,636 Speaker 3: That's the exactly okay, yeah, pretty much like the temperature 342 00:18:39,716 --> 00:18:41,716 Speaker 3: is pretty much the velocity it goes at and things 343 00:18:41,756 --> 00:18:44,916 Speaker 3: like that. So we get the atoms, we get them 344 00:18:44,916 --> 00:18:48,036 Speaker 3: down to a microkelvin, and then we kind of shuttle 345 00:18:48,076 --> 00:18:50,156 Speaker 3: them using a laser. We kind of push them up 346 00:18:50,596 --> 00:18:53,996 Speaker 3: into that tiny little area that's half a millimeter by 347 00:18:53,996 --> 00:18:54,316 Speaker 3: half a. 348 00:18:54,236 --> 00:18:57,836 Speaker 4: Million little box that's computer sort of. 349 00:18:58,476 --> 00:18:59,836 Speaker 3: And then all of a sudden we get to this 350 00:18:59,876 --> 00:19:03,156 Speaker 3: little area. And what we do through that microscope objective 351 00:19:03,316 --> 00:19:05,396 Speaker 3: is we put a big beam into the back of 352 00:19:05,396 --> 00:19:08,036 Speaker 3: that microscope objective. And the reason why we put a 353 00:19:08,076 --> 00:19:11,756 Speaker 3: big beam when I say, it's like twenty millimeters yeah, okay, 354 00:19:11,756 --> 00:19:14,396 Speaker 3: So you're shooting light through the microscope lens, let's say 355 00:19:14,556 --> 00:19:18,436 Speaker 3: lens lens, okay, and when you do that, you put 356 00:19:18,436 --> 00:19:22,196 Speaker 3: a big light beam into the back of that lensky 357 00:19:22,236 --> 00:19:24,436 Speaker 3: What it does is it focuses down really really tight, 358 00:19:24,596 --> 00:19:27,236 Speaker 3: and it creates an optical tweezer. Okay, And this won 359 00:19:27,316 --> 00:19:30,876 Speaker 3: the Nobel Prize, and I think it was like twenty 360 00:19:30,996 --> 00:19:34,196 Speaker 3: nineteen or something like that. The cool thing here is 361 00:19:34,236 --> 00:19:37,716 Speaker 3: that this optical tweezer at the very focus of that 362 00:19:37,836 --> 00:19:41,436 Speaker 3: lens gets really really tight and diverges really really quickly 363 00:19:42,196 --> 00:19:45,916 Speaker 3: and for some light, and we very very carefully choose 364 00:19:45,996 --> 00:19:48,916 Speaker 3: what kind of laser we're doing this with. Atoms are 365 00:19:49,396 --> 00:19:52,436 Speaker 3: tracted to the point of highest intensity, okay, and so 366 00:19:52,516 --> 00:19:55,116 Speaker 3: the atom kind of gets sucked in to the optical 367 00:19:55,156 --> 00:19:58,476 Speaker 3: tweezer and then it wants to sit at the exact 368 00:19:58,636 --> 00:20:00,156 Speaker 3: center of that pholk. 369 00:20:00,196 --> 00:20:02,676 Speaker 1: So it's called an optical tweezer because it is grabbing 370 00:20:02,796 --> 00:20:04,196 Speaker 1: a single atom. 371 00:20:04,516 --> 00:20:07,996 Speaker 3: Yeah, okay, So what we do is we do a 372 00:20:08,036 --> 00:20:09,756 Speaker 3: bunch of tricks so that we we don't just create 373 00:20:09,796 --> 00:20:15,916 Speaker 3: one optical tweezer, but generally speaking, we build display technology 374 00:20:16,236 --> 00:20:20,836 Speaker 3: that creates the image of many, many optical tweezers and 375 00:20:20,956 --> 00:20:23,036 Speaker 3: just stuffs that into the back of the lens. 376 00:20:23,316 --> 00:20:27,676 Speaker 1: So you basically have like what twelve hundred optical tweezers 377 00:20:27,676 --> 00:20:30,596 Speaker 1: in each way, he grabs one atom and exactly sticks 378 00:20:30,636 --> 00:20:31,316 Speaker 1: it in the box. 379 00:20:31,996 --> 00:20:33,756 Speaker 3: Exactly. No, no, that is exactly what we do. 380 00:20:33,836 --> 00:20:36,996 Speaker 1: So now there's this box that's ready to help someone 381 00:20:37,076 --> 00:20:40,436 Speaker 1: figure out something about the world. What is something about 382 00:20:40,476 --> 00:20:43,836 Speaker 1: the world that it might actually help them understand. 383 00:20:44,436 --> 00:20:47,436 Speaker 3: Yeah, So, say there's a user in Denmark and Copenhagen 384 00:20:47,436 --> 00:20:50,196 Speaker 3: who wants to understand the ground state of some molecule. 385 00:20:50,956 --> 00:20:54,076 Speaker 3: They write down an algorithm that says, I am going 386 00:20:54,156 --> 00:20:58,756 Speaker 3: to simulate many, many electrons, and I am going to 387 00:20:58,876 --> 00:21:01,796 Speaker 3: use it such that it kind of gets down to 388 00:21:01,836 --> 00:21:04,076 Speaker 3: the lowest energy state, Okay, and then I will read 389 00:21:04,116 --> 00:21:08,076 Speaker 3: out the cubits in their various positions and things like that. Aha, 390 00:21:08,196 --> 00:21:10,876 Speaker 3: so that we can actually understand what was the state 391 00:21:10,956 --> 00:21:13,396 Speaker 3: of the electrons in this simulated system. 392 00:21:13,956 --> 00:21:17,716 Speaker 1: So are they're sort of saying to the quantum computer 393 00:21:17,916 --> 00:21:20,476 Speaker 1: that you have built, act like you are this molecule. 394 00:21:20,476 --> 00:21:23,436 Speaker 1: Act like you are the electrons in this molecule exactly 395 00:21:23,476 --> 00:21:26,356 Speaker 1: in their lowest energy state, and tell me what state 396 00:21:26,356 --> 00:21:41,876 Speaker 1: you're in, Yes, exactly. We'll be back in just a minute. Hey, 397 00:21:42,076 --> 00:21:44,036 Speaker 1: it's Jacob, and I want to tell you that I 398 00:21:44,036 --> 00:21:47,636 Speaker 1: am hosting a new show called Business History. It's about 399 00:21:47,676 --> 00:21:52,396 Speaker 1: the incredible innovations and massive failures and unbelievable characters in 400 00:21:52,436 --> 00:21:55,356 Speaker 1: the history of business. And I hope I think the 401 00:21:55,436 --> 00:21:59,236 Speaker 1: show provides insights about how business works today. At the 402 00:21:59,396 --> 00:22:01,796 Speaker 1: end of today's episode of What's Your Problem, We're going 403 00:22:01,876 --> 00:22:04,276 Speaker 1: to play you a clip from Business History. 404 00:22:04,356 --> 00:22:05,276 Speaker 4: It's the story. 405 00:22:04,956 --> 00:22:08,476 Speaker 1: Behind the video game company Atari, and they're surprising early 406 00:22:08,556 --> 00:22:11,916 Speaker 1: hire of a young hippie named Steve Jobs. The show's 407 00:22:11,956 --> 00:22:14,396 Speaker 1: called Business History. You can listen to it wherever you're 408 00:22:14,396 --> 00:22:17,196 Speaker 1: listening right now, and will play that clip at the end. 409 00:22:17,116 --> 00:22:18,036 Speaker 4: Of today's episode. 410 00:22:22,356 --> 00:22:25,276 Speaker 1: One of the big problems in quantum computing is detecting 411 00:22:25,316 --> 00:22:28,676 Speaker 1: and correcting errors. This is a hard problem for a 412 00:22:28,676 --> 00:22:31,276 Speaker 1: few reasons. One of those reasons gets at the heart 413 00:22:31,316 --> 00:22:35,636 Speaker 1: of quantum weirdness, and it's this. When a quantum computer 414 00:22:35,756 --> 00:22:39,036 Speaker 1: is working, the cubits are essentially in many states at once. 415 00:22:39,596 --> 00:22:42,156 Speaker 1: But if at a given moment you will look at 416 00:22:42,196 --> 00:22:44,996 Speaker 1: a cubit try and figure out what state it's in, 417 00:22:45,396 --> 00:22:48,516 Speaker 1: it will instantly snap into a single state. All that 418 00:22:48,636 --> 00:22:52,436 Speaker 1: beautiful quantum weirdness of multiple states at once will suddenly disappear, 419 00:22:52,796 --> 00:22:56,236 Speaker 1: and your quantum computer will not work. There's been a 420 00:22:56,236 --> 00:22:58,716 Speaker 1: lot of progress on this in the past few years, 421 00:22:59,356 --> 00:23:02,436 Speaker 1: but for the most part, quantum error correction still only 422 00:23:02,476 --> 00:23:05,756 Speaker 1: works at a scale too small to be useful for practical, 423 00:23:05,956 --> 00:23:09,796 Speaker 1: real world problems. I asked Ben, why. 424 00:23:09,716 --> 00:23:12,836 Speaker 3: All the classical stuff we're building, all the laser projectors, 425 00:23:12,876 --> 00:23:15,596 Speaker 3: all the spot makers, all these things. As you scale 426 00:23:15,636 --> 00:23:18,876 Speaker 3: those numbers up, if you know you're a stray light 427 00:23:19,156 --> 00:23:21,196 Speaker 3: or whatever it is you're doing for your quantum computer, 428 00:23:21,236 --> 00:23:24,556 Speaker 3: if that increases, then all of a sudden, your quantumeric 429 00:23:24,596 --> 00:23:26,436 Speaker 3: corection doesn't quite work as well as you want it to. 430 00:23:29,196 --> 00:23:32,076 Speaker 4: It seems very hard, yes, very hard. 431 00:23:32,156 --> 00:23:33,556 Speaker 1: Like I mean, I talk to a lot of Italy 432 00:23:33,636 --> 00:23:37,516 Speaker 1: do things that sae hard, but this seems like wild hard. 433 00:23:38,556 --> 00:23:41,796 Speaker 3: I would say that the last twenty four months there 434 00:23:41,796 --> 00:23:44,876 Speaker 3: have been so many amazing advances. I would say everyone 435 00:23:44,916 --> 00:23:47,796 Speaker 3: in the industry is more excited than they've ever been 436 00:23:48,156 --> 00:23:51,116 Speaker 3: because I think you go back two years ago and 437 00:23:51,716 --> 00:23:55,836 Speaker 3: no one had demonstrated quantumeric correction at any scale. Now 438 00:23:55,836 --> 00:23:59,316 Speaker 3: there's US, there's Google, there's lots of other companies that 439 00:23:59,356 --> 00:24:03,316 Speaker 3: have now demonstrated quantumeric corection. Yeah, a small number of cubits, 440 00:24:03,836 --> 00:24:05,836 Speaker 3: but I think that is a key milestone, which is 441 00:24:05,876 --> 00:24:09,116 Speaker 3: to say, look that theory is right, Like your errors 442 00:24:09,396 --> 00:24:12,356 Speaker 3: go down as you spread this quantum information across your 443 00:24:12,476 --> 00:24:15,596 Speaker 3: quantum processor. And I think that's a huge, huge boon 444 00:24:15,716 --> 00:24:18,276 Speaker 3: because it says, no, all you have to do is 445 00:24:18,356 --> 00:24:20,636 Speaker 3: just get to larger and larger and larger numbers. 446 00:24:21,956 --> 00:24:24,116 Speaker 1: So there's this phrase, I think I heard you use 447 00:24:24,156 --> 00:24:27,316 Speaker 1: it or maybe I read it, which is commercial advantage. Right. 448 00:24:27,356 --> 00:24:33,316 Speaker 1: You've talked about sort of governments being initial users. What's 449 00:24:33,396 --> 00:24:37,676 Speaker 1: the universe where a quantum computer becomes practical for a 450 00:24:37,756 --> 00:24:38,636 Speaker 1: private company? 451 00:24:38,956 --> 00:24:41,556 Speaker 3: Yeah, I mean I think that like a pharmaceutical company 452 00:24:41,596 --> 00:24:44,156 Speaker 3: like Novo Nordisk or Eli Lilly or something like that. 453 00:24:44,356 --> 00:24:48,196 Speaker 3: I think they're going to have simulation frameworks that you know, 454 00:24:48,836 --> 00:24:51,236 Speaker 3: engineers are going to sit down at their desks and 455 00:24:51,596 --> 00:24:53,956 Speaker 3: use those simulation frameworks, and it's going to be constantly 456 00:24:53,996 --> 00:24:55,796 Speaker 3: sending jobs to a quantum computer. 457 00:24:56,236 --> 00:24:59,316 Speaker 4: Tell me about this molecule in its lowest. 458 00:24:59,036 --> 00:25:02,516 Speaker 3: Energy state exactly, yeah, or dynamics or something like. 459 00:25:02,476 --> 00:25:06,116 Speaker 1: That, like what are the dynamics if this drug binds 460 00:25:06,156 --> 00:25:07,556 Speaker 1: with this part of a cell? 461 00:25:08,396 --> 00:25:13,076 Speaker 3: Exactly? No, exactly. So I think that most companies will 462 00:25:13,196 --> 00:25:16,036 Speaker 3: view quantic computers in that lens where it's just another 463 00:25:16,436 --> 00:25:19,676 Speaker 3: cloud computing resource that they're spending money on. And I 464 00:25:19,676 --> 00:25:22,436 Speaker 3: could even imagine a future where you know, this is 465 00:25:22,596 --> 00:25:26,996 Speaker 3: so ingrained in kind of simulation frameworks. It's not even 466 00:25:26,996 --> 00:25:29,436 Speaker 3: clear you know, you're spending it on a quantum computing 467 00:25:30,116 --> 00:25:33,116 Speaker 3: you know, hours on a quantic computer. You're actually just 468 00:25:33,156 --> 00:25:35,716 Speaker 3: you know, buying time on your simulation framework that you 469 00:25:35,756 --> 00:25:37,236 Speaker 3: get from another company or so on. 470 00:25:37,476 --> 00:25:41,236 Speaker 1: Yes, we haven't talked about AI. We've gone a while, 471 00:25:41,236 --> 00:25:43,516 Speaker 1: we haven't talked about AI. And there's like a couple 472 00:25:43,556 --> 00:25:46,356 Speaker 1: of sides of AI, right, There's like AI helping to 473 00:25:46,396 --> 00:25:50,876 Speaker 1: make quantum computers. There's also AI being able to do things, 474 00:25:50,956 --> 00:25:53,996 Speaker 1: you know, on classical chips that we didn't think maybe 475 00:25:53,996 --> 00:25:56,756 Speaker 1: classical computers could do. Like I'm thinking of of the 476 00:25:56,796 --> 00:26:02,396 Speaker 1: protein folding problem, right, this famous hard molecular level problem 477 00:26:02,476 --> 00:26:05,796 Speaker 1: that AI solved that nobody could solve for a long time, 478 00:26:06,476 --> 00:26:08,196 Speaker 1: seems like the kind of thing that you might have 479 00:26:08,316 --> 00:26:12,116 Speaker 1: looked years ago been like, oh, here's the thing quantum 480 00:26:12,156 --> 00:26:14,436 Speaker 1: computers can do. They can predict the shape of a protein. 481 00:26:14,556 --> 00:26:17,396 Speaker 3: Yeah, I think that's true, I will say, when we 482 00:26:17,436 --> 00:26:20,276 Speaker 3: go and talk to you know, the experts in the field. 483 00:26:20,316 --> 00:26:21,956 Speaker 3: I think one of the things we hear an awful 484 00:26:21,996 --> 00:26:25,036 Speaker 3: lot about is is the idea that the AI is 485 00:26:25,076 --> 00:26:27,956 Speaker 3: only ever good at the data you give it and 486 00:26:28,236 --> 00:26:30,436 Speaker 3: a new use case for quantum computers that you know, 487 00:26:30,476 --> 00:26:33,916 Speaker 3: no one talked about more than like three years ago, 488 00:26:34,436 --> 00:26:37,796 Speaker 3: was using quantum computers to just pump out data for 489 00:26:37,956 --> 00:26:40,556 Speaker 3: a train, and. 490 00:26:40,636 --> 00:26:44,516 Speaker 1: I it would be if that was the case, it's like, oh, 491 00:26:44,596 --> 00:26:47,196 Speaker 1: we're just making the AI better. We kind of a 492 00:26:47,196 --> 00:26:49,836 Speaker 1: bummer at sub level, not to be silly, but you 493 00:26:49,876 --> 00:26:50,396 Speaker 1: know what I mean. 494 00:26:55,316 --> 00:26:57,876 Speaker 3: But I do think it's this idea that you know, fundamentally, 495 00:26:57,996 --> 00:27:01,316 Speaker 3: like if all of your AI data is coming from 496 00:27:01,476 --> 00:27:06,476 Speaker 3: classical models or classical you know, algorithms spitting out data 497 00:27:06,556 --> 00:27:09,356 Speaker 3: to go and train alpha fold or whatever it's called on, 498 00:27:10,236 --> 00:27:12,276 Speaker 3: you only get it so good. And if you can 499 00:27:12,316 --> 00:27:15,796 Speaker 3: go a step further and start getting the AI to 500 00:27:16,356 --> 00:27:20,156 Speaker 3: understand the kind of quantum pieces of the puzzle, that 501 00:27:20,196 --> 00:27:21,756 Speaker 3: all of a sudden your AI is going to start 502 00:27:21,796 --> 00:27:26,236 Speaker 3: including those in its predictions. But I do agree that 503 00:27:26,276 --> 00:27:29,116 Speaker 3: the flip side of this is building a ton of 504 00:27:29,196 --> 00:27:32,396 Speaker 3: quantum systems whose sole job it is just pumped out 505 00:27:32,476 --> 00:27:35,236 Speaker 3: data for FREYI is a little surprising. 506 00:27:34,956 --> 00:27:36,596 Speaker 4: A little bit of a sad trombone. 507 00:27:36,716 --> 00:27:41,196 Speaker 1: And I mean, is there any way in which AI 508 00:27:41,356 --> 00:27:43,596 Speaker 1: is helping you or helping the field? 509 00:27:44,076 --> 00:27:45,036 Speaker 4: Figure things out. 510 00:27:45,676 --> 00:27:47,276 Speaker 3: Yeah, I mean I do think it is like I 511 00:27:47,556 --> 00:27:50,316 Speaker 3: think that actually in control, I think they're a huge, 512 00:27:50,396 --> 00:27:53,796 Speaker 3: huge ability for AI. Like I think that when we 513 00:27:53,796 --> 00:27:56,196 Speaker 3: talk about scaling up systems and how do you tune 514 00:27:56,236 --> 00:27:59,276 Speaker 3: things and how do you kind of get control to 515 00:27:59,716 --> 00:28:03,436 Speaker 3: across you know, many many, many cubits, AI is much 516 00:28:03,476 --> 00:28:05,876 Speaker 3: much better at finding correlations and data and things like 517 00:28:05,876 --> 00:28:08,876 Speaker 3: that and actually having an understanding of how you turn 518 00:28:08,916 --> 00:28:11,796 Speaker 3: the troll knobs you have into the outputs you want. 519 00:28:12,116 --> 00:28:14,356 Speaker 3: AI is actually fantastic at that. I also think the 520 00:28:14,396 --> 00:28:16,956 Speaker 3: other thing is true, which is just that I mean 521 00:28:17,036 --> 00:28:20,516 Speaker 3: we operate faster because people write software faster now, oh right, 522 00:28:20,636 --> 00:28:22,436 Speaker 3: Like even in the last like six months, I would 523 00:28:22,476 --> 00:28:24,756 Speaker 3: say there is more and more and more software at 524 00:28:24,756 --> 00:28:28,316 Speaker 3: Atom Computing that is being written with AI, and it 525 00:28:28,356 --> 00:28:30,996 Speaker 3: would be done you know, I don't even know ten 526 00:28:31,036 --> 00:28:32,436 Speaker 3: times faster with AI than it. 527 00:28:32,396 --> 00:28:39,956 Speaker 1: Was possible speaking of simple productivity gains with profound cons Yeah. 528 00:28:40,036 --> 00:28:42,916 Speaker 1: So well, we started out talking about a you know, 529 00:28:43,156 --> 00:28:49,316 Speaker 1: relatively optimistic scenario five years, ten years, like why might 530 00:28:49,676 --> 00:28:53,476 Speaker 1: quantum computing not get there or take much longer than 531 00:28:53,516 --> 00:28:53,916 Speaker 1: you think? 532 00:28:55,156 --> 00:28:58,356 Speaker 3: I think it's all a challenge of you know, how much. 533 00:28:58,756 --> 00:29:02,716 Speaker 3: How many resources are you willing to devote to get 534 00:29:03,036 --> 00:29:06,076 Speaker 3: quantum computers to work? And what are the use cases? 535 00:29:06,356 --> 00:29:08,556 Speaker 3: Like I think that a lot of the kind of 536 00:29:08,676 --> 00:29:12,276 Speaker 3: chemistry use cases and stuff we're excited about. But like 537 00:29:12,316 --> 00:29:14,396 Speaker 3: you said, there's always going to be new techniques and 538 00:29:14,636 --> 00:29:17,996 Speaker 3: things like that. And if we can find new techniques 539 00:29:18,036 --> 00:29:20,876 Speaker 3: that you know, get us far enough, then the thing 540 00:29:20,876 --> 00:29:23,716 Speaker 3: that we only have to fall back on is decryption. 541 00:29:24,236 --> 00:29:26,756 Speaker 3: And the question is, you know who there's only one 542 00:29:26,796 --> 00:29:29,516 Speaker 3: customer that wants to decrypt at least in the United. 543 00:29:29,316 --> 00:29:32,236 Speaker 4: States, at least two. I was gonna say every. 544 00:29:31,956 --> 00:29:35,876 Speaker 3: Government in the world, right, Yeah, But I think it's 545 00:29:35,916 --> 00:29:39,396 Speaker 3: it's a question of like resources and resource allocation, which 546 00:29:39,476 --> 00:29:41,996 Speaker 3: is that if that's something the government's you know, very 547 00:29:42,076 --> 00:29:44,116 Speaker 3: very excited about still, then of course, you know, I 548 00:29:44,436 --> 00:29:46,756 Speaker 3: think we can keep scaling and we can make bigger 549 00:29:46,756 --> 00:29:47,876 Speaker 3: and bigger quantic computers. 550 00:29:47,876 --> 00:29:50,236 Speaker 4: And this is the use case you say, it's just money. 551 00:29:50,556 --> 00:29:52,116 Speaker 3: I mean I think that we have and I think 552 00:29:52,156 --> 00:29:53,836 Speaker 3: this is true of a lot of different kinds of 553 00:29:53,876 --> 00:29:57,636 Speaker 3: quantic computing modalities. Now the science has now been demonstrated 554 00:29:57,836 --> 00:30:00,756 Speaker 3: error correction works. We need, like you said, a thousand 555 00:30:00,756 --> 00:30:03,476 Speaker 3: times more cubits, and we want to go and do 556 00:30:03,596 --> 00:30:07,236 Speaker 3: that by building network machines and scaling up the number 557 00:30:07,236 --> 00:30:09,556 Speaker 3: of cubits inside each one of our systems and so on. 558 00:30:09,716 --> 00:30:12,596 Speaker 3: And I'm sure our competitors have similar stories as well. 559 00:30:13,156 --> 00:30:13,436 Speaker 5: Uh. 560 00:30:13,476 --> 00:30:15,876 Speaker 3: And so the question just becomes, you know, is there 561 00:30:15,916 --> 00:30:19,396 Speaker 3: the capital, is there the the excitement around building it? 562 00:30:19,996 --> 00:30:25,756 Speaker 1: So you you mentioned your competitors. You are a private company, right. 563 00:30:26,876 --> 00:30:30,636 Speaker 1: Your competitors include some public quantum computing companies, but they 564 00:30:30,636 --> 00:30:35,596 Speaker 1: also include like Google and IBM, Right, like these giant 565 00:30:35,636 --> 00:30:40,676 Speaker 1: companies with huge revenue streams and kind of all the. 566 00:30:40,636 --> 00:30:45,396 Speaker 4: Money they want, literally but a lot of money. How 567 00:30:45,436 --> 00:30:48,996 Speaker 4: do you compete? How do you how do how does that? 568 00:30:49,236 --> 00:30:52,036 Speaker 4: How does that work for you? Oh? 569 00:30:52,156 --> 00:30:55,756 Speaker 3: I mean I think that, uh, I mean like any industry. 570 00:30:55,836 --> 00:30:58,156 Speaker 3: I mean I think there's you know, venture investors and 571 00:30:58,196 --> 00:31:01,636 Speaker 3: stuff who are excited about, you know, first of all, 572 00:31:01,676 --> 00:31:05,396 Speaker 3: building funding technology that's different than the technology that's found 573 00:31:05,436 --> 00:31:08,956 Speaker 3: at those giant hyperscaler you know, big companies, and second, 574 00:31:09,276 --> 00:31:13,356 Speaker 3: uh who want to invest in that technology because if 575 00:31:13,396 --> 00:31:17,796 Speaker 3: that technology wins, they actually get significantly more back from 576 00:31:17,876 --> 00:31:20,916 Speaker 3: their investment than if they invest in Google. Like if 577 00:31:20,956 --> 00:31:23,436 Speaker 3: Google has a quantum computer. I actually don't think the 578 00:31:23,596 --> 00:31:26,956 Speaker 3: Google quantum stock is going to double overnight. Whereas if 579 00:31:26,996 --> 00:31:28,836 Speaker 3: all of a sudden we have a universal fault talent 580 00:31:28,996 --> 00:31:32,556 Speaker 3: quantum computer at Adam, yeah, our value could go up 581 00:31:32,556 --> 00:31:34,636 Speaker 3: by a ten or one hundred x or something like that. 582 00:31:34,716 --> 00:31:36,716 Speaker 3: So I think there's just like an asymmetry there and 583 00:31:36,956 --> 00:31:39,156 Speaker 3: returns things like that. Yeah. 584 00:31:39,276 --> 00:31:42,036 Speaker 1: So one of the interesting things about the field is 585 00:31:43,076 --> 00:31:48,596 Speaker 1: there are a bunch of different companies using very different approaches, 586 00:31:48,636 --> 00:31:53,276 Speaker 1: like physically different approaches. And I recognize that maybe more 587 00:31:53,276 --> 00:31:54,876 Speaker 1: than one will work, or some will be good for 588 00:31:54,876 --> 00:31:56,956 Speaker 1: some things and something good for others. But there might 589 00:31:56,996 --> 00:32:00,396 Speaker 1: be something of a binary outcome, right, Like somebody might win. 590 00:32:00,556 --> 00:32:03,636 Speaker 1: Somebody might get there first. What do you think of 591 00:32:03,676 --> 00:32:06,276 Speaker 1: the chances it'll be somebody other than you. 592 00:32:08,596 --> 00:32:13,196 Speaker 3: I certainly think there's a chance. I think that who 593 00:32:13,276 --> 00:32:15,476 Speaker 3: wins in the end is going to just come down 594 00:32:15,636 --> 00:32:20,876 Speaker 3: to dollars per unit compute. Like I think there's someone 595 00:32:20,916 --> 00:32:23,236 Speaker 3: will get there first. I hope it's Adam, but you 596 00:32:23,236 --> 00:32:25,476 Speaker 3: know someone's going to get there first. I think there 597 00:32:25,476 --> 00:32:29,036 Speaker 3: will be a few years of multiple people then getting there, 598 00:32:29,116 --> 00:32:31,716 Speaker 3: multiple modalities getting there, And I think at the end 599 00:32:31,756 --> 00:32:34,476 Speaker 3: of the day, what wins is just dollar per unit compute, 600 00:32:34,716 --> 00:32:36,716 Speaker 3: And all of a sudden, if there's a ten x 601 00:32:36,756 --> 00:32:40,396 Speaker 3: difference in price between running on this system versus running 602 00:32:40,396 --> 00:32:43,036 Speaker 3: on another system, people are just going to gravitate towards 603 00:32:43,076 --> 00:32:45,156 Speaker 3: a cheaper one. And I think that will be the 604 00:32:45,156 --> 00:32:47,956 Speaker 3: one that actually turns out to be the one that 605 00:32:48,036 --> 00:32:50,036 Speaker 3: you know, an entire industry is built around. 606 00:32:51,036 --> 00:32:52,716 Speaker 1: Where do you think we should end the main part 607 00:32:52,756 --> 00:32:55,196 Speaker 1: of this conversation, Like if you sort of sit back 608 00:32:55,236 --> 00:32:58,476 Speaker 1: and think big thoughts and gaze off into the distance, 609 00:32:58,596 --> 00:33:02,436 Speaker 1: like what like where do you land thinking about this today? 610 00:33:04,236 --> 00:33:06,636 Speaker 3: I mean, I think the quantum computers are more of 611 00:33:06,676 --> 00:33:09,356 Speaker 3: an inevitability than they've ever been. Like, I think that 612 00:33:09,396 --> 00:33:13,116 Speaker 3: we've made such amazing progress as an industry that everyone 613 00:33:13,196 --> 00:33:15,276 Speaker 3: is on board with the idea that no, no, this 614 00:33:15,356 --> 00:33:18,396 Speaker 3: is this is just going to happen. Like if someone's 615 00:33:18,436 --> 00:33:21,396 Speaker 3: going to have a universal fault talent quantum computer, people 616 00:33:21,436 --> 00:33:23,116 Speaker 3: are going to be able to use it over the cloud. 617 00:33:23,156 --> 00:33:25,236 Speaker 3: They're going to be able to do all the problems 618 00:33:25,276 --> 00:33:27,076 Speaker 3: they want to do, and so on and so forth. 619 00:33:27,116 --> 00:33:29,636 Speaker 3: And I feel like even I don't know, three four 620 00:33:29,716 --> 00:33:31,636 Speaker 3: or five years ago, I don't think people would have 621 00:33:31,676 --> 00:33:34,836 Speaker 3: said that across the board. 622 00:33:36,676 --> 00:33:49,676 Speaker 1: We'll be back in a minute with the lightning round. Okay, 623 00:33:49,716 --> 00:33:52,076 Speaker 1: let's finish with the lightning round. It's gonna be a 624 00:33:52,116 --> 00:33:54,476 Speaker 1: little more random, but fun. I hope. 625 00:33:57,036 --> 00:33:59,276 Speaker 4: Albert Einstein overrated or underrated? 626 00:34:00,556 --> 00:34:01,156 Speaker 3: Underrated? 627 00:34:01,636 --> 00:34:15,316 Speaker 1: Yeah, very highly rated. Richard Feynman overrated rounded, Uh. 628 00:34:13,996 --> 00:34:16,996 Speaker 3: I think underrated. I think that actually seeing him give lectures. 629 00:34:16,996 --> 00:34:19,276 Speaker 3: I didn't get to see him in person, but I mean, 630 00:34:19,316 --> 00:34:21,396 Speaker 3: I think seeing recordings of him given lectures, I mean 631 00:34:21,436 --> 00:34:24,076 Speaker 3: I think he was probably the most amazing physics teacher 632 00:34:24,116 --> 00:34:24,476 Speaker 3: there was. 633 00:34:25,196 --> 00:34:27,476 Speaker 4: Is it right? Did Feineman come up with the idea 634 00:34:27,556 --> 00:34:28,556 Speaker 4: of the quantum computer? 635 00:34:28,676 --> 00:34:31,116 Speaker 3: I read it also, Yeah, and he has this amazing 636 00:34:31,196 --> 00:34:33,916 Speaker 3: sentence about how you know it would be so simple 637 00:34:33,956 --> 00:34:36,276 Speaker 3: to do this with a bunch of atoms that you 638 00:34:36,396 --> 00:34:38,756 Speaker 3: kind of rearrange and you kind of move around and 639 00:34:38,756 --> 00:34:41,276 Speaker 3: stuff like that. Someone showed that to me many many 640 00:34:41,356 --> 00:34:43,356 Speaker 3: years after I had started a company to do this 641 00:34:43,436 --> 00:34:43,876 Speaker 3: with Adam. 642 00:34:43,956 --> 00:34:46,916 Speaker 4: So was he right that it would be so simple? 643 00:34:46,956 --> 00:34:47,836 Speaker 3: Absolutely? Yeah? 644 00:34:48,116 --> 00:34:53,116 Speaker 4: Wait? What no? Is it right that. 645 00:34:53,516 --> 00:34:56,596 Speaker 1: You made or helped to make an atomic clock that's 646 00:34:56,676 --> 00:34:59,756 Speaker 1: precise to the second over five billion years? 647 00:34:59,996 --> 00:35:04,916 Speaker 4: The most something precise clock ever, Yeah, so okay, A 648 00:35:04,916 --> 00:35:08,876 Speaker 4: few questions following on that. Precisely? How early do you 649 00:35:08,916 --> 00:35:11,756 Speaker 4: get to the airport to catch a plane? Oh? 650 00:35:11,916 --> 00:35:14,316 Speaker 3: Actually, this is a great thing that someone taught me. 651 00:35:14,596 --> 00:35:17,356 Speaker 3: If you don't miss a flight every like, you know, 652 00:35:17,436 --> 00:35:19,636 Speaker 3: fifty times, you're always getting to the airport tour. 653 00:35:19,756 --> 00:35:22,716 Speaker 1: Yes, that is a theory, that's an optimization. So what 654 00:35:22,916 --> 00:35:25,956 Speaker 1: for you is the optimal fraction of flights to miss? 655 00:35:27,316 --> 00:35:29,396 Speaker 3: I think like one percent or something like that. 656 00:35:29,636 --> 00:35:30,956 Speaker 4: When was the last time you missed a plane? 657 00:35:32,876 --> 00:35:35,676 Speaker 3: Probably like thirty forty fifty flights ago or something. 658 00:35:35,876 --> 00:35:36,716 Speaker 4: So you're doing okay? 659 00:35:36,996 --> 00:35:37,316 Speaker 3: Yeah ye. 660 00:35:45,716 --> 00:35:50,196 Speaker 1: Ben Bloom is the co founder and CEO of Adam Computing. 661 00:35:50,476 --> 00:35:53,756 Speaker 1: Today's show was produced by Gabriel Hunter Chang. It was 662 00:35:53,996 --> 00:35:57,476 Speaker 1: edited by Lyddy jeene Kott and engineered by Sarah Bruguer. 663 00:35:57,916 --> 00:36:01,116 Speaker 1: You can email us at problem at Pushkin dot FM. 664 00:36:01,676 --> 00:36:04,036 Speaker 1: I'm Jacob Goldstein and we'll be back next week with 665 00:36:04,076 --> 00:36:15,956 Speaker 1: another episode of What's Your Problem. I'm Jacob Goldstein, and 666 00:36:16,076 --> 00:36:18,996 Speaker 1: right now we're going to play you a clip of 667 00:36:19,076 --> 00:36:21,596 Speaker 1: a new show that I co host. The show's called 668 00:36:21,796 --> 00:36:24,676 Speaker 1: Business History. My co host is Robert Smith and This 669 00:36:24,836 --> 00:36:28,836 Speaker 1: clip is from an episode we did about how Nolan Bushnell, 670 00:36:29,156 --> 00:36:33,236 Speaker 1: a stoner turned entrepreneur, created the video game company Atari 671 00:36:33,836 --> 00:36:37,996 Speaker 1: and hired a young, inexperienced Steve Jobs. I really hope 672 00:36:37,996 --> 00:36:40,236 Speaker 1: you like the clip, and if you want to hear more, 673 00:36:40,356 --> 00:36:43,396 Speaker 1: you can find business history wherever you're listening to this 674 00:36:43,516 --> 00:36:47,916 Speaker 1: show right now. This like nineteen year old hippie kid 675 00:36:47,956 --> 00:36:50,996 Speaker 1: walks in and he says he won't leave until they 676 00:36:50,996 --> 00:36:53,876 Speaker 1: give him a job, And the receptionist calls the head 677 00:36:53,876 --> 00:36:57,076 Speaker 1: engineer and she goes, yeah, we got a hippie kid 678 00:36:57,076 --> 00:36:57,596 Speaker 1: in the lobby. 679 00:36:57,676 --> 00:36:59,836 Speaker 4: Says he won't leave until we hire him. Should we 680 00:36:59,876 --> 00:37:03,436 Speaker 4: call the cops or let him in? And the engineer says, 681 00:37:03,516 --> 00:37:04,316 Speaker 4: bring him on in. 682 00:37:04,556 --> 00:37:07,836 Speaker 5: It's nineteen seventies, a Silicon valley, and this guy wanders 683 00:37:07,876 --> 00:37:10,716 Speaker 5: in and he is when if you tell a story 684 00:37:10,756 --> 00:37:11,476 Speaker 5: like this, you know who it is. 685 00:37:11,516 --> 00:37:14,116 Speaker 4: It's Steve Jobs. It's Steve Job. So fun, it's so 686 00:37:14,236 --> 00:37:16,836 Speaker 4: delightful and perfectly. 687 00:37:17,556 --> 00:37:20,836 Speaker 1: Steve Jobs is very good at his job, yes, and 688 00:37:20,956 --> 00:37:23,036 Speaker 1: very unpleasant to wrqu On. 689 00:37:23,156 --> 00:37:23,676 Speaker 4: Surprising. 690 00:37:24,116 --> 00:37:27,716 Speaker 1: He tells Bushnell that like everybody's soldering wrong, right, they're 691 00:37:27,716 --> 00:37:30,396 Speaker 1: actually putting together the hardware sladering the hardware. He's probably right, 692 00:37:30,396 --> 00:37:32,436 Speaker 1: and bush Nell's like, yeah, he was right. He keeps 693 00:37:32,476 --> 00:37:33,956 Speaker 1: calling his manager a dumb shit. 694 00:37:34,156 --> 00:37:35,436 Speaker 4: Probably was not. 695 00:37:35,556 --> 00:37:40,076 Speaker 1: Kind, not necessary. Bushell winds up putting Jobs on the 696 00:37:40,196 --> 00:37:43,796 Speaker 1: night shift, partly so he won't bother so many people, 697 00:37:43,836 --> 00:37:46,836 Speaker 1: and partly because he knew that Jobs like to hang 698 00:37:46,876 --> 00:37:50,316 Speaker 1: out at night with his buddy Steve Wozniak, who was 699 00:37:50,356 --> 00:37:51,716 Speaker 1: a great engineer, would. 700 00:37:51,476 --> 00:37:53,636 Speaker 4: Be great to have hanging around Atari. 701 00:37:53,716 --> 00:37:56,956 Speaker 1: And in fact, Jobs and Wozniak helped to make Breakout 702 00:37:57,716 --> 00:37:58,396 Speaker 1: a great a target. 703 00:37:58,516 --> 00:37:59,636 Speaker 4: Remember breaking of. 704 00:37:59,596 --> 00:38:01,556 Speaker 5: Course, you're trying to knock down the bricks in a wall. 705 00:38:01,836 --> 00:38:03,676 Speaker 4: Still, games like that, when you got a little paddle 706 00:38:03,676 --> 00:38:04,356 Speaker 4: at the bottom. 707 00:38:04,156 --> 00:38:05,716 Speaker 5: End, there's a moment when it goes through the wall 708 00:38:05,716 --> 00:38:06,116 Speaker 5: and then. 709 00:38:05,996 --> 00:38:08,956 Speaker 4: Goes so good. 710 00:38:09,716 --> 00:38:12,076 Speaker 1: So Jobs worked at Atari for a little while and 711 00:38:12,116 --> 00:38:14,116 Speaker 1: then decided that he wanted to go off to India 712 00:38:14,156 --> 00:38:18,436 Speaker 1: to find his guru. Perfect asked Atari to pay for 713 00:38:18,516 --> 00:38:21,876 Speaker 1: the trip. Nobody ever said he lacked moxie, and wound 714 00:38:21,916 --> 00:38:24,676 Speaker 1: up making a deal with Atari where they pay him 715 00:38:24,676 --> 00:38:27,156 Speaker 1: to go part of the way there. They had exported 716 00:38:27,196 --> 00:38:28,676 Speaker 1: some games to Germany and there was some kind of 717 00:38:28,676 --> 00:38:30,356 Speaker 1: problem with the games in Germany and they're like, we'll 718 00:38:30,396 --> 00:38:33,036 Speaker 1: send you to Germany to fix the games and then 719 00:38:33,076 --> 00:38:34,636 Speaker 1: you can get the rest of the way to India. 720 00:38:35,156 --> 00:38:37,916 Speaker 1: And you know, the Germans said Jobs was terrible to 721 00:38:37,956 --> 00:38:41,116 Speaker 1: work with, but he fixed the games. I was thinking 722 00:38:41,116 --> 00:38:43,556 Speaker 1: about like the link between Atarian Jobs and what did 723 00:38:43,596 --> 00:38:45,836 Speaker 1: he learn there, And it felt like maybe a little overdetermined, 724 00:38:45,876 --> 00:38:49,036 Speaker 1: but I do think you know, clearly he had this 725 00:38:49,156 --> 00:38:53,596 Speaker 1: profound sense of aesthetics and of delight, right, Like think 726 00:38:53,596 --> 00:38:56,396 Speaker 1: of the Macintosh, right, this breakthrough Apple machine in the eighties. 727 00:38:56,476 --> 00:38:59,316 Speaker 1: It was round and instead of squares, it was rounded, 728 00:38:59,356 --> 00:39:01,676 Speaker 1: and it cost them more money, but it was beautiful 729 00:39:01,676 --> 00:39:03,996 Speaker 1: and it was fun and you were engaged with it 730 00:39:04,196 --> 00:39:04,756 Speaker 1: like a game. 731 00:39:05,356 --> 00:39:07,436 Speaker 5: It almost looked a little bit like an arcade game 732 00:39:07,476 --> 00:39:10,996 Speaker 5: with the curves than that. I think that especially at 733 00:39:10,996 --> 00:39:13,036 Speaker 5: Silicon Valley at the time when they were dealing in 734 00:39:13,156 --> 00:39:16,196 Speaker 5: actual silicon Right, if you're making chips for somebody, you're 735 00:39:16,236 --> 00:39:19,116 Speaker 5: thinking about the future and the computers. You're not thinking 736 00:39:19,116 --> 00:39:21,636 Speaker 5: about the psychology of the customer, because the customer was 737 00:39:21,676 --> 00:39:25,356 Speaker 5: another electronics company, right, and so Atari and the strength 738 00:39:25,396 --> 00:39:27,676 Speaker 5: of it was really the first time where they're just like, 739 00:39:28,036 --> 00:39:31,676 Speaker 5: how will a regular human being who has no training 740 00:39:31,716 --> 00:39:33,756 Speaker 5: whatsoever interact with technology. 741 00:39:33,916 --> 00:39:39,956 Speaker 1: Yeah, so Atari now mid seventies. They're selling all the 742 00:39:39,996 --> 00:39:43,396 Speaker 1: machines they can make. They need more space, and so 743 00:39:43,436 --> 00:39:46,556 Speaker 1: they rent an abandoned roller rink and they turn it 744 00:39:46,596 --> 00:39:49,076 Speaker 1: into this office slash video game factory. 745 00:39:49,596 --> 00:39:51,836 Speaker 5: I've been ten years older. I would have loved to 746 00:39:51,836 --> 00:39:53,836 Speaker 5: have worked in a roller rink video game factory. 747 00:39:53,916 --> 00:39:57,076 Speaker 4: Yes, everybody smoked weed. Yeah, there was a hot tub. 748 00:39:58,676 --> 00:40:00,876 Speaker 1: There was a pool party where everybody ended up naked 749 00:40:00,876 --> 00:40:04,796 Speaker 1: in the pool at Bushnell himself looked back on it 750 00:40:04,876 --> 00:40:08,076 Speaker 1: later and said, if that isn't a horror show for 751 00:40:08,156 --> 00:40:10,996 Speaker 1: any hr person today, I don't know what is