[00:00] That's why I debated the title of this talk and almost titled it, The Path to Almost Everything. [00:07] We live in a world made of atoms. [00:09] The way those atoms are arranged makes an enormous difference. [00:13] It's the difference between coal and diamond. [00:15] It's the difference between cancer and healthy tissue. [00:19] Most fundamental material technology we can develop is a technology that can guide the [00:24] motion of molecules in a planned, programmable way, to have reactive molecules go together [00:32] to make larger structures, to make larger structures, to make larger structures with [00:36] atomistic precision that can do things for us. [00:39] This is how biology works in a very limited way that emerged on earth through chemical [00:44] processes and our cells are still full of salt water, much like the composition of the [00:49] ocean. [00:50] We can do much better with advanced molecular machinery. [00:54] I would like to speak to the vision of that, which I think the most important development [01:00] in this area, as with perhaps with aging, is to understand the vision for people to [01:05] understand there is something to pursue there. [01:09] We'll argue that the best way to have a clear vision is to have a clear picture, physical [01:13] modeling, images, videos of what this technology base can look like. [01:19] That is a sketch. [01:22] I would like to emphasize that we're in a different time now than we were five years [01:26] ago, ten years ago. [01:27] AI is exploding. [01:29] I should say deep learning is exploding. [01:31] It's providing generative models for protein design. [01:34] As I pointed out in the proceedings of the U.S. National Academy of Sciences in 1981, [01:38] founding the field of, protein engineering is a path to building molecular machine systems [01:44] that can build better molecular machine systems, already atomically precise, already things [01:49] that you can make in macroscopic quantities. [01:52] There are now generative models for protein design just in the last few years that are [01:55] revolutionizing that field. [01:58] Eventually we're going to see generative models for essentially the whole of engineering design [02:02] and with rapid design, progress will be swift. [02:04] It's all bottlenecked on design. [02:08] So the vision, reminder, enormous productive capacity, material abundance, just being able [02:13] to make a lot of very high quality stuff and do it rapidly and cleanly, scale it. [02:18] Atomically accurate restoration. [02:19] It's taking CO2 out of the atmosphere. [02:21] It's just moving stuff around. [02:22] Takes three terawatts for ten years or ten terawatts for three years or 30 terawatts [02:27] for one year and those are all things you could construct and take out the excess CO2. [02:32] Space settlement and space flight. [02:33] That's about making spacecraft and things in space, about arranging stuff, high quality [02:38] stuff, cheap. [02:40] More complicated stories, how one can pursue and achieve permanent health. [02:45] The ability to have atomically precise devices that can sense structure, let us understand [02:52] biology, the ultimate omics, really map things rapidly in full detail. [02:59] Interventions at that level can change medicine more profoundly than I think we can, more [03:07] than you can barely imagine it today. [03:10] So to ground this a little bit in an abstraction, well, excuse me, first some numbers. [03:16] I have been at Oxford. [03:18] I was in the offices of the Future of Humanity Institute, which is shared with the Center [03:23] for Effective Altruism, which is ground zero for the EA movement. [03:26] So of course I have to do an EA style calculation. [03:30] All of this is worth at least $100,000 per capita per year for a poor country. [03:34] And if we add, let's see, a life extension and so on, that's an underestimate. [03:40] Intervention about 10 to the 10th people, multiply that out, that's 10 to the 15th [03:44] dollars per year. [03:45] A one month shift in the period required to develop such a technology is worth 10 to the [03:50] 14th dollars. [03:53] There is a $1 million intervention that can make an enormous difference to that of at [03:56] least one month. [03:57] I will be outlining that and the next speaker will tell you about the progress we have made. [04:03] So it's about design. [04:05] To rationalize this, to understand this, we have already seen a pervasive revolution in [04:09] the world. [04:10] One that has brought us, has replaced essentially the whole of information processing, all the [04:15] analog equipment, et cetera, et cetera, et cetera, with nanoscale digital electronics [04:20] and gave us, by the way, AI. [04:22] This technology is deeply analogous. [04:25] Discrete components moved with great reliability because physics lets you do that. [04:30] Low error rates across trillions of operations, very fast operations, large arrays of components [04:35] working together to make intricate patterns. [04:38] All these are parallels. [04:40] One dominates information processing and with the scalability that comes from molecular [04:45] machinery being able to make more machinery, radical scalability, we're in a position to [04:50] dominate physical production. [04:52] When you think about machines building components for more machines, please do not think of [04:56] bugs. [04:57] Little bugs, little nano bugs. [04:59] That's not how you do manufacturing with swarms. [05:01] Little bugs, please. [05:04] That's a misunderstanding of an idea that was obsolete in 1992, but the media loves [05:09] it, the science fiction authors love it, and it's in everybody's minds. [05:13] Okay, so a minor point in this context. [05:16] It's minor, you can replace semiconductor fabrication with systems that produce enormously [05:20] better hardware for a fraction of the cost and don't require billions of dollars. [05:26] Make superior laptops in your home if you wanted, including the chips, yes. [05:31] Okay, vision. [05:33] Once upon a time, people thought about moving into space, opening up the space frontier. [05:38] They had a vision. [05:39] Early 1990s, excuse me, early, early, early 1950s, the dates, the 1950s, 1952 Collier's [05:47] magazine, very famous issue, article by von Braun and Willy Ley, was about space flight. [05:54] This spacecraft there is very different from what people ended up building, but it's about [05:59] the right mass. [06:00] It has detailed labels. [06:02] On the right, you see a space station. [06:03] It turns out zero gravity is okay for people, so we don't have spinning space stations, [06:07] but it also has detailed labels, and it has detailed labels because von Braun knew what [06:12] he was talking about. [06:13] He led the engineering effort that, in the next decade, built the Saturn V booster that [06:19] launched Apollo missions to the moon. [06:21] Okay, so he had a clear vision. [06:23] He could draw pictures, and people said, oh, cool, space, we can build stuff like this. [06:27] Go to the moon. [06:29] What do we have today? [06:31] Well, complex nanomechanical systems are what's necessary to move things around, put them [06:35] together. [06:36] Atomically precise mass fabrication. [06:38] We have cartoons like this and a handful of atomistic designs and simulations, but basically [06:44] the picture that we have of this future is this. [06:49] This is not inspiring. [06:50] This does not orient people. [06:53] We need to find ways forward. [06:55] We already have molecular fabrication with atomic precision and scalable to mass quantities [07:00] if one wishes through protein engineering. [07:04] Proteins by the way are material that's about as solid as wood. [07:07] It's an engineering material. [07:08] It's not like gelatin or meat or something. [07:11] We have design capacity, molecular engineering to make complex structures, and again, the [07:17] generative models coming out of quote unquote AI, meaning deep learning. [07:22] But what we don't have are clear goals. [07:24] There is a sketch, an architecture for a 3D molecular printer that can be made by self-assembly, [07:31] 100 nanometer scale. [07:32] If you make one, you build 10 to the 12th of them. [07:35] And beyond that, atomically precise fabrication, but again, no picture. [07:43] So how do we break design bottlenecks and get those concrete designs and images? [07:49] Well, we need to build exploratory design tools and user communities. [07:54] The design tools means physical modeling. [07:56] It means top down refinement, being able to design machines, refine them to atomistic [08:01] level, and say something about user communities. [08:04] In a moment here, we have a gap between science and engineering. [08:09] Molecular sciences are very well advanced. [08:11] Most people don't know that you can model molecules as mechanical systems, and the models [08:14] are really excellent. [08:15] They're used to model biomolecules and so on. [08:18] Oh, you can model this stuff? [08:20] Yeah, we can. [08:23] Systems engineering. [08:24] Well, we know how to do that on the macroscopic scale. [08:26] The principles are the same, not in biology, but in systems away from the mess of biology, [08:32] molecular machine systems in controlled environments. [08:35] We know how to do systems engineering that applies in that domain as well. [08:40] We have biomolecular engineering. [08:42] There are laboratory scientists and computational chemists who know how to do this stuff. [08:46] They have motivations. [08:47] They're companies, science careers, and so they do this. [08:51] What about nanosystems engineering? [08:53] What about what would give us a vision, an orientation, a pathway forward? [08:57] Well, who's going to do the work? [09:00] You can't make these things, therefore companies won't pay for it. [09:05] It's not science, it's engineering. [09:07] So it's engineering of something you can't make. [09:09] Big gap. [09:10] On the other hand, it turns out that it's fun to design these things. [09:14] Certified, many people have done this with rather crude tools. [09:19] And so we look for visionary amateurs and engaged gamers who eventually mature into [09:24] professionals and drawn by online communities of competition and cooperation, making cool [09:30] stuff, and fun and challenges. [09:34] So our next speaker will be saying more about the molecular systems engineering platform [09:38] MSEP 1, a shared workspace with visualization manipulation on top of all the infrastructure [09:45] you need to have a good application for this kind of functionality. [09:50] Science tools to bring in scientists who will find that this is very good in their workflows. [09:54] It turns out that the software they have right now is excellent at modeling and for user [09:59] interfaces and ease of installation and so on. [10:02] It's crap. [10:03] This would be much better professionally done. [10:06] It is. [10:07] And easy to install and free, open source. [10:12] In the middle, system level design, atomistic refinement. [10:16] And on the input funnel side, content driven puzzles is an easy on-ramp, gamified design, [10:22] tutorials, feeding into people working on design libraries, building up sets of systems, [10:28] components that are designed that can feed into system level design and also give us [10:33] lovely videos and vision. [10:37] So to move forward, we need more tools. [10:40] We have some basic science tools there. [10:44] We need more tools for design workflows and management for community building, the online [10:51] community of people who will be actually doing the advanced design work. [10:56] And of course, stable financial support. [11:00] So I suggested this has enormous payoff. [11:03] In my final slide, I would like to step back and ask, is this actually in that benefit? [11:08] Many people say, well, no, nanotechnology, disruptive, dangerous, and so on. [11:14] Well, first, the benefit side. [11:16] I have a dual mission here. [11:17] The benefit side, accelerate applications. [11:20] As I already said, a very simple calculation says, my god, $10 to the 14th for one month [11:26] acceleration. [11:27] You get a month acceleration by having design tools now in your future. [11:33] But what about safety? [11:35] There I argued that what we need is the ability to see where we're going. [11:38] People have no clue where we're going. [11:40] What will 21st century physical technology look like? [11:44] It's not going to be based on the manufacturing of today. [11:46] It's going to be based on atomically precise systems that work like nanoscale electronics, [11:51] Digital, fast, high throughput, novel products, mass production, low cost, changes everything. [12:00] Medicine, the environment, global poverty, access to space. [12:06] So we need to understand that, both the dangers and the opportunities, because the opportunities [12:12] can help us coordinate to solve other problems. [12:16] And the value of that, accelerating understanding, preparation for consequences, is existential. [12:23] So because transformative AI is inseparable from transformative nanotechnology, we are [12:29] going to get this level of AI. [12:30] It is going to give us this technology very rapidly once it gets to some threshold. [12:36] This is not optional. [12:37] Thank you.