1 00:00:00,680 --> 00:00:01,640 I'm really excited. 2 00:00:01,640 --> 00:00:05,080 I guess I'm Paul's designated announcer for people here today. 3 00:00:05,080 --> 00:00:08,040 So I'm excited to welcome 4 00:00:08,520 --> 00:00:09,040 Dr. 5 00:00:09,040 --> 00:00:16,440 Rob Ivester, who's the senior advisor on advanced manufacturing at the National Institute for Standards and Technology. 6 00:00:17,000 --> 00:00:31,080 Rob brings decades of leadership across federal research and manufacturing programs, including service as a deputy director of the Hollings Manufacturing Extension Partnership, which is one of the programs that funds Cirrus, and leadership roles within the Department of Energy. 7 00:00:31,800 --> 00:00:37,880 Over the course of his career, he's helped launch major national initiatives, including multiple manufacturing USA institutes, 8 00:00:38,440 --> 00:00:46,280 and the Critical Materials Hub, which is located here at Iowa State University, while also leading research and advanced manufacturing at NIST. 9 00:00:47,160 --> 00:00:47,640 Dr. 10 00:00:47,640 --> 00:01:00,280 Ivister continues to shape the next generation of manufacturing through his work at the intersection of research, policy, and industry, and as an instructor in graduate-level manufacturing engineering at Johns Hopkins University. 11 00:01:01,000 --> 00:01:07,880 In this session, he'll explore how public-private partnerships are advancing the application of AI in manufacturing, 12 00:01:08,280 --> 00:01:21,080 As the lines blur between research and real-world deployment, he'll continue to, he'll outline how government, industry, and academic collaboration is accelerating the transition of AI from concept to practice. 13 00:01:21,320 --> 00:01:23,280 So please join me in welcoming Dr. 14 00:01:23,280 --> 00:01:24,120 Rob Ivester. 15 00:01:29,720 --> 00:01:29,960 All right. 16 00:01:29,960 --> 00:01:30,680 Thanks, Mike. 17 00:01:32,280 --> 00:01:33,040 Mike volume's good. 18 00:01:33,040 --> 00:01:34,320 You can hear me in the back of the room okay? 19 00:01:34,680 --> 00:01:35,160 All right. 20 00:01:37,360 --> 00:01:38,360 Okay, this is not that. 21 00:01:39,880 --> 00:01:40,560 No, it's okay. 22 00:01:40,560 --> 00:01:41,440 Don't worry about it. 23 00:01:41,440 --> 00:01:41,720 It's fine. 24 00:01:43,000 --> 00:01:46,040 No, it's just, I'm used to using the screen. 25 00:01:46,760 --> 00:01:47,120 It's okay. 26 00:01:47,120 --> 00:01:48,040 It's all right. 27 00:01:48,400 --> 00:01:50,440 Don't worry about it. 28 00:01:51,400 --> 00:01:56,520 So, I want to start up because I had a question during the break. 29 00:01:57,000 --> 00:01:58,320 about a public-private partnership. 30 00:01:58,320 --> 00:02:08,760 And I just want to give a quick, let's assume that we're talking about funding technology development, paying for research and development to mature technology. 31 00:02:08,760 --> 00:02:22,440 One definition of a public-private partnership is a public entity, a representation of government, invests resources, dollars, and a private entity, maybe Pella, 32 00:02:23,160 --> 00:02:27,440 invest resources or dollars in a partnership, a public-private partnership. 33 00:02:28,200 --> 00:02:45,400 And I think it's an important element as we try and transition technologies in key areas that the government has a role in that, but also to ensure successful realization of those technologies by industry, private sector has to have a role as well. 34 00:02:45,400 --> 00:02:51,160 So that's public-private partnerships, and we're all already talking about AI for manufacturing, so I don't need to explain that. 35 00:02:52,600 --> 00:02:58,840 So one of the things that I often forget is that not everybody lives in the Washington, D.C. 36 00:02:58,840 --> 00:03:05,160 area and studies the anatomy of the federal government and understands departments and mission spaces and all that kind of stuff. 37 00:03:05,400 --> 00:03:08,520 Manufacturing has a complicated footprint into the federal government. 38 00:03:09,720 --> 00:03:14,440 You know, each of the members of the president's cabinet has a stake in manufacturing. 39 00:03:15,160 --> 00:03:16,920 All of them, not just one or two. 40 00:03:16,920 --> 00:03:18,440 There's no Department of Manufacturing. 41 00:03:18,440 --> 00:03:21,600 I don't know if anybody noticed that, but there's no Department of Manufacturing. 42 00:03:21,600 --> 00:03:22,800 It doesn't exist in this country. 43 00:03:23,880 --> 00:03:25,440 We do have the Department of Commerce. 44 00:03:25,440 --> 00:03:28,200 So the first column, economic competitiveness. 45 00:03:28,440 --> 00:03:34,680 That's kind of where the Department of Commerce is looking to advance things on behalf of the country. 46 00:03:34,680 --> 00:03:37,240 We want a highly competitive 47 00:03:37,640 --> 00:03:38,360 economy. 48 00:03:38,600 --> 00:03:47,560 We're in a, not a war, not a battle, but we are actively in a competition with every other country on the planet. 49 00:03:47,720 --> 00:03:51,480 They're all trying to succeed economically. 50 00:03:51,480 --> 00:03:56,280 We're trying to succeed economically, and we want to be highly competitive. 51 00:03:56,280 --> 00:04:02,360 We want to win a lot of the time, and we always want to be in the race across the globe, across all parts of the economy. 52 00:04:03,000 --> 00:04:05,800 An important part of that is bringing innovative products into the marketplace. 53 00:04:07,160 --> 00:04:19,160 The Department of War, previously the Department of Defense, as well as a couple of other departments, have really significant footprints into national security and manufactured products, manufacturing. 54 00:04:19,400 --> 00:04:23,400 It's a core element of how we defend our national security. 55 00:04:23,400 --> 00:04:32,600 So Department of War, absolutely, you know, all the planes and tanks, munitions, lots and lots of other things, not just that, but those are things that we can all relate to. 56 00:04:32,760 --> 00:04:36,800 Battleships, you know, those are all products that have to be 57 00:04:36,880 --> 00:04:37,320 made. 58 00:04:37,640 --> 00:04:42,440 And if we want to have the best products, we have to innovate how we make them and what technologies we make them with. 59 00:04:42,720 --> 00:04:44,280 And then finally, energy security. 60 00:04:44,360 --> 00:04:50,520 It's a critical part of our trade and our relationship with other countries on the globe. 61 00:04:50,760 --> 00:04:52,360 Where does our energy come from? 62 00:04:53,720 --> 00:04:55,000 Where does our energy go? 63 00:04:55,240 --> 00:05:00,800 And do we have a reliable and secure and stably priced supply 64 00:05:00,880 --> 00:05:01,640 supply of energy. 65 00:05:01,960 --> 00:05:03,800 So the Department of Energy has a stake in this. 66 00:05:04,040 --> 00:05:11,400 All three of these departments have been sponsors of public-private partnerships to advance manufacturing called the Manufacturing USA Institutes. 67 00:05:11,800 --> 00:05:15,320 Mike referred to them in his introductory remarks. 68 00:05:20,280 --> 00:05:29,160 We as a nation for the last 70 years have been the pioneer in innovative thought. 69 00:05:30,120 --> 00:05:31,400 We're very creative. 70 00:05:32,520 --> 00:05:42,760 As a nation, one of the things that we tend to lose sight of, and I know I heard Paul say it several times, but not everybody was necessarily in the room. 71 00:05:43,080 --> 00:05:46,040 Essentially, fail fast, fail cheap is a different way of saying it. 72 00:05:46,120 --> 00:05:49,880 But let's back up from the fail fast part. 73 00:05:50,120 --> 00:05:50,680 Fail. 74 00:05:52,280 --> 00:05:54,200 It's okay in this country to fail. 75 00:05:54,280 --> 00:05:55,520 You go out, you innovate, 76 00:05:55,960 --> 00:05:58,920 You trip, you skin your knee, you get up, you do it again. 77 00:05:59,160 --> 00:06:01,480 You trip, you skin your knee, you get up, you do it again. 78 00:06:01,720 --> 00:06:05,400 In many other cultures around the world, you skin your knee once, you're done. 79 00:06:05,400 --> 00:06:06,600 You're A second-class citizen. 80 00:06:07,400 --> 00:06:09,520 No one will give you the chance to go innovate again. 81 00:06:09,520 --> 00:06:11,080 No one will invest in your idea. 82 00:06:11,400 --> 00:06:17,120 We are remarkably resilient and tolerant of failure in our thought leaders, in our innovators. 83 00:06:17,320 --> 00:06:22,040 We are still best in the world at innovating ideas and inventions. 84 00:06:23,560 --> 00:06:25,000 We are not best in the world 85 00:06:25,720 --> 00:06:28,760 at translating those inventions into products that are made here. 86 00:06:29,160 --> 00:06:30,680 There's been a variety of studies. 87 00:06:30,680 --> 00:06:33,320 They don't do all 170-some nations. 88 00:06:33,320 --> 00:06:37,160 They do like the 40 nations in the OECD or something like that. 89 00:06:37,560 --> 00:06:39,880 And, you know, we're not always dead last. 90 00:06:40,040 --> 00:06:43,480 Just everybody take some solace in that. 91 00:06:43,560 --> 00:06:48,720 Whatever the list is, 20 countries, 40 countries, you know, sometimes we even make the top 10. 92 00:06:48,720 --> 00:06:50,440 But we are not number one. 93 00:06:53,240 --> 00:07:06,520 The institutes were created as an element of supporting that need of transitioning technologies from something that you can demonstrate in the laboratory of any of our world-class universities. 94 00:07:07,320 --> 00:07:13,560 But if we're talking, say, chemicals, do you make something in a beaker? 95 00:07:13,560 --> 00:07:15,240 Do you make it in a bucket? 96 00:07:15,800 --> 00:07:16,840 Do you make it in a vat? 97 00:07:17,400 --> 00:07:19,600 Or do you make it in a building-sized silo? 98 00:07:19,640 --> 00:07:22,360 You have to scale from beaker 99 00:07:22,760 --> 00:07:23,560 to silo. 100 00:07:24,040 --> 00:07:31,400 And the problem changes as you go through each of those steps in scale, and there's technology maturation that has to go with it. 101 00:07:31,720 --> 00:07:39,720 Just because it works with 12 PhDs babysitting it in a lab in a beaker does not mean that it will work in the silo. 102 00:07:40,200 --> 00:07:40,920 It won't. 103 00:07:41,480 --> 00:07:44,040 There's work to be done there, and somebody has to pay for it. 104 00:07:44,280 --> 00:07:46,120 We do a great job at the beaker. 105 00:07:46,120 --> 00:07:47,120 We are world leading. 106 00:07:47,800 --> 00:07:50,440 We are not world leading getting it all the way to the silo. 107 00:07:55,960 --> 00:08:02,600 So we want to address all three of the departmental missions that I mentioned, economic security, national security, energy security. 108 00:08:03,240 --> 00:08:10,840 There's A confluence of those interests in manufacturing and in the technology areas that the Manufacturing USA Institutes have been selected to focus on. 109 00:08:11,080 --> 00:08:17,280 So some of the institutes are sponsored out of the Department of Energy, some out of the Department of Defense, some out of the Department of Commerce. 110 00:08:17,320 --> 00:08:18,640 We work together as a team. 111 00:08:18,640 --> 00:08:21,400 They're coordinated through an office at NIST. 112 00:08:21,960 --> 00:08:28,120 But they're all there to bring the people, ideas, and technology to cross that gap, to mature those technologies. 113 00:08:29,360 --> 00:08:30,440 I keep looking at the laptop. 114 00:08:30,440 --> 00:08:31,400 It's just habit. 115 00:08:32,520 --> 00:08:32,880 It's okay. 116 00:08:32,880 --> 00:08:33,440 It's okay. 117 00:08:35,320 --> 00:08:42,360 You know, I know I'm the last thing before Paul closes us out, and I probably have just a couple more slides, so I'm going to skip this one. 118 00:08:42,680 --> 00:08:46,680 There's goals, and they involve like workforce and stuff and themes that you guys have been talking about. 119 00:08:47,360 --> 00:08:49,320 Because I want to spend a little bit of time on this. 120 00:08:51,240 --> 00:08:53,800 Is this a pointer? 121 00:08:55,640 --> 00:08:58,360 I think I'm going to turn the whole screen off if I push that button. 122 00:08:58,440 --> 00:08:58,760 Okay. 123 00:08:59,240 --> 00:08:59,480 All right. 124 00:08:59,480 --> 00:09:01,160 So I'm going to not push that button. 125 00:09:01,160 --> 00:09:02,120 I don't want to turn the screen off. 126 00:09:02,120 --> 00:09:03,800 The screen will imagine what you're pointing out. 127 00:09:04,680 --> 00:09:07,320 Government universities are in the hump on the left. 128 00:09:08,280 --> 00:09:08,920 Oh, yeah. 129 00:09:10,040 --> 00:09:11,560 Land grant university. 130 00:09:12,200 --> 00:09:17,640 Iowa State, fantastic R1 university doing loads of wonderful research work. 131 00:09:17,960 --> 00:09:20,600 Almost all of it paid for by the federal government. 132 00:09:20,600 --> 00:09:22,360 Not quite all, but almost all of it. 133 00:09:22,680 --> 00:09:38,040 So there's the government in the left part where the government is actually doing the work, like in a federal lab, but the vast majority of research being conducted at our leading research universities is paid for by the federal government. 134 00:09:38,440 --> 00:09:41,080 So this is the public side of the public-private partnership. 135 00:09:41,320 --> 00:09:45,880 But as you go to make the silo, as you go to scale, that's over on the right-hand side. 136 00:09:46,280 --> 00:09:53,960 The amount of money that it takes to do that per technology is massive and much bigger than the government puts into the equation. 137 00:09:54,200 --> 00:09:56,360 That's why the right hump is taller than the left hump. 138 00:09:56,600 --> 00:10:00,000 So that's one of the things that I want to, okay, we do some stuff over here on the left. 139 00:10:00,000 --> 00:10:01,960 We actually do lots of stuff in beakers. 140 00:10:02,200 --> 00:10:04,920 We do 1,000 or 5,000 projects. 141 00:10:05,320 --> 00:10:11,880 and three of them or five of them are ready to then cross over the valley and get scaled. 142 00:10:12,600 --> 00:10:19,320 The cost of the five of them to get scaled is more than the cost of the thousand of them to get researched in a lab. 143 00:10:19,640 --> 00:10:21,240 The cost grows dramatically. 144 00:10:23,080 --> 00:10:31,240 Somebody has to pay for that, and we have to come to agreement that the things being done on the left line up with the things on the right. 145 00:10:31,560 --> 00:10:39,720 This is the really critical visual that I hold in my mind, and I'm hoping you all can hold in your minds, the need for the public-private partnership. 146 00:10:39,720 --> 00:10:45,240 The role of the public-private partnership is to narrow the gap between the two humps. 147 00:10:45,960 --> 00:10:50,600 But just as importantly, this is essentially a handoff through the partnership. 148 00:10:50,920 --> 00:10:53,480 Somebody is over here and they hike the ball and they carry it. 149 00:10:53,480 --> 00:10:55,560 Oops, okay, I'm going to put that down. 150 00:10:57,080 --> 00:11:01,240 They hike the ball and they carry it for the 1st 10 yards, dealing with the beaker stuff. 151 00:11:02,440 --> 00:11:09,480 And they hope that 80 yards down the field for the last 10 yards, the company is going to take the ball and cross the goal line. 152 00:11:10,040 --> 00:11:12,840 There's 80 yards in the middle that they've got to work together on. 153 00:11:13,080 --> 00:11:14,600 They've got to line up their direction. 154 00:11:14,600 --> 00:11:17,080 They've got to look at the other barriers on the field. 155 00:11:17,080 --> 00:11:21,080 You know, there's blockers and tacklers and people running at each other. 156 00:11:21,320 --> 00:11:23,320 All of that has to be coordinated. 157 00:11:23,560 --> 00:11:26,840 You don't just start at the 10-yard line and be like, well, I'll just toss it. 158 00:11:27,680 --> 00:11:30,040 And somebody will grab it and run the rest of the way. 159 00:11:31,560 --> 00:11:33,800 You have to line up and be in agreement. 160 00:11:33,800 --> 00:11:53,800 So one of the critical things that I have driven is I want to see the private sector partners that are going to invest on the right hump in the room when we're planning out the beaker project and say, if the beaker project gets to this stage and then we do it in a bucket, what are the things that you're worried about as we go from bucket 161 00:11:54,520 --> 00:11:56,040 to VAT, to silo. 162 00:11:56,280 --> 00:12:07,000 What are the key measures of technological performance and economic performance that are what you need to see so that you will bet your company's future on scaling that technology? 163 00:12:07,000 --> 00:12:09,240 Not you'll embrace it, you'll put a little money in. 164 00:12:09,440 --> 00:12:11,960 No, you're all in, this is your path forward. 165 00:12:12,160 --> 00:12:17,560 What do you need from us in the early stage so that your confidence level is much higher in the later stage? 166 00:12:18,600 --> 00:12:18,880 All right. 167 00:12:22,200 --> 00:12:22,840 It did change. 168 00:12:24,520 --> 00:12:25,240 That's changed. 169 00:12:26,200 --> 00:12:26,600 Okay. 170 00:12:27,480 --> 00:12:27,760 All right. 171 00:12:29,960 --> 00:12:32,280 So we've got 17 institutes live today. 172 00:12:32,920 --> 00:12:36,680 We have coverage in all 50 states plus Puerto Rico, much like the MEP program. 173 00:12:38,120 --> 00:12:45,080 In addition to the three sponsoring institutes on the right, we have 9 partner federal agencies that are also investing in the network. 174 00:12:45,400 --> 00:12:51,640 To whatever degree the federal government is coming together on priorities in advanced manufacturing, this is the program where it happens. 175 00:12:52,120 --> 00:12:53,280 Are we doing a great job? 176 00:12:53,640 --> 00:12:54,000 No. 177 00:12:54,520 --> 00:12:56,040 I give us like a C minus. 178 00:12:57,160 --> 00:13:01,560 We're doing a great job with the resources that we have, but we're dramatically under-resourced. 179 00:13:01,960 --> 00:13:09,000 The type of thing that we're trying to do, the opportunity space that we're operating in, we could do 100 times as much activity easily. 180 00:13:10,120 --> 00:13:12,520 But we don't have 100 times as much money. 181 00:13:12,840 --> 00:13:15,240 So just so I'm clear, that's the reason for the C minus. 182 00:13:18,120 --> 00:13:20,440 So we have 17 institutes, 183 00:13:22,200 --> 00:13:25,160 loosely grouped into the five themes here. 184 00:13:25,480 --> 00:13:27,480 You may see some familiar logos. 185 00:13:29,880 --> 00:13:39,000 Anybody just, if you've heard of one of these institutes before, or if you've heard of the Manufacturing USA Institutes, can I just get a show of hands? 186 00:13:39,000 --> 00:13:41,320 Like what are we, what's our, okay. 187 00:13:42,280 --> 00:13:45,960 So like I'm gonna say less than, somewhere around 10% of the room. 188 00:13:46,360 --> 00:13:47,600 The most of you, 189 00:13:48,560 --> 00:13:51,000 have not really had exposure to these. 190 00:13:51,320 --> 00:14:00,200 The electronics, I think, is self-explanatory, and the materials as a theme area. 191 00:14:00,440 --> 00:14:07,480 The digital and automation, because we're here to talk about AI, I want to just talk a little bit about digital and automation before I close out. 192 00:14:09,240 --> 00:14:18,000 And I'm going to start with the Smart Manufacturing Institute, which I helped launch in 2000. 193 00:14:19,840 --> 00:14:23,080 And essentially I would say everything, and it's called SESME. 194 00:14:23,080 --> 00:14:29,080 Everything that SESME has done from the very beginning is really just gearing up for better AI implementation. 195 00:14:29,560 --> 00:14:36,360 We didn't necessarily know it then, but that's, it's just, I'm going to say that's just a true statement. 196 00:14:36,400 --> 00:14:37,560 I don't need to defend it. 197 00:14:37,560 --> 00:14:38,440 It's just true. 198 00:14:39,000 --> 00:14:39,880 everything that they're doing. 199 00:14:40,200 --> 00:14:41,800 They're instrumenting processes. 200 00:14:41,800 --> 00:14:43,000 They're structuring data. 201 00:14:43,240 --> 00:14:50,360 They're basically creating an enterprise that is much more friendly to the application and utilization of AI. 202 00:14:50,360 --> 00:14:56,440 They were doing it for other reasons, but now that they've been doing it, all of that infrastructure is in place. 203 00:14:56,440 --> 00:15:03,800 On the far right, digital manufacturing, MXD, 204 00:15:04,760 --> 00:15:05,960 headquartered in Chicago. 205 00:15:06,200 --> 00:15:07,240 Similar kind of thing. 206 00:15:07,240 --> 00:15:15,520 It's basically trying from idea to customer support, full digitalization of all product information. 207 00:15:15,520 --> 00:15:21,720 We're going to track everything about the product from the very beginning to the very end of life, including disposal and recycling. 208 00:15:21,960 --> 00:15:23,960 We're going to have an electronic footprint. 209 00:15:23,960 --> 00:15:28,480 We're going to have a digital model of everything we need to know about that and seamlessly interconnected. 210 00:15:28,480 --> 00:15:34,640 So if you want to think about as you're in the design stage, what happens in the use stage, you have a model that informs that. 211 00:15:35,480 --> 00:15:39,160 Again, that's like an information superhighway for AI applications. 212 00:15:40,320 --> 00:15:48,920 And then finally out of that list, I want to talk about the Advanced Robotics Institute, ARM, which is headquartered in Pittsburgh, Pennsylvania. 213 00:15:50,760 --> 00:15:52,760 This is really just looking at the use of robots. 214 00:15:54,440 --> 00:16:00,000 We don't have a problem in this nation with robots replacing workers. 215 00:16:00,040 --> 00:16:00,800 That's a common myth. 216 00:16:01,000 --> 00:16:02,120 It's just not true. 217 00:16:02,760 --> 00:16:07,800 If anybody wants to hear my spiel on debunking that, I'll be happy to do that in the networking. 218 00:16:08,040 --> 00:16:10,040 I can understand it is a concern, but it's just not true. 219 00:16:10,520 --> 00:16:13,880 Robots help enterprises be more productive. 220 00:16:14,040 --> 00:16:16,120 It does not help them downsize their workforce. 221 00:16:16,120 --> 00:16:18,280 It helps them upskill their workforce. 222 00:16:19,000 --> 00:16:25,880 And everything that ARM has done has laid the groundwork for more applications to AI, because it's helping them understand 223 00:16:26,400 --> 00:16:33,640 where the value comes from in all of their activities inside their facility, and what can be automated, and what currently we still need people for. 224 00:16:35,080 --> 00:16:37,880 In my mind, that's teeing up the things that we still need people for. 225 00:16:38,120 --> 00:16:44,960 That's because people, in the context of establishing ARM, AI doesn't exist as a tool. 226 00:16:45,640 --> 00:16:49,480 We're looking at robots replacing the physical actions of people. 227 00:16:49,800 --> 00:16:54,600 Now those robots and the software systems around it can be additionally empowered 228 00:16:55,000 --> 00:17:00,120 with the use of AI so that they can do things, additional things that people normally do. 229 00:17:03,480 --> 00:17:03,880 All right. 230 00:17:07,320 --> 00:17:14,600 So we have launched a competition for an 18th institute on the use of AI for resilient manufacturing. 231 00:17:18,360 --> 00:17:20,200 The thing that I forgot to say about the digital 232 00:17:21,560 --> 00:17:23,960 cross-cut that I talked about the three different institutes from. 233 00:17:24,280 --> 00:17:27,240 In some sense, those are all cross-cutting of every other institute. 234 00:17:27,560 --> 00:17:29,480 Every other institute has use for robotics. 235 00:17:29,480 --> 00:17:31,800 Every other institute has use for product information. 236 00:17:32,040 --> 00:17:36,520 Every other institute has manufacturing processes that could be made more smart. 237 00:17:37,160 --> 00:17:41,640 The AI institute is the cross-cut of everything and all of the cross-cuts. 238 00:17:41,960 --> 00:17:48,600 We can take advantage of those superhighways of AI opportunity in the digitization theme. 239 00:17:49,320 --> 00:17:53,000 with AI, but we can also use it for all of the other institutes. 240 00:17:53,240 --> 00:18:01,240 And by the way, all 17 institutes have a portfolio of projects that are currently using AI in their domain, in their work. 241 00:18:01,400 --> 00:18:02,760 They're already using AI. 242 00:18:03,160 --> 00:18:08,840 This institute is not going to be, well, all the AI work happens here, and you guys stop you doing AI. 243 00:18:09,400 --> 00:18:14,320 No, this institute is to help all of the other institutes succeed better at using AI. 244 00:18:16,280 --> 00:18:18,320 So with that, 245 00:18:19,000 --> 00:18:19,680 I'll close out. 246 00:18:19,680 --> 00:18:21,160 I think I'm on time. 247 00:18:21,160 --> 00:18:22,200 Not too bad, really. 248 00:18:22,680 --> 00:18:23,080 Okay. 249 00:18:23,320 --> 00:18:23,720 All right. 250 00:18:24,200 --> 00:18:33,080 So together with all of these institutes, our purpose is to secure America's manufacturing future and mature more things across that valley. 251 00:18:33,320 --> 00:18:37,640 Final comment, and this came out in one of the discussions. 252 00:18:38,280 --> 00:18:46,760 I think the role of the public, of the federal government in investing in early stage technologies as they mature, 253 00:18:47,400 --> 00:18:56,080 There's an interesting flip here because we, the federal government, are not the primary economic driver of AI innovation. 254 00:18:56,080 --> 00:18:57,720 The private sector has taken the lead. 255 00:18:59,160 --> 00:18:59,960 That's not a problem. 256 00:19:00,840 --> 00:19:02,520 We're happy to have the private sector take the lead. 257 00:19:02,600 --> 00:19:03,000 Good. 258 00:19:03,240 --> 00:19:04,320 We don't have to pay for it. 259 00:19:04,320 --> 00:19:05,080 They can pay for it. 260 00:19:06,160 --> 00:19:07,840 And then we can still reap the benefits of it. 261 00:19:08,040 --> 00:19:15,400 But every other technology area, all the other 17 institutes, the government is still pushing on the left-hand side, desperately trying to make it go faster. 262 00:19:15,560 --> 00:19:16,840 We don't need to do that with AI. 263 00:19:16,880 --> 00:19:17,800 That's fantastic. 264 00:19:19,240 --> 00:19:19,560 All right. 265 00:19:21,400 --> 00:19:21,800 Thank you. 266 00:19:30,920 --> 00:19:31,600 I'd like to... 267 00:19:32,360 --> 00:19:33,080 Okay, can you hear me? 268 00:19:33,640 --> 00:19:35,080 Are there any questions? 269 00:19:35,080 --> 00:19:36,360 Do we have one or two questions? 270 00:19:36,360 --> 00:19:38,920 Anybody have any questions right now? 271 00:19:39,160 --> 00:19:40,240 I'd say questions are not. 272 00:19:41,560 --> 00:19:43,480 Okay, totally understandable. 273 00:19:43,880 --> 00:19:45,320 I think this is quite exciting. 274 00:19:45,320 --> 00:19:52,920 The thing that Robert was telling me is that, you know, they're just trying to kind of keep up with 275 00:19:53,400 --> 00:20:00,320 or understand or be able to coordinate what's going on in the AI space now and to bring it into all of this. 276 00:20:00,320 --> 00:20:04,840 And that is quite exciting because coordination could be tremendous. 277 00:20:05,160 --> 00:20:06,840 So thank you very much again. 278 00:20:06,840 --> 00:20:08,080 I really appreciate you coming. 279 00:20:08,120 --> 00:20:13,680 You had to come all the way from the East Coast to our little conference here and we appreciate you being here. 280 00:20:13,680 --> 00:20:15,680 It was a wonderful experience. 281 00:20:15,680 --> 00:20:15,920 Thank you. 282 00:20:15,920 --> 00:20:16,200 Thank you. 283 00:20:16,200 --> 00:20:16,480 All right.