1 00:00:00,090 --> 00:00:02,430 The following content is provided under a Creative 2 00:00:02,430 --> 00:00:03,820 Commons license. 3 00:00:03,820 --> 00:00:06,030 Your support will help MIT OpenCourseWare 4 00:00:06,030 --> 00:00:10,120 continue to offer high-quality educational resources for free. 5 00:00:10,120 --> 00:00:12,660 To make a donation or to view additional materials 6 00:00:12,660 --> 00:00:16,620 from hundreds of MIT courses, visit MIT Open CourseWare 7 00:00:16,620 --> 00:00:17,992 at ocw.mit.edu. 8 00:00:21,550 --> 00:00:24,300 WILLIAM BONVILLIAN: All right, we're going to do two in a row. 9 00:00:24,300 --> 00:00:26,470 And Kevin has got these. 10 00:00:26,470 --> 00:00:29,490 So first we're going to do a snapshot on, gee, could 11 00:00:29,490 --> 00:00:31,410 the Defense Department-- 12 00:00:31,410 --> 00:00:33,930 you remember those guys, with that connected model. 13 00:00:33,930 --> 00:00:35,190 Could they play a role, here? 14 00:00:35,190 --> 00:00:37,790 Is there something useful they can do, here? 15 00:00:37,790 --> 00:00:41,130 And then the second is on this new RPG-- 16 00:00:41,130 --> 00:00:43,710 fairly new-- ARPA-E model that's come about. 17 00:00:43,710 --> 00:00:45,510 So this is Dorothy Robyn. 18 00:00:45,510 --> 00:00:47,215 She was the former Deputy Undersecretary 19 00:00:47,215 --> 00:00:51,000 of Defense for something called Facilities and Environment. 20 00:00:54,180 --> 00:00:57,390 And she worked for, you know, Ash Carter. 21 00:00:57,390 --> 00:00:59,970 DOD had the largest-- 22 00:00:59,970 --> 00:01:04,660 it's the largest facilities owner in the United States. 23 00:01:04,660 --> 00:01:08,460 507 installations and bases, 300,000 buildings, 24 00:01:08,460 --> 00:01:11,280 2.2 billion square feet of space. 25 00:01:11,280 --> 00:01:12,430 That's interesting. 26 00:01:12,430 --> 00:01:12,930 Right? 27 00:01:12,930 --> 00:01:14,760 Maybe they're a test bed. 28 00:01:14,760 --> 00:01:17,220 Right? 29 00:01:17,220 --> 00:01:19,333 And, you know, they do consume more oil 30 00:01:19,333 --> 00:01:21,000 than anybody else in the United States-- 31 00:01:21,000 --> 00:01:21,990 1.7%. 32 00:01:21,990 --> 00:01:25,520 That's not a lot, but still it's a lot of oil. 33 00:01:25,520 --> 00:01:29,130 And they spend a lot on energy every year. 34 00:01:29,130 --> 00:01:33,120 So maybe they've got an interest in some of this. 35 00:01:33,120 --> 00:01:36,540 So, sure enough, DOD actually thinks 36 00:01:36,540 --> 00:01:38,370 it's got an energy problem-- 37 00:01:38,370 --> 00:01:40,170 for some pretty good reasons. 38 00:01:40,170 --> 00:01:43,530 They understand that they have a strategic problem 39 00:01:43,530 --> 00:01:45,470 having to do with worldwide energy supply. 40 00:01:48,490 --> 00:01:55,800 The United States is profoundly dependent on its oil supply. 41 00:01:55,800 --> 00:01:59,640 And that is an international market. 42 00:01:59,640 --> 00:02:05,730 We probably spend a third to a half of our defense 43 00:02:05,730 --> 00:02:11,190 budget on protecting what the military calls 44 00:02:11,190 --> 00:02:14,070 their "lines of communication" around oil-- 45 00:02:14,070 --> 00:02:16,530 i.e., their oil-supply system. 46 00:02:16,530 --> 00:02:18,690 So, cleverly, the oil industry has 47 00:02:18,690 --> 00:02:23,460 managed to get the American taxpayers to foot at least $250 48 00:02:23,460 --> 00:02:26,070 billion a year, protecting their supply system. 49 00:02:26,070 --> 00:02:29,670 That's pretty clever-- a signal of a politically powerful 50 00:02:29,670 --> 00:02:32,790 legacy system. 51 00:02:32,790 --> 00:02:36,180 So there is a deep strategic problem around oil supply. 52 00:02:36,180 --> 00:02:40,040 And then there's a profound tactical set of problems that-- 53 00:02:40,040 --> 00:02:43,680 you know, they've been engaged in two Middle Eastern 54 00:02:43,680 --> 00:02:51,840 wars in the past decade, largely around related to oil supply. 55 00:02:51,840 --> 00:02:56,070 And their own internal energy supply 56 00:02:56,070 --> 00:03:00,220 lines created most of their casualties. 57 00:03:00,220 --> 00:03:00,720 Right? 58 00:03:00,720 --> 00:03:05,400 That's why we lose people, in these painful supply convoys. 59 00:03:05,400 --> 00:03:08,640 It forces the army in particular into a terrible tactical 60 00:03:08,640 --> 00:03:12,300 position of having to defend these fixed points 61 00:03:12,300 --> 00:03:15,090 and concentrate forces to defend these fixed points, 62 00:03:15,090 --> 00:03:17,830 in an asymmetric war where you don't want to have fixed 63 00:03:17,830 --> 00:03:18,330 points. 64 00:03:18,330 --> 00:03:21,390 You want to be part of communities and populations. 65 00:03:21,390 --> 00:03:23,880 So essentially the oil-supply problem 66 00:03:23,880 --> 00:03:26,520 has completely counterdicted everything 67 00:03:26,520 --> 00:03:28,410 the army knows about how it should 68 00:03:28,410 --> 00:03:31,110 fight asymmetric conflicts. 69 00:03:31,110 --> 00:03:33,510 It's forced it into offending long supply chains 70 00:03:33,510 --> 00:03:35,990 to fixed points, which is not a tactical position it 71 00:03:35,990 --> 00:03:37,140 wants to be in. 72 00:03:37,140 --> 00:03:41,140 And it's, in turn, forced many casualties, as a result. 73 00:03:41,140 --> 00:03:44,820 So the Army and the Marine Corps wants to get out of this box. 74 00:03:44,820 --> 00:03:49,920 They want more mobile, flexible, tactically free forces, 75 00:03:49,920 --> 00:03:51,870 to be able to sustain the kind of models 76 00:03:51,870 --> 00:03:56,400 they've developed for optimizing their warfaring capabilities. 77 00:03:56,400 --> 00:03:58,770 So they've got a strategic problem, a tactical problem, 78 00:03:58,770 --> 00:04:01,890 and then they've got a big facilities problem. 79 00:04:01,890 --> 00:04:05,700 DOD has lots of aging, old facilities, 80 00:04:05,700 --> 00:04:09,300 on old, long-established bases, often built 81 00:04:09,300 --> 00:04:13,530 in the World War II time period or the Cold War time period. 82 00:04:13,530 --> 00:04:17,120 They have been, for the last-- since the end of the Cold War-- 83 00:04:17,120 --> 00:04:19,620 under a significant amount of cost pressure. 84 00:04:19,620 --> 00:04:23,400 How can they get their facilities' cost down? 85 00:04:23,400 --> 00:04:26,700 So that's where Dorothy Robyn, who 86 00:04:26,700 --> 00:04:29,580 has the facilities responsibility at DOD, where 87 00:04:29,580 --> 00:04:32,520 she came in. 88 00:04:32,520 --> 00:04:36,000 Interestingly, DOD every year gets $20 billion 89 00:04:36,000 --> 00:04:40,170 in something called "milcon"-- 90 00:04:40,170 --> 00:04:41,310 military construction. 91 00:04:41,310 --> 00:04:44,460 That's for rehabbing, repairing, upgrading, 92 00:04:44,460 --> 00:04:47,820 and undertaking new construction for its facilities and bases. 93 00:04:47,820 --> 00:04:51,720 That's, like, a guaranteed revenue stream. 94 00:04:51,720 --> 00:04:53,503 And you can do a lot of interesting things 95 00:04:53,503 --> 00:04:55,170 with a pretty guaranteed revenue stream. 96 00:04:55,170 --> 00:04:57,780 So one of the things that the Defense Department was 97 00:04:57,780 --> 00:05:00,690 attempting to do is really take advantage of this revenue 98 00:05:00,690 --> 00:05:04,080 stream to do significant facilities upgrades, 99 00:05:04,080 --> 00:05:05,400 in terms of energy uses. 100 00:05:05,400 --> 00:05:10,770 And so that was one of her major projects, there. 101 00:05:10,770 --> 00:05:16,200 So DOD could be a very interesting testbed 102 00:05:16,200 --> 00:05:21,420 and a very interesting initial market for a suite 103 00:05:21,420 --> 00:05:22,630 of new energy technologies. 104 00:05:22,630 --> 00:05:23,130 Right? 105 00:05:23,130 --> 00:05:26,410 So DOD Is not going to do carbon capture and sequestration. 106 00:05:26,410 --> 00:05:26,910 Right? 107 00:05:26,910 --> 00:05:29,070 That's not its problem. 108 00:05:29,070 --> 00:05:32,050 But it sure is interested in getting off the grid. 109 00:05:32,050 --> 00:05:32,610 Right? 110 00:05:32,610 --> 00:05:35,280 It believes it has a terrible cyber security 111 00:05:35,280 --> 00:05:37,170 problem, by being on the grid. 112 00:05:37,170 --> 00:05:39,390 It wants off. 113 00:05:39,390 --> 00:05:42,360 It significantly wants to reduce its energy costs. 114 00:05:42,360 --> 00:05:45,420 It's ready to experiment with renewables, 115 00:05:45,420 --> 00:05:46,920 partly because of the grid strategy, 116 00:05:46,920 --> 00:05:51,290 probably to establish more mobility 117 00:05:51,290 --> 00:05:55,280 and get off fossil fuels line of supplies. 118 00:05:55,280 --> 00:05:58,800 It's got an incredible number of vehicles, 119 00:05:58,800 --> 00:06:02,240 both for military purposes and unmilitary purposes. 120 00:06:02,240 --> 00:06:04,220 That again is another testbed opportunity. 121 00:06:04,220 --> 00:06:08,510 So the idea here, as her testimony laid out, 122 00:06:08,510 --> 00:06:10,760 to one of the armed-services committees, 123 00:06:10,760 --> 00:06:16,310 is that DOD actually could be a partner 124 00:06:16,310 --> 00:06:18,980 in an energy-technology strategy, 125 00:06:18,980 --> 00:06:21,800 as a demonstration and testbed kind of center 126 00:06:21,800 --> 00:06:24,470 and an opportunity to introduce certain kinds of new energy 127 00:06:24,470 --> 00:06:26,030 technologies. 128 00:06:26,030 --> 00:06:29,200 Huge interest in batteries, for example. 129 00:06:29,200 --> 00:06:35,690 So ARPA-E was a gap-filling attempt. 130 00:06:35,690 --> 00:06:40,203 The Department of Energy innovation system, 131 00:06:40,203 --> 00:06:42,620 it's kind of what it looked like before ARPA-E came along. 132 00:06:42,620 --> 00:06:43,120 Right? 133 00:06:43,120 --> 00:06:45,410 The red stuff is the new stuff. 134 00:06:45,410 --> 00:06:48,920 The black and white slides or boxes 135 00:06:48,920 --> 00:06:50,150 are what was there before. 136 00:06:50,150 --> 00:06:53,030 So, before the new stuff arrived, 137 00:06:53,030 --> 00:06:57,230 the Department of Energy had big, fundamental research 138 00:06:57,230 --> 00:06:59,390 organization, very basic research 139 00:06:59,390 --> 00:07:01,880 in areas like particle physics and chemistry. 140 00:07:01,880 --> 00:07:04,770 Famous Vannevar Bush basic research entity-- 141 00:07:04,770 --> 00:07:07,280 the DOE Office of Science. 142 00:07:07,280 --> 00:07:09,770 The great bulk of the energy laboratories 143 00:07:09,770 --> 00:07:12,410 reported through the DOE Office of Science. 144 00:07:12,410 --> 00:07:15,540 They took up about 60% of DOE Office of Science budget. 145 00:07:15,540 --> 00:07:17,680 It was about $5 billion a year. 146 00:07:17,680 --> 00:07:21,560 The energy labs-- one of the largest armies 147 00:07:21,560 --> 00:07:22,640 PhDs in the world. 148 00:07:22,640 --> 00:07:23,352 Right? 149 00:07:23,352 --> 00:07:27,820 An incredible 12,000 army-- 150 00:07:27,820 --> 00:07:29,700 great majority, physicists. 151 00:07:29,700 --> 00:07:33,820 There may be some engineers in there. 152 00:07:33,820 --> 00:07:35,260 It was on the wrong problem. 153 00:07:35,260 --> 00:07:35,830 Right? 154 00:07:35,830 --> 00:07:41,770 It was on the historical nuclear-weapons problem. 155 00:07:41,770 --> 00:07:47,380 So, of the 14 energy labs, the nuclear-weapons laboratories 156 00:07:47,380 --> 00:07:52,720 had about 5,000 of that army of PhDs. 157 00:07:52,720 --> 00:07:56,800 The NREL laboratory, renewable-energy laboratory, 158 00:07:56,800 --> 00:07:59,630 had 340 of the PhDs. 159 00:07:59,630 --> 00:08:00,130 Right? 160 00:08:00,130 --> 00:08:02,890 You can see what the imbalance here is. 161 00:08:02,890 --> 00:08:04,457 It's not the right lineup. 162 00:08:04,457 --> 00:08:06,040 So it was kind of, a lot of the talent 163 00:08:06,040 --> 00:08:07,990 was on the wrong set of issues-- or at least 164 00:08:07,990 --> 00:08:09,370 not the new set of issues. 165 00:08:12,310 --> 00:08:15,670 There was an energy-efficiency and renewable-energy entity, 166 00:08:15,670 --> 00:08:17,230 had about a $2 billion budget. 167 00:08:17,230 --> 00:08:20,320 There was some other applied-energy offices. 168 00:08:20,320 --> 00:08:21,610 That was the landscape. 169 00:08:21,610 --> 00:08:25,420 And then a huge nuclear security kind 170 00:08:25,420 --> 00:08:30,442 of weapons-oriented part and a big cleanup, nuclear-cleanup, 171 00:08:30,442 --> 00:08:31,400 part of the department. 172 00:08:31,400 --> 00:08:33,940 That was kind of the department. 173 00:08:33,940 --> 00:08:36,159 Something that happened under Sam Bodman and then 174 00:08:36,159 --> 00:08:38,620 Steve Chu and then Ernie Moniz is 175 00:08:38,620 --> 00:08:43,669 that that whole picture of that department got reorganized. 176 00:08:43,669 --> 00:08:46,910 One of those pieces was ARPA-E. We'll come back 177 00:08:46,910 --> 00:08:49,200 to this slide in a minute. 178 00:08:49,200 --> 00:08:54,550 ARPA-E was organized to bring a DARPA-like model-- 179 00:08:54,550 --> 00:08:56,480 a breakthrough energy research-- 180 00:08:56,480 --> 00:08:59,290 into a structure that didn't do that. 181 00:08:59,290 --> 00:09:00,140 Right? 182 00:09:00,140 --> 00:09:02,510 The applied agencies worked primarily 183 00:09:02,510 --> 00:09:04,700 with established industry. 184 00:09:04,700 --> 00:09:07,250 There was nobody really working on the breakthrough side. 185 00:09:07,250 --> 00:09:09,023 So, if you happened to think that you 186 00:09:09,023 --> 00:09:10,940 need a lot of breakthrough energy technologies 187 00:09:10,940 --> 00:09:13,880 to solve the climate problem, you probably 188 00:09:13,880 --> 00:09:15,290 need something like this. 189 00:09:15,290 --> 00:09:18,650 So an interesting process got put together, 190 00:09:18,650 --> 00:09:21,968 to get that assembled. 191 00:09:21,968 --> 00:09:24,260 You know, Max, you asked a very good question earlier-- 192 00:09:24,260 --> 00:09:27,950 how come it's only $300 million, when DARPA's $3 billion? 193 00:09:27,950 --> 00:09:32,450 Those of us who were involved in advocating and supporting 194 00:09:32,450 --> 00:09:37,590 the legislation, we wanted a much larger budget, frankly, 195 00:09:37,590 --> 00:09:40,740 a $1-billion kind of budget for ARPA-E-- 196 00:09:40,740 --> 00:09:43,770 and have never politically been able to get there. 197 00:09:43,770 --> 00:09:47,000 But, nonetheless, I would argue that ARPA-E has actually 198 00:09:47,000 --> 00:09:52,400 been a pretty remarkably successful entity. 199 00:09:52,400 --> 00:09:54,890 So ARPA-E does all this stuff that we've 200 00:09:54,890 --> 00:09:56,450 talked about for DARPA. 201 00:09:56,450 --> 00:09:58,790 It's got that model down-- 202 00:09:58,790 --> 00:10:02,120 flat, nonhierarchical, empowered program managers. 203 00:10:02,120 --> 00:10:04,450 They're called "project directors." 204 00:10:04,450 --> 00:10:07,220 Streamlined approval process for both hiring 205 00:10:07,220 --> 00:10:08,990 and for contracting. 206 00:10:08,990 --> 00:10:10,160 It's right-left. 207 00:10:10,160 --> 00:10:12,030 It's challenge-based. 208 00:10:12,030 --> 00:10:14,810 It only wants to do breakthroughs. 209 00:10:14,810 --> 00:10:17,720 It's not going to do incremental work. 210 00:10:17,720 --> 00:10:20,210 It uses island/bridge. 211 00:10:20,210 --> 00:10:24,350 In fact, Arun Majumdar, who was the first head of ARPA-E, 212 00:10:24,350 --> 00:10:27,350 who's one of the most talented science leaders I've ever 213 00:10:27,350 --> 00:10:28,340 seen-- 214 00:10:28,340 --> 00:10:31,880 remarkably talented guy-- he had been-- 215 00:10:31,880 --> 00:10:33,660 Steve Chu, the energy secretary-- 216 00:10:33,660 --> 00:10:37,400 he'd been Steve Chu's deputy at Lawrence Berkeley Laboratory. 217 00:10:37,400 --> 00:10:41,270 So, when Arun moved to Washington, 218 00:10:41,270 --> 00:10:44,580 he lived in Steve Chu's basement for six months. 219 00:10:44,580 --> 00:10:46,540 So there was no island/bridge problem there. 220 00:10:46,540 --> 00:10:47,040 Right? 221 00:10:47,040 --> 00:10:49,940 [LAUGH] You know, they were only a floor away. 222 00:10:49,940 --> 00:10:54,020 There was extremely good communication between the two. 223 00:10:54,020 --> 00:10:56,490 That's the best island/bridge example I know of. 224 00:10:56,490 --> 00:11:00,350 [LAUGH] So I try to bring it up. 225 00:11:00,350 --> 00:11:03,830 But, interestingly, ARPA-E, it didn't 226 00:11:03,830 --> 00:11:09,410 have that connected energy system for innovation. 227 00:11:09,410 --> 00:11:10,100 Right? 228 00:11:10,100 --> 00:11:12,600 Because the Department of Energy doesn't do any procurement. 229 00:11:12,600 --> 00:11:14,060 They don't buy batteries. 230 00:11:14,060 --> 00:11:16,370 They don't buy electric cars. 231 00:11:16,370 --> 00:11:18,410 You know, they don't buy this stuff. 232 00:11:18,410 --> 00:11:21,260 So DOD buys their first round of products. 233 00:11:21,260 --> 00:11:23,750 It can be an initial market creator. 234 00:11:23,750 --> 00:11:25,880 That's one of the advantages DARPA's got. 235 00:11:25,880 --> 00:11:28,640 How does ARPA-E function, when it 236 00:11:28,640 --> 00:11:31,280 doesn't have that follow-on capability embedded 237 00:11:31,280 --> 00:11:33,660 in the department, which it's located? 238 00:11:33,660 --> 00:11:37,370 So it's had to come up with a whole bunch of new approaches 239 00:11:37,370 --> 00:11:39,060 that have really been quite interesting. 240 00:11:39,060 --> 00:11:42,350 And I list some of them in this piece 241 00:11:42,350 --> 00:11:46,340 that I did with a friend and a DARPA expert, Dick VanAtta. 242 00:11:46,340 --> 00:11:48,200 They did a lot of work on how to sharpen 243 00:11:48,200 --> 00:11:50,960 their research-visioning process. 244 00:11:50,960 --> 00:11:55,070 They definitely followed that research-visioning model. 245 00:11:55,070 --> 00:11:59,210 It's not only, is this a cool technology, 246 00:11:59,210 --> 00:12:02,090 but is this a technology that is not only 247 00:12:02,090 --> 00:12:05,360 potentially a breakthrough, but could it actually scale up? 248 00:12:05,360 --> 00:12:08,720 Is it plausible-- do we have a plausible pathway, 249 00:12:08,720 --> 00:12:11,330 by which this technology could come into the marketplace? 250 00:12:11,330 --> 00:12:14,360 And that's definitely part of the research visioning 251 00:12:14,360 --> 00:12:18,020 that ARPA-E undertakes, in a way that DARPA doesn't really 252 00:12:18,020 --> 00:12:21,740 have to because it's got military customers often. 253 00:12:21,740 --> 00:12:24,560 It's done a remarkable job at building a support community. 254 00:12:24,560 --> 00:12:28,190 So ARPA-E, just for one example, it 255 00:12:28,190 --> 00:12:32,480 does what's now become probably the most important US energy 256 00:12:32,480 --> 00:12:34,640 technology summit every year. 257 00:12:34,640 --> 00:12:37,760 They get 2,000 to 3,000 people showing up at this. 258 00:12:37,760 --> 00:12:40,208 Every major energy firm, every venture-capital firm, 259 00:12:40,208 --> 00:12:42,250 they're all there for, like, a three-day session. 260 00:12:42,250 --> 00:12:45,050 They have great speakers-- and amazing technology. 261 00:12:48,070 --> 00:12:50,120 In other words, if you do technology for ARPA-E, 262 00:12:50,120 --> 00:12:51,860 it's going to get showcased. 263 00:12:51,860 --> 00:12:55,925 It's going to get presented to this energy world. 264 00:12:55,925 --> 00:12:57,050 It's going to be shown off. 265 00:12:57,050 --> 00:12:59,240 They're going to help you take that next step. 266 00:12:59,240 --> 00:13:03,050 And, interestingly, in the first summit, 267 00:13:03,050 --> 00:13:06,140 when they put out their first, you know, offer of-- you know, 268 00:13:06,140 --> 00:13:08,060 for proposals-- 269 00:13:08,060 --> 00:13:10,310 which didn't specify areas they wanted to research in; 270 00:13:10,310 --> 00:13:12,440 they just had an open proposal. 271 00:13:12,440 --> 00:13:13,970 Hi, energy community, out there-- 272 00:13:13,970 --> 00:13:16,190 send us your best stuff-- 273 00:13:16,190 --> 00:13:18,560 they expected to get about 400 proposals. 274 00:13:18,560 --> 00:13:20,700 Instead, they got 4,000. 275 00:13:20,700 --> 00:13:21,200 Right? 276 00:13:21,200 --> 00:13:22,617 Because there was so much interest 277 00:13:22,617 --> 00:13:25,880 in working with a DARPA-like thing. 278 00:13:25,880 --> 00:13:26,815 So they were drowning. 279 00:13:26,815 --> 00:13:28,190 They had to invent a whole review 280 00:13:28,190 --> 00:13:30,843 process, to manage all that. 281 00:13:30,843 --> 00:13:32,510 But, interestingly-- and they could only 282 00:13:32,510 --> 00:13:36,540 approve a modest number. 283 00:13:36,540 --> 00:13:42,890 But they invited all the best proposals-- 284 00:13:42,890 --> 00:13:44,660 a much larger number-- 285 00:13:44,660 --> 00:13:49,160 to show up to their first summit and present. 286 00:13:49,160 --> 00:13:52,520 Which helped build a community. 287 00:13:52,520 --> 00:13:54,420 You know, the community felt, hey, 288 00:13:54,420 --> 00:13:56,930 these guys are going to look out for us. 289 00:13:56,930 --> 00:14:01,700 And it created a whole community interest 290 00:14:01,700 --> 00:14:04,640 in what this thing was going to be that has been really quite 291 00:14:04,640 --> 00:14:05,330 successful. 292 00:14:05,330 --> 00:14:07,460 So they've got a strong support community 293 00:14:07,460 --> 00:14:11,660 in the venture-capital community. 294 00:14:11,660 --> 00:14:13,430 They've got strong university support. 295 00:14:13,430 --> 00:14:14,900 They've got established companies 296 00:14:14,900 --> 00:14:17,450 that are working with DARPA-- 297 00:14:17,450 --> 00:14:21,680 supported research and firms. 298 00:14:21,680 --> 00:14:23,270 It's pretty interesting. 299 00:14:23,270 --> 00:14:25,250 The most interesting thing they've been doing 300 00:14:25,250 --> 00:14:30,020 is on the technology-implementation side. 301 00:14:30,020 --> 00:14:35,780 And here, they created their own commercialization team. 302 00:14:35,780 --> 00:14:41,130 So there are these project managers, and they-- 303 00:14:41,130 --> 00:14:44,660 you know, they're empowered, DARPA-like project managers. 304 00:14:44,660 --> 00:14:47,990 But, on their team, they pull in somebody 305 00:14:47,990 --> 00:14:51,570 from ARPA-E's commercialization group. 306 00:14:51,570 --> 00:14:53,390 And these are people with, like, expertise 307 00:14:53,390 --> 00:14:56,570 in getting venture capital and commercializing technology. 308 00:14:56,570 --> 00:15:01,010 They know how larger firms do technology commercialization. 309 00:15:01,010 --> 00:15:03,770 They even have somebody who's expert at military contracting, 310 00:15:03,770 --> 00:15:07,300 so you might sell it to a DOD market. 311 00:15:07,300 --> 00:15:11,000 The commercialization team has a member that's 312 00:15:11,000 --> 00:15:13,200 part of the technology group. 313 00:15:13,200 --> 00:15:14,000 Right? 314 00:15:14,000 --> 00:15:17,990 So commercialization is thought through from the outset 315 00:15:17,990 --> 00:15:20,100 of an ARPA-E technology project. 316 00:15:20,100 --> 00:15:22,600 Because, again, they don't have this big procurement budget. 317 00:15:22,600 --> 00:15:25,580 They've got to find more creative ways around it. 318 00:15:25,580 --> 00:15:30,680 And the greatest compliment so far to ARPA-E and its success-- 319 00:15:30,680 --> 00:15:33,650 DARPA has now copied the model. 320 00:15:33,650 --> 00:15:36,830 So, like, the parent has now copied the child. 321 00:15:36,830 --> 00:15:42,290 And DARPA, earlier this year-- or last year-- 322 00:15:42,290 --> 00:15:45,590 hired ARPA-E's head of their commercialization team 323 00:15:45,590 --> 00:15:48,110 to set up a commercialization team at DARPA. 324 00:15:48,110 --> 00:15:50,260 So, interesting. 325 00:15:50,260 --> 00:15:51,440 Right? 326 00:15:51,440 --> 00:15:56,540 So those are some of the efforts that ARPA-E has been making. 327 00:15:56,540 --> 00:15:58,700 And Kevin and I were talking, earlier, 328 00:15:58,700 --> 00:16:04,130 but ARPA:E did a very thorough, tough-minded evaluation of all 329 00:16:04,130 --> 00:16:06,920 of its research budgets and then issued reports in August 330 00:16:06,920 --> 00:16:08,230 and September. 331 00:16:08,230 --> 00:16:10,047 And it's a pretty fascinating story. 332 00:16:10,047 --> 00:16:11,630 You know, as we know from this class-- 333 00:16:11,630 --> 00:16:13,547 and Kevin and I were just talking about this-- 334 00:16:13,547 --> 00:16:15,890 technology standup takes a long time. 335 00:16:15,890 --> 00:16:17,010 Right? 336 00:16:17,010 --> 00:16:20,710 1947, we do the first mainframe computer. 337 00:16:20,710 --> 00:16:26,150 You know, 1993, the internet and desktop computing are scaling. 338 00:16:26,150 --> 00:16:27,520 That's a long time. 339 00:16:27,520 --> 00:16:28,430 Right? 340 00:16:28,430 --> 00:16:32,200 Fracking happened a lot faster than most technology standups. 341 00:16:32,200 --> 00:16:33,790 That was a 15-year project. 342 00:16:33,790 --> 00:16:37,430 It's paradigm-compatible with the legacy sector, 343 00:16:37,430 --> 00:16:39,720 so that helped, but that was still a 15-year project. 344 00:16:39,720 --> 00:16:42,530 So seven years is much too short a timetable 345 00:16:42,530 --> 00:16:45,920 to be evaluating whether these energy technologies are 346 00:16:45,920 --> 00:16:47,300 going to scale. 347 00:16:47,300 --> 00:16:48,930 But, in terms of technology advance, 348 00:16:48,930 --> 00:16:51,590 and in terms of attracting additional funding from 349 00:16:51,590 --> 00:16:56,020 nongovernmental sources, ARPA-E has had a very good track 350 00:16:56,020 --> 00:16:57,140 record-- 351 00:16:57,140 --> 00:17:00,260 as evidenced in these August and September reports 352 00:17:00,260 --> 00:17:02,180 they've put out. 353 00:17:02,180 --> 00:17:03,570 All right. 354 00:17:03,570 --> 00:17:05,783 All yours, sir. 355 00:17:05,783 --> 00:17:07,200 MARTHA: Can I just ask a question? 356 00:17:07,200 --> 00:17:08,325 WILLIAM BONVILLIAN: Please. 357 00:17:08,325 --> 00:17:10,940 MARTHA: Didn't they announce that basically the companies 358 00:17:10,940 --> 00:17:14,359 had attracted about as much outside funding as they had 359 00:17:14,359 --> 00:17:15,785 spent since our ARPA-E began? 360 00:17:15,785 --> 00:17:16,785 WILLIAM BONVILLIAN: Yes. 361 00:17:16,785 --> 00:17:19,220 And that was composed of two sources-- other federal R&D, 362 00:17:19,220 --> 00:17:19,720 or-- 363 00:17:19,720 --> 00:17:20,660 MARTHA: OK, OK. 364 00:17:20,660 --> 00:17:24,770 WILLIAM BONVILLIAN: --financial support from allied companies 365 00:17:24,770 --> 00:17:26,128 or from venture-capital firms. 366 00:17:26,128 --> 00:17:28,420 And we're going to talk about the venture-capital model 367 00:17:28,420 --> 00:17:28,950 in a bit. 368 00:17:28,950 --> 00:17:29,690 MARTHA: OK. 369 00:17:29,690 --> 00:17:30,140 Sorry for interrupting. 370 00:17:30,140 --> 00:17:32,520 WILLIAM BONVILLIAN: No, but it was a good point to make. 371 00:17:32,520 --> 00:17:34,260 Thank you, Martha. 372 00:17:34,260 --> 00:17:41,390 KEVIN: OK, so, going back to the testimony by Dr. Robyn, 373 00:17:41,390 --> 00:17:46,430 she stated that all these critical facilities 374 00:17:46,430 --> 00:17:50,240 that the DOD depends on for running operations 375 00:17:50,240 --> 00:17:54,720 across the board are so vulnerable. 376 00:17:54,720 --> 00:17:58,280 Why did they let it get to such a point 377 00:17:58,280 --> 00:18:00,150 where, you know, someone needs to tell them, 378 00:18:00,150 --> 00:18:02,790 like, hey, you know, we should innovate in this regard, 379 00:18:02,790 --> 00:18:04,970 to prevent all that from happening. 380 00:18:04,970 --> 00:18:07,010 And, taking those lessons learned, 381 00:18:07,010 --> 00:18:09,470 how should the DOD or any department 382 00:18:09,470 --> 00:18:13,747 really prioritize any proposals that come forward to it? 383 00:18:17,987 --> 00:18:19,820 PERSON: Do you mind rephrasing the question? 384 00:18:19,820 --> 00:18:20,320 KEVIN: Yeah. 385 00:18:20,320 --> 00:18:25,600 So she said these critical systems are really vulnerable. 386 00:18:25,600 --> 00:18:27,760 Here's my proposal. 387 00:18:27,760 --> 00:18:30,370 In the future, or in anyone's opinion, 388 00:18:30,370 --> 00:18:34,450 how should any department and particularly the DOD 389 00:18:34,450 --> 00:18:41,110 prioritize its resources, based on these proposals that they 390 00:18:41,110 --> 00:18:45,940 get, in order to prevent such vulnerabilities from occurring? 391 00:18:45,940 --> 00:18:47,650 STEPH: I can't imagine that this was 392 00:18:47,650 --> 00:18:50,825 published without some of those vulnerabilities being patched. 393 00:18:53,097 --> 00:18:54,680 MARTHA: What do you mean by "patched"? 394 00:18:54,680 --> 00:18:57,263 STEPH: Like, it does not occur to me that the government would 395 00:18:57,263 --> 00:18:59,340 allow-- or, you know, the-- what is she-- 396 00:18:59,340 --> 00:19:01,025 the Deputy Undersecretary of Defense-- 397 00:19:01,025 --> 00:19:01,900 MARTHA: To publicly-- 398 00:19:01,900 --> 00:19:05,790 STEPH: --to publicly announce that these vulnerabilities 399 00:19:05,790 --> 00:19:09,540 exist within their system, in their infrastructure, 400 00:19:09,540 --> 00:19:11,210 without them first being patched. 401 00:19:11,210 --> 00:19:11,710 Right? 402 00:19:11,710 --> 00:19:13,545 And I know that a lot-- 403 00:19:13,545 --> 00:19:15,420 could you talk a little bit about that, Bill? 404 00:19:15,420 --> 00:19:15,800 Because-- 405 00:19:15,800 --> 00:19:16,410 WILLIAM BONVILLIAN: Well, I mean, she's-- 406 00:19:16,410 --> 00:19:17,610 STEPH: --it says that it's hold until released. 407 00:19:17,610 --> 00:19:17,860 WILLIAM BONVILLIAN: Right. 408 00:19:17,860 --> 00:19:20,340 She's testifying in front of the Armed Services Committee, 409 00:19:20,340 --> 00:19:22,620 and they want to know what's going on. 410 00:19:22,620 --> 00:19:25,620 And a witness has got an obligation 411 00:19:25,620 --> 00:19:29,470 to come forward with what the state of affairs is. 412 00:19:29,470 --> 00:19:33,510 You know I don't think these were probably classified-- 413 00:19:33,510 --> 00:19:37,020 I know these weren't classified issues, because this 414 00:19:37,020 --> 00:19:39,960 was an open hearing. 415 00:19:39,960 --> 00:19:44,010 But she's got a responsibility, as a governmental official, 416 00:19:44,010 --> 00:19:46,260 to tell a congressional committee what 417 00:19:46,260 --> 00:19:49,140 in fact is going on and what the issues and vulnerabilities are. 418 00:19:49,140 --> 00:19:52,530 So I think she's doing her job, and the congressional committee 419 00:19:52,530 --> 00:19:53,500 is doing its job. 420 00:19:53,500 --> 00:19:56,073 It's got to probe and find out what the problems are. 421 00:19:56,073 --> 00:19:58,240 I'm not sure that's a great answer to your question. 422 00:19:58,240 --> 00:19:59,573 STEPH: I guess-- does that not-- 423 00:19:59,573 --> 00:20:01,287 I guess, to follow up, would that not 424 00:20:01,287 --> 00:20:02,745 set us up for more vulnerabilities, 425 00:20:02,745 --> 00:20:04,740 if we openly acknowledge that that's something 426 00:20:04,740 --> 00:20:06,450 that we're concerned about? 427 00:20:06,450 --> 00:20:09,270 Just-- and would it not be a problem 428 00:20:09,270 --> 00:20:11,250 that we will find ourselves more into, 429 00:20:11,250 --> 00:20:12,960 if we admit to such vulnerabilities 430 00:20:12,960 --> 00:20:14,842 in a public setting? 431 00:20:14,842 --> 00:20:16,300 MARTHA: Maybe it's already obvious, 432 00:20:16,300 --> 00:20:20,610 if it's been in the press, et cetera. 433 00:20:20,610 --> 00:20:21,730 People dying-- yeah. 434 00:20:21,730 --> 00:20:26,640 STUDENT: And then what they do is particularly surprising. 435 00:20:26,640 --> 00:20:28,140 STEPH: I don't disagree, but I think 436 00:20:28,140 --> 00:20:32,300 it's different to have a deputy undersecretary admitting it-- 437 00:20:32,300 --> 00:20:34,300 is my point. 438 00:20:34,300 --> 00:20:36,970 KEVIN: I think, following up on that, if, you know, 439 00:20:36,970 --> 00:20:39,910 it's not a surprise to anyone, why 440 00:20:39,910 --> 00:20:44,380 are other projects prioritized over preventing this 441 00:20:44,380 --> 00:20:47,110 from happening? 442 00:20:47,110 --> 00:20:49,238 If it's like, oh, well, of course, they're 443 00:20:49,238 --> 00:20:51,280 vulnerable to cyber attacks, and these facilities 444 00:20:51,280 --> 00:20:53,930 are falling apart. 445 00:20:53,930 --> 00:20:57,550 You know, we were just talking about, the dependence on oil 446 00:20:57,550 --> 00:20:59,090 causing a lot of problems. 447 00:20:59,090 --> 00:21:02,223 Why not innovate in that area? 448 00:21:02,223 --> 00:21:04,681 STUDENT: Well, I think part of it goes back to the funding, 449 00:21:04,681 --> 00:21:05,985 from that graph. 450 00:21:05,985 --> 00:21:09,780 You remember that graph, the graph about funding and oil 451 00:21:09,780 --> 00:21:13,050 prices that [INAUDIBLE] follow the same trend? 452 00:21:13,050 --> 00:21:15,010 So, like, if funding isn't really steady, 453 00:21:15,010 --> 00:21:17,950 you can't really innovate very well. 454 00:21:17,950 --> 00:21:19,810 It's hard to maintain facilities. 455 00:21:19,810 --> 00:21:22,580 KEVIN: But you said they get a $20 billion-- 456 00:21:22,580 --> 00:21:24,830 WILLIAM BONVILLIAN: They do have an annual $20-billion 457 00:21:24,830 --> 00:21:27,802 military-construction appropriation 458 00:21:27,802 --> 00:21:30,010 that's potentially an interesting revenue stream that 459 00:21:30,010 --> 00:21:31,755 you could finance off of. 460 00:21:31,755 --> 00:21:33,270 STUDENT: But that's just DOD. 461 00:21:33,270 --> 00:21:35,630 Like, other departments, they still have these problems. 462 00:21:35,630 --> 00:21:37,650 WILLIAM BONVILLIAN: Right, But DOD is the monster in the room. 463 00:21:37,650 --> 00:21:39,692 They're the ones that really have the facilities. 464 00:21:42,090 --> 00:21:44,670 STUDENT: Also, I wonder about the distribution 465 00:21:44,670 --> 00:21:49,290 of the quality, I guess, in facilities or infrastructure. 466 00:21:49,290 --> 00:21:52,350 So I can imagine, not all these 300,000 buildings 467 00:21:52,350 --> 00:21:54,800 are really falling apart and in disrepair. 468 00:21:54,800 --> 00:21:57,810 But I think maybe it's just, they 469 00:21:57,810 --> 00:22:01,010 don't like that there are a number of buildings sort 470 00:22:01,010 --> 00:22:03,270 of on this lighter end of-- 471 00:22:03,270 --> 00:22:05,070 kind of built in World War II-esque, 472 00:22:05,070 --> 00:22:06,870 and they haven't really been upgraded from a construction 473 00:22:06,870 --> 00:22:08,180 or systems point of view. 474 00:22:08,180 --> 00:22:11,625 And I would argue that, like, the $20 billion 475 00:22:11,625 --> 00:22:13,000 or however they're getting yearly 476 00:22:13,000 --> 00:22:16,800 to upgrade these services is adequate or kind of serving 477 00:22:16,800 --> 00:22:22,140 them well, such that those are-- like, that's your patch. 478 00:22:22,140 --> 00:22:27,720 And it's not really an issue of national security, in a sense, 479 00:22:27,720 --> 00:22:31,147 because this is a distributed problem, kind of over the DOD 480 00:22:31,147 --> 00:22:32,730 network, rather than, like, all right, 481 00:22:32,730 --> 00:22:36,780 all of our systems in Virginia or in this particular area 482 00:22:36,780 --> 00:22:40,110 are subject to cyber attack and are vulnerable. 483 00:22:40,110 --> 00:22:42,360 It seems like-- like, it's too big of a problem for it 484 00:22:42,360 --> 00:22:46,782 to be actual information for her, you know, 485 00:22:46,782 --> 00:22:48,240 not to be able to testify about it. 486 00:22:48,240 --> 00:22:49,907 This isn't a national-security interest, 487 00:22:49,907 --> 00:22:51,540 in that it has to be protected. 488 00:22:51,540 --> 00:22:52,080 STEPH: Yeah. 489 00:22:52,080 --> 00:22:54,080 And, to your point about the size of the budget, 490 00:22:54,080 --> 00:22:57,440 I'm looking at the 2017 report on infrastructure management, 491 00:22:57,440 --> 00:22:59,190 from the Government Accountability Office. 492 00:22:59,190 --> 00:23:02,670 And it says that they expect the DOD estimated replacement 493 00:23:02,670 --> 00:23:05,310 value to be $880 billion. 494 00:23:05,310 --> 00:23:07,260 So. 495 00:23:07,260 --> 00:23:07,760 That's a-- 496 00:23:07,760 --> 00:23:09,470 STUDENT: What do you mean by "replacement value"? 497 00:23:09,470 --> 00:23:11,220 STEPH: Well, that's what they're-- for the 498 00:23:11,220 --> 00:23:13,845 infrastructure, for the DOD, that they need to improve 499 00:23:13,845 --> 00:23:14,345 [INAUDIBLE]. 500 00:23:14,345 --> 00:23:15,732 STUDENT: That's a lot of money. 501 00:23:15,732 --> 00:23:17,080 [LAUGHTER] 502 00:23:17,080 --> 00:23:17,830 So that was just-- 503 00:23:17,830 --> 00:23:20,277 I guess that was just released for fiscal year 2017. 504 00:23:20,277 --> 00:23:20,860 STUDENT: Yeah. 505 00:23:20,860 --> 00:23:22,350 I mean, I don't think it's too much an issue 506 00:23:22,350 --> 00:23:23,080 that they released this. 507 00:23:23,080 --> 00:23:24,880 There's this other thing called Zero Days, which 508 00:23:24,880 --> 00:23:26,380 is actually things that you can hack 509 00:23:26,380 --> 00:23:27,940 into infrastructure systems. 510 00:23:27,940 --> 00:23:29,170 And that's more serious. 511 00:23:29,170 --> 00:23:33,690 What they do is, they will report it to the agency. 512 00:23:33,690 --> 00:23:35,733 And, because they know agencies will get lazy, 513 00:23:35,733 --> 00:23:37,900 if you say you're not going to do anything they say, 514 00:23:37,900 --> 00:23:41,522 I'll give you x amount of time until I do report it publicly. 515 00:23:41,522 --> 00:23:43,480 And I think this was an issue that they already 516 00:23:43,480 --> 00:23:45,280 knew it was OK to say publicly. 517 00:23:45,280 --> 00:23:48,400 And so I'm not too concerned with that. 518 00:23:48,400 --> 00:23:51,850 On the issue of actual, oh, this is a problem, 519 00:23:51,850 --> 00:23:54,050 I think it's just more that it's a big government. 520 00:23:54,050 --> 00:23:56,230 There's a lot of problems. 521 00:23:56,230 --> 00:23:58,170 And there isn't really going to be-- you know, 522 00:23:58,170 --> 00:23:59,680 nothing's going to be perfect. 523 00:23:59,680 --> 00:24:01,750 And so they're just trying to bring light to it, 524 00:24:01,750 --> 00:24:04,390 so they can put funds to it. 525 00:24:04,390 --> 00:24:06,110 And things do precipitate, especially 526 00:24:06,110 --> 00:24:07,870 with organizations where-- 527 00:24:07,870 --> 00:24:08,950 I mean, this happens with people all the time. 528 00:24:08,950 --> 00:24:09,090 Right? 529 00:24:09,090 --> 00:24:10,000 You really don't know what you're going 530 00:24:10,000 --> 00:24:11,110 to do, like, a day from now. 531 00:24:11,110 --> 00:24:11,640 Right? 532 00:24:11,640 --> 00:24:13,432 Or a lot of things will add up, and they'll 533 00:24:13,432 --> 00:24:16,250 get past saturation points. 534 00:24:16,250 --> 00:24:18,140 And it's also just a big legacy sector, 535 00:24:18,140 --> 00:24:20,938 so there is going to be issues. 536 00:24:20,938 --> 00:24:22,480 AUDIENCE: Didn't you ask the question 537 00:24:22,480 --> 00:24:24,210 of how should they prioritize? 538 00:24:24,210 --> 00:24:24,990 KEVIN: [INAUDIBLE] 539 00:24:24,990 --> 00:24:26,150 MARTHA: Yeah. 540 00:24:26,150 --> 00:24:28,665 KEVIN: [LAUGH] You know, where should those $20 billion 541 00:24:28,665 --> 00:24:29,290 go, every year? 542 00:24:29,290 --> 00:24:29,790 MARTHA: Mhm? 543 00:24:32,608 --> 00:24:34,900 WOMAN: I just think it's hard, because, to most people, 544 00:24:34,900 --> 00:24:37,720 $20 billion seems like it could solve a lot of problems. 545 00:24:37,720 --> 00:24:39,620 Like, that seems like a lot of money. 546 00:24:39,620 --> 00:24:42,850 But, I guess, when you spread it across all the facilities 547 00:24:42,850 --> 00:24:45,725 that they have, to make a real impact 548 00:24:45,725 --> 00:24:48,940 you really need to pick specific things to focus on. 549 00:24:48,940 --> 00:24:52,180 And then, I think, a lot of politics can come into, like, 550 00:24:52,180 --> 00:24:55,150 who's getting the money and how they're allocating it, 551 00:24:55,150 --> 00:25:00,050 because there's not enough for every base to get an upgrade. 552 00:25:00,050 --> 00:25:02,350 And so I'm sure that's an additional challenge. 553 00:25:02,350 --> 00:25:07,670 STEPH: The report says 562,000 facilities worldwide, 554 00:25:07,670 --> 00:25:09,730 at 4,800 sites. 555 00:25:09,730 --> 00:25:12,785 So that's steep. 556 00:25:12,785 --> 00:25:13,660 STUDENT: $20 billion? 557 00:25:13,660 --> 00:25:14,160 STEPH: Yeah. 558 00:25:17,998 --> 00:25:19,440 STUDENT: It's not too much money. 559 00:25:19,440 --> 00:25:21,690 WILLIAM BONVILLIAN: Kevin, how about a closing thought 560 00:25:21,690 --> 00:25:25,705 on Dorothy Robyn's testimony? 561 00:25:25,705 --> 00:25:30,270 KEVIN: Well, I'm curious to see how the proposal she laid out 562 00:25:30,270 --> 00:25:34,260 has progressed since it was made in 2012. 563 00:25:34,260 --> 00:25:39,735 I would hope that more people bring attention 564 00:25:39,735 --> 00:25:41,110 to this-- like, hey, you know, we 565 00:25:41,110 --> 00:25:45,430 should innovate in these other things that aren't just, like, 566 00:25:45,430 --> 00:25:46,870 weapons. 567 00:25:46,870 --> 00:25:50,990 Because the development of other projects 568 00:25:50,990 --> 00:25:54,667 depends on the development of those, as well. 569 00:25:54,667 --> 00:25:55,750 WILLIAM BONVILLIAN: Right. 570 00:25:55,750 --> 00:25:59,470 And I think it's fair to say that she and colleagues at DOD 571 00:25:59,470 --> 00:26:03,400 actually made significant progress in using 572 00:26:03,400 --> 00:26:06,460 these facilities as, in effect, test beds and demonstration 573 00:26:06,460 --> 00:26:10,060 centers for new technologies. 574 00:26:10,060 --> 00:26:13,450 And, because this is essentially cost-saving and 575 00:26:13,450 --> 00:26:16,780 security-related issues, there's good reason 576 00:26:16,780 --> 00:26:20,020 to think that, under the new administration, a lot of this 577 00:26:20,020 --> 00:26:23,020 will continue. 578 00:26:23,020 --> 00:26:24,575 Let me turn to the ARPA-E piece. 579 00:26:28,460 --> 00:26:31,320 Questions for us, on that one? 580 00:26:31,320 --> 00:26:35,500 KEVIN: So, you know, since you said they just 581 00:26:35,500 --> 00:26:38,860 released a report, analyzing [INAUDIBLE] projects 582 00:26:38,860 --> 00:26:41,850 on the research and the relative success of that, 583 00:26:41,850 --> 00:26:45,910 and because we have evidence files [INAUDIBLE] DARPA 584 00:26:45,910 --> 00:26:49,570 has been, why don't we really hear 585 00:26:49,570 --> 00:26:51,150 about any other DARPA qualms? 586 00:26:51,150 --> 00:26:54,400 You know, they mentioned that the Department of Education was 587 00:26:54,400 --> 00:26:57,815 considering ARPA-E, that the NIH was considering their research 588 00:26:57,815 --> 00:27:00,093 models depending on-- 589 00:27:00,093 --> 00:27:04,540 [LAUGH] that sort of mimic DARPA. 590 00:27:04,540 --> 00:27:07,090 Why aren't innovation models like 591 00:27:07,090 --> 00:27:12,170 the ones in DARPA and ARPA-E being utilized in other fields? 592 00:27:12,170 --> 00:27:13,410 STUDENT: It's possible that-- 593 00:27:13,410 --> 00:27:16,040 this is just an opinion, and I have no facts to back it up-- 594 00:27:16,040 --> 00:27:16,540 but-- 595 00:27:16,540 --> 00:27:17,330 [LAUGHTER] 596 00:27:17,330 --> 00:27:21,230 --it's possible that maybe some of the challenges that 597 00:27:21,230 --> 00:27:25,100 are solved by DARPA and ARPA-E, they don't necessarily 598 00:27:25,100 --> 00:27:26,840 translate as well to social problems, 599 00:27:26,840 --> 00:27:28,820 like Department of Education. 600 00:27:28,820 --> 00:27:34,010 So with education, it's less of a technical problem. 601 00:27:34,010 --> 00:27:36,780 And maybe a lot of it's more, how do we manage people, 602 00:27:36,780 --> 00:27:40,910 how do we determine what's a good versus a bad student, good 603 00:27:40,910 --> 00:27:42,870 versus bad teacher, et cetera. 604 00:27:42,870 --> 00:27:47,350 So I'm not sure if it would fit as well. 605 00:27:47,350 --> 00:27:48,932 Again, opinion. 606 00:27:48,932 --> 00:27:52,100 KEVIN: To add, I think education in particular 607 00:27:52,100 --> 00:27:54,240 would also be considered a legacy sector. 608 00:27:54,240 --> 00:27:57,410 And to stand up, you know, a DARPA-like model for education 609 00:27:57,410 --> 00:27:59,390 would be to completely undermine the education 610 00:27:59,390 --> 00:28:00,980 system in the United States. 611 00:28:00,980 --> 00:28:04,190 And that would require the undertaking 612 00:28:04,190 --> 00:28:08,810 of not only the education system in terms of national standards 613 00:28:08,810 --> 00:28:11,510 but also a reframing fundamentally 614 00:28:11,510 --> 00:28:15,200 at the state level of the ways in which we conduct education 615 00:28:15,200 --> 00:28:16,310 policy. 616 00:28:16,310 --> 00:28:20,510 And that, I think, from a reframing the conversation 617 00:28:20,510 --> 00:28:22,490 nationally, would be an immensely difficult 618 00:28:22,490 --> 00:28:23,060 undertaking. 619 00:28:23,060 --> 00:28:24,230 It would be politically-- 620 00:28:24,230 --> 00:28:26,272 I mean, I don't know if "politically unviable" is 621 00:28:26,272 --> 00:28:27,950 the right word, but it seems to me 622 00:28:27,950 --> 00:28:30,050 like it would be politically insurmountable. 623 00:28:30,050 --> 00:28:33,290 Because you're now threatening, you know, states' rights. 624 00:28:33,290 --> 00:28:34,790 PERSON: Why does it-- 625 00:28:34,790 --> 00:28:37,910 why is it an undermining of the education system I mean, the-- 626 00:28:37,910 --> 00:28:39,500 STEPH: [INTERPOSING VOICES] 627 00:28:39,500 --> 00:28:40,542 PERSON: --defense system. 628 00:28:40,542 --> 00:28:42,583 WILLIAM BONVILLIAN: Let me just give a little bit 629 00:28:42,583 --> 00:28:44,900 of background, because I was involved in some of this. 630 00:28:44,900 --> 00:28:45,870 And it never happened. 631 00:28:45,870 --> 00:28:47,995 And Congress was never interested in funding in it. 632 00:28:47,995 --> 00:28:50,780 And part of it was, you know, what does the Department 633 00:28:50,780 --> 00:28:52,640 of Education-- which is essentially 634 00:28:52,640 --> 00:28:55,740 an entitlement-administration organization-- 635 00:28:55,740 --> 00:28:58,860 what do they know about technology policy in education? 636 00:28:58,860 --> 00:28:59,390 Right? 637 00:28:59,390 --> 00:29:01,790 But, with the development of online capability 638 00:29:01,790 --> 00:29:04,730 and computer-gaming technologies, 639 00:29:04,730 --> 00:29:07,430 a whole new raft of technology options 640 00:29:07,430 --> 00:29:09,140 has entered the education field. 641 00:29:09,140 --> 00:29:13,550 So there was a fair amount of thinking that maybe there 642 00:29:13,550 --> 00:29:16,760 was room for a technology-breakthrough entity 643 00:29:16,760 --> 00:29:17,960 in the education space. 644 00:29:17,960 --> 00:29:21,470 The education space is also notorious 645 00:29:21,470 --> 00:29:24,440 for conducting almost no R&D. Right? 646 00:29:24,440 --> 00:29:25,980 Almost zero. 647 00:29:25,980 --> 00:29:26,480 Right? 648 00:29:26,480 --> 00:29:27,313 It's tragic. 649 00:29:27,313 --> 00:29:27,980 KEVIN: I would-- 650 00:29:27,980 --> 00:29:28,760 WILLIAM BONVILLIAN: And how are you 651 00:29:28,760 --> 00:29:31,152 going to transform a sector without, you know, 652 00:29:31,152 --> 00:29:33,110 undertaking technology development and research 653 00:29:33,110 --> 00:29:34,250 and development on it? 654 00:29:34,250 --> 00:29:37,310 So, agree, it's threatening, right? 655 00:29:37,310 --> 00:29:39,050 Online education and blended learning 656 00:29:39,050 --> 00:29:41,390 are threatening models to establish systems-- 657 00:29:41,390 --> 00:29:44,210 no question about it. 658 00:29:44,210 --> 00:29:48,400 But this was actually, I think, an interesting idea. 659 00:29:48,400 --> 00:29:52,330 The problem was, who's going to find the right technology 660 00:29:52,330 --> 00:29:54,760 crowd that would really create the kind of breakthroughs 661 00:29:54,760 --> 00:29:56,355 that a DARPA-like entity could do? 662 00:29:56,355 --> 00:29:58,147 And I think that was more of the challenge. 663 00:29:58,147 --> 00:29:59,980 KEVIN: And you're saying it's making threats 664 00:29:59,980 --> 00:30:02,060 to establish education models. 665 00:30:02,060 --> 00:30:05,340 Is that necessarily a bad thing, wherein, you know, 666 00:30:05,340 --> 00:30:06,923 we see the US rankings are way below-- 667 00:30:06,923 --> 00:30:09,548 WILLIAM BONVILLIAN: No, I'm not saying it's a bad thing at all. 668 00:30:09,548 --> 00:30:11,430 I think the whole system needs to be changed. 669 00:30:11,430 --> 00:30:14,060 But I agree with you, Kevin. 670 00:30:14,060 --> 00:30:16,458 And this would be a tool to try some of that with. 671 00:30:16,458 --> 00:30:18,250 STUDENT: And it's the big disruption thing. 672 00:30:18,250 --> 00:30:19,980 It's like-- it's like Uber. 673 00:30:19,980 --> 00:30:23,700 So imagine, like, if you really affect the teachers' jobs, 674 00:30:23,700 --> 00:30:24,840 there's all these unions. 675 00:30:24,840 --> 00:30:25,350 Right? 676 00:30:25,350 --> 00:30:27,257 So, like, now a kid can go and, like, 677 00:30:27,257 --> 00:30:28,840 he doesn't-- he still needs a teacher, 678 00:30:28,840 --> 00:30:31,075 but now you've kind of made them very uncomfortable. 679 00:30:31,075 --> 00:30:32,700 So you can get the amount of push-back. 680 00:30:32,700 --> 00:30:33,830 So, when you create this system, you 681 00:30:33,830 --> 00:30:35,288 have to figure out how you're going 682 00:30:35,288 --> 00:30:37,496 to make it so that the teacher doesn't feel offended. 683 00:30:37,496 --> 00:30:39,621 I mean, Kahn Academy did a really good job of this, 684 00:30:39,621 --> 00:30:41,910 of, like, OK, well, now you can spend your time doing 685 00:30:41,910 --> 00:30:44,010 what you do, in the classroom. 686 00:30:44,010 --> 00:30:46,635 But even then, how are you going to get mass support? 687 00:30:46,635 --> 00:30:48,760 And I still don't know what their numbers are like. 688 00:30:48,760 --> 00:30:49,980 STUDENT: Why is the kid uncomfortable? 689 00:30:49,980 --> 00:30:51,570 STUDENT: Not the kid, the teacher. 690 00:30:51,570 --> 00:30:52,528 Because there's unions. 691 00:30:52,528 --> 00:30:54,965 So this is especially important in, like, the-- 692 00:30:54,965 --> 00:30:56,340 Steve Case, the guy who made AOL. 693 00:30:56,340 --> 00:30:59,080 He made a book called The Third Wave, which is, like, you know, 694 00:30:59,080 --> 00:31:00,910 the internet entrepreneurs that will affect 695 00:31:00,910 --> 00:31:03,840 physical structures and not just web 2.0 that is on Facebook 696 00:31:03,840 --> 00:31:06,090 and Snapchat, the people that would create systems 697 00:31:06,090 --> 00:31:08,910 that interact with people like Uber, 698 00:31:08,910 --> 00:31:10,450 they don't just make a technology. 699 00:31:10,450 --> 00:31:14,250 They have to focus on the legacy history of the people 700 00:31:14,250 --> 00:31:15,280 in that organization. 701 00:31:15,280 --> 00:31:16,230 So, when you make an Uber, you have 702 00:31:16,230 --> 00:31:18,522 to worry about the taxi-cab drivers who paid $1 million 703 00:31:18,522 --> 00:31:19,350 for a medallion. 704 00:31:19,350 --> 00:31:21,267 And this is how they're supporting themselves, 705 00:31:21,267 --> 00:31:23,320 and now you're going to disrupt it. 706 00:31:23,320 --> 00:31:25,403 And also, what's going to happen to these drivers? 707 00:31:25,403 --> 00:31:27,600 What about union problems? 708 00:31:27,600 --> 00:31:31,517 How do you ensure safety, as there's been several concerns. 709 00:31:31,517 --> 00:31:32,350 So it's not a tech-- 710 00:31:32,350 --> 00:31:35,585 These aren't-- I think for DARPA and ARPA-E, 711 00:31:35,585 --> 00:31:36,710 there's a technology issue. 712 00:31:36,710 --> 00:31:39,180 Let's do the technology. 713 00:31:39,180 --> 00:31:40,800 For these issues, it's more of a, 714 00:31:40,800 --> 00:31:42,510 this is very much a people technology. 715 00:31:42,510 --> 00:31:43,010 Right? 716 00:31:43,010 --> 00:31:45,460 Like-- And most politicians-- 717 00:31:45,460 --> 00:31:48,347 Michael Bloomberg, Bill Gates, who's a billionaire, 718 00:31:48,347 --> 00:31:49,180 which you all know-- 719 00:31:49,180 --> 00:31:53,070 WILLIAM BONVILLIAN: But, Martín, there still have been-- 720 00:31:53,070 --> 00:31:56,220 look, I mean, how many technological disruptions 721 00:31:56,220 --> 00:31:57,750 of education have there been? 722 00:31:57,750 --> 00:32:01,316 I mean, we came up with the printing press in, what, 1562? 723 00:32:01,316 --> 00:32:02,130 [LAUGHTER] 724 00:32:02,130 --> 00:32:02,820 Right? 725 00:32:02,820 --> 00:32:03,850 That was a big one. 726 00:32:03,850 --> 00:32:04,670 Right? 727 00:32:04,670 --> 00:32:06,270 Books-- we figured out books. 728 00:32:06,270 --> 00:32:07,330 That's about it. 729 00:32:07,330 --> 00:32:07,890 Right? 730 00:32:07,890 --> 00:32:09,870 That's pretty much the change. 731 00:32:09,870 --> 00:32:13,110 So applying this whole new information-technology online 732 00:32:13,110 --> 00:32:18,460 world to the education system, those are profound technology-- 733 00:32:18,460 --> 00:32:22,530 and, I agree, social and learning challenges 734 00:32:22,530 --> 00:32:23,387 go with those. 735 00:32:23,387 --> 00:32:25,470 And they are threatening to establish communities. 736 00:32:25,470 --> 00:32:26,640 I agree completely. 737 00:32:26,640 --> 00:32:29,340 But I do think, interestingly, certainly 738 00:32:29,340 --> 00:32:31,740 for the first time in my lifetime, 739 00:32:31,740 --> 00:32:35,760 I've seen an opportunity for significant technology entry 740 00:32:35,760 --> 00:32:39,310 into a classic legacy sector. 741 00:32:39,310 --> 00:32:43,146 And so the idea of putting a DARPA-like thing around that, 742 00:32:43,146 --> 00:32:45,220 that was an interesting idea. 743 00:32:45,220 --> 00:32:45,720 Right? 744 00:32:45,720 --> 00:32:48,145 It just hasn't happened. 745 00:32:48,145 --> 00:32:49,770 STUDENT: I think I'm going to push back 746 00:32:49,770 --> 00:32:50,480 on this a little bit-- 747 00:32:50,480 --> 00:32:50,780 WILLIAM BONVILLIAN: Please. 748 00:32:50,780 --> 00:32:52,530 STUDENT: --the idea that education doesn't 749 00:32:52,530 --> 00:32:54,930 have a DARPA-like model. 750 00:32:54,930 --> 00:32:57,240 Like, the rise of charter schools, I think, 751 00:32:57,240 --> 00:33:01,020 has really disrupted how we think about the system 752 00:33:01,020 --> 00:33:01,878 of public education. 753 00:33:01,878 --> 00:33:04,170 And you used to really just have public versus private, 754 00:33:04,170 --> 00:33:07,620 but now you have private and, like, quasi public 755 00:33:07,620 --> 00:33:11,040 charter schools that receive federal and state funding 756 00:33:11,040 --> 00:33:14,820 but, like, do state testing but don't do some other things. 757 00:33:14,820 --> 00:33:16,710 And they have the elements that you 758 00:33:16,710 --> 00:33:18,877 think you get in a public education, which is, like, 759 00:33:18,877 --> 00:33:22,092 the group environment, but they focus their classes 760 00:33:22,092 --> 00:33:23,550 and they structure them differently 761 00:33:23,550 --> 00:33:24,630 and they do a whole bunch of other stuff, 762 00:33:24,630 --> 00:33:26,005 because they don't have to adhere 763 00:33:26,005 --> 00:33:28,920 to kind of all of the regulations that 764 00:33:28,920 --> 00:33:31,870 come from the state and the federal government. 765 00:33:31,870 --> 00:33:35,160 And so I would say that education has-- 766 00:33:35,160 --> 00:33:37,500 it's like a distributed-- it is a distributed system, 767 00:33:37,500 --> 00:33:39,260 because it gets, like, more state by state 768 00:33:39,260 --> 00:33:40,968 than, like, really the Federal Department 769 00:33:40,968 --> 00:33:42,810 of Education-mandated things. 770 00:33:42,810 --> 00:33:46,140 But also, in charter schools and things like this, 771 00:33:46,140 --> 00:33:48,498 you have opportunities for different models that are-- 772 00:33:48,498 --> 00:33:50,040 like, people are already testing out, 773 00:33:50,040 --> 00:33:53,370 and you're already seeing this disruption that Martín is 774 00:33:53,370 --> 00:33:56,700 talking about, where you have these entrenched 775 00:33:56,700 --> 00:33:59,790 public-education systems, but now you're having this rival 776 00:33:59,790 --> 00:34:03,240 charter school that now comes in and kind of disrupts 777 00:34:03,240 --> 00:34:04,823 teachers' unions and things like that. 778 00:34:04,823 --> 00:34:06,990 WILLIAM BONVILLIAN: All right, so I'm going to-- you 779 00:34:06,990 --> 00:34:09,070 know, I'm going to halt our education discussion. 780 00:34:09,070 --> 00:34:09,570 Right? 781 00:34:09,570 --> 00:34:10,230 [LAUGHTER] 782 00:34:10,230 --> 00:34:13,440 Because we're going to have a whole class, next week, 783 00:34:13,440 --> 00:34:14,310 on education. 784 00:34:14,310 --> 00:34:18,960 So we can pursue this at length. 785 00:34:18,960 --> 00:34:21,630 This is kind of a breath of what's to come, 786 00:34:21,630 --> 00:34:23,500 in next week's experiment. 787 00:34:23,500 --> 00:34:27,300 But, Kevin, why don't you close out our ARPA-E discussion 788 00:34:27,300 --> 00:34:27,840 with-- 789 00:34:27,840 --> 00:34:30,132 maybe summarize what you thought some of the key points 790 00:34:30,132 --> 00:34:30,870 are about ARPA-E? 791 00:34:34,197 --> 00:34:35,280 KEVIN: It's still growing. 792 00:34:35,280 --> 00:34:39,520 I think-- well, it might not be growing [LAUGH] anymore. 793 00:34:39,520 --> 00:34:44,060 But it's a good proof of concept that the DARPA model and models 794 00:34:44,060 --> 00:34:50,760 like it are good change agents, when they're needed. 795 00:34:50,760 --> 00:34:53,560 Especially in a really established legacy sector 796 00:34:53,560 --> 00:34:56,489 like energy is. 797 00:34:56,489 --> 00:34:59,990 My personal opinion-- I'd like to see these kind of models 798 00:34:59,990 --> 00:35:01,272 applied elsewhere. 799 00:35:01,272 --> 00:35:03,480 You know, I was reading, here, that Homeland Security 800 00:35:03,480 --> 00:35:08,000 intelligence and others were planning their own ARPA models. 801 00:35:08,000 --> 00:35:10,635 And, even on smaller scales, I feel like this innovation model 802 00:35:10,635 --> 00:35:13,303 could be really beneficial. 803 00:35:13,303 --> 00:35:14,345 WILLIAM BONVILLIAN: Good. 804 00:35:14,345 --> 00:35:14,660 OK. 805 00:35:14,660 --> 00:35:15,080 STUDENT: I have one more question, 806 00:35:15,080 --> 00:35:16,700 because we were talking about innovation organizations. 807 00:35:16,700 --> 00:35:17,990 I was wondering if there was an innovation 808 00:35:17,990 --> 00:35:20,110 organization for manufacturing, because that's 809 00:35:20,110 --> 00:35:21,952 a focus of yours. 810 00:35:21,952 --> 00:35:24,410 WILLIAM BONVILLIAN: There are these brand-new manufacturing 811 00:35:24,410 --> 00:35:25,130 institutes. 812 00:35:25,130 --> 00:35:26,880 And there's 14 of these. 813 00:35:26,880 --> 00:35:31,130 And they are organized around major technology challenges 814 00:35:31,130 --> 00:35:32,525 in the manufacturing space. 815 00:35:32,525 --> 00:35:33,650 STUDENT: Could you specify? 816 00:35:33,650 --> 00:35:35,710 WILLIAM BONVILLIAN: So, 3D printing. 817 00:35:35,710 --> 00:35:38,780 You know, what technology advances are we going to get 818 00:35:38,780 --> 00:35:40,250 out of that, whether it's-- 819 00:35:40,250 --> 00:35:43,847 there's an institute around tissue engineering 820 00:35:43,847 --> 00:35:44,930 and regenerative medicine. 821 00:35:44,930 --> 00:35:46,710 There's an institute around photonics. 822 00:35:46,710 --> 00:35:49,610 There's an institute around power electronics 823 00:35:49,610 --> 00:35:51,070 and wideband-gap semiconductors. 824 00:35:51,070 --> 00:35:54,690 There's an institute around advanced composites. 825 00:35:54,690 --> 00:35:57,680 So, in 14 different interesting technology areas 826 00:35:57,680 --> 00:36:02,480 that could be quite powerful, across a range of manufacturing 827 00:36:02,480 --> 00:36:04,910 sectors, we are attempting an innovation model. 828 00:36:04,910 --> 00:36:06,830 It's a public-private collaboration. 829 00:36:06,830 --> 00:36:08,900 STUDENT: So they try to do best practices in standardization? 830 00:36:08,900 --> 00:36:10,442 WILLIAM BONVILLIAN: Well, no, they're 831 00:36:10,442 --> 00:36:12,210 attempting to do technology development. 832 00:36:12,210 --> 00:36:13,490 So, TRA level-- 833 00:36:13,490 --> 00:36:19,100 TRL levels 4 through 7, kind of, mid- to later-stage technology 834 00:36:19,100 --> 00:36:22,215 development efforts, tying that to the communities that 835 00:36:22,215 --> 00:36:24,090 would have to be involved if these models are 836 00:36:24,090 --> 00:36:25,820 going to get picked up. 837 00:36:25,820 --> 00:36:29,100 So it's an interesting-- it's the first attempt, really, 838 00:36:29,100 --> 00:36:33,560 in the US, other than SEMATECH, to bring an innovation model 839 00:36:33,560 --> 00:36:35,000 to the manufacturing sector. 840 00:36:35,000 --> 00:36:36,980 STUDENT: Do these manufacturing institutes 841 00:36:36,980 --> 00:36:39,290 follow one general innovation model? 842 00:36:39,290 --> 00:36:42,270 Or does each one cater to whatever-- 843 00:36:42,270 --> 00:36:44,610 WILLIAM BONVILLIAN: Each one is-- 844 00:36:44,610 --> 00:36:46,100 they share a lot of similarities. 845 00:36:46,100 --> 00:36:47,060 They're all cost-share. 846 00:36:47,060 --> 00:36:48,710 They involve small and large firms. 847 00:36:48,710 --> 00:36:51,230 They involve university with strong technology 848 00:36:51,230 --> 00:36:52,670 and engineering programs. 849 00:36:52,670 --> 00:36:54,077 They involve community colleges. 850 00:36:54,077 --> 00:36:55,660 They have workforce-development model. 851 00:36:55,660 --> 00:36:57,690 So they share those pieces. 852 00:36:57,690 --> 00:36:59,570 But then the particular technology area 853 00:36:59,570 --> 00:37:01,408 they're pursuing means they're going to be 854 00:37:01,408 --> 00:37:02,700 organized somewhat differently. 855 00:37:02,700 --> 00:37:06,590 So the one MIT is leading, on revolutionary fibers, 856 00:37:06,590 --> 00:37:09,500 that's got a different approach and a different kind of sector, 857 00:37:09,500 --> 00:37:13,370 frankly, than the composite sector. 858 00:37:13,370 --> 00:37:15,770 So it's an interesting attempt to bring innovation 859 00:37:15,770 --> 00:37:20,210 into a long-standing legacy sector where the federal 860 00:37:20,210 --> 00:37:22,610 innovation system never really played any role-- 861 00:37:22,610 --> 00:37:24,330 except for SEMATECH. 862 00:37:24,330 --> 00:37:29,450 So let me turn to this kind of Plan B idea. 863 00:37:29,450 --> 00:37:33,080 The idea here was, you know, we're 864 00:37:33,080 --> 00:37:37,250 not going to do a cap-and-trade proposal anytime soon. 865 00:37:37,250 --> 00:37:38,800 So what do we do? 866 00:37:38,800 --> 00:37:41,630 You know, what's the menu of options, if we actually want 867 00:37:41,630 --> 00:37:43,220 to deal with climate change? 868 00:37:43,220 --> 00:37:45,680 And one of the problems-- look, I 869 00:37:45,680 --> 00:37:50,630 was involved in drafting the original Senate climate-change 870 00:37:50,630 --> 00:37:51,298 legislation. 871 00:37:51,298 --> 00:37:53,090 And one of the problems in that legislation 872 00:37:53,090 --> 00:37:57,710 was, we were attempting an economy-wide fix, 873 00:37:57,710 --> 00:38:01,880 based upon a neoclassical economic concept 874 00:38:01,880 --> 00:38:05,900 that you could alter prices and drive change. 875 00:38:05,900 --> 00:38:09,930 And it turned out to be more complicated than that. 876 00:38:09,930 --> 00:38:11,150 Right? 877 00:38:11,150 --> 00:38:14,640 First of all, it's hard to get an economy-wide model imposed. 878 00:38:14,640 --> 00:38:16,640 It's hard to nail everybody at the same time. 879 00:38:16,640 --> 00:38:17,140 Right? 880 00:38:17,140 --> 00:38:20,300 The political system tends to resist this. 881 00:38:20,300 --> 00:38:22,100 In economic terms, it's very interesting 882 00:38:22,100 --> 00:38:25,200 to impose an economy-wide model, but it's hard. 883 00:38:25,200 --> 00:38:29,900 And then, secondly-- well, I had actually 884 00:38:29,900 --> 00:38:35,070 worked on the original acid-rain provisions 885 00:38:35,070 --> 00:38:37,670 the Clean Air Act of 1990, legislation 886 00:38:37,670 --> 00:38:40,730 to develop a cap-and-trade system there. 887 00:38:40,730 --> 00:38:43,340 It worked brilliantly, and it was a stalking horse 888 00:38:43,340 --> 00:38:46,800 for what we knew we were going to do on the climate layer. 889 00:38:46,800 --> 00:38:49,560 And cap-and-trade worked brilliantly, there. 890 00:38:49,560 --> 00:38:52,470 It worked brilliantly, because we already had the technology 891 00:38:52,470 --> 00:38:54,840 solutions at hand. 892 00:38:54,840 --> 00:38:56,565 They could be the scrubbers that we 893 00:38:56,565 --> 00:39:00,120 were going to put on smokestacks in Midwestern power plants. 894 00:39:00,120 --> 00:39:02,250 We knew the technology was there. 895 00:39:02,250 --> 00:39:05,730 So a pricing system could really drive, very quickly, 896 00:39:05,730 --> 00:39:08,940 the forced adoption of that technology. 897 00:39:08,940 --> 00:39:13,410 When we did cap-and-trade, it took us a while 898 00:39:13,410 --> 00:39:16,770 to understand that a lot of the technologies were not close. 899 00:39:16,770 --> 00:39:18,840 They were still a considerable distance away. 900 00:39:18,840 --> 00:39:21,570 We've talked about carbon capture and sequestration. 901 00:39:21,570 --> 00:39:22,450 It's a good example. 902 00:39:22,450 --> 00:39:22,950 Right? 903 00:39:22,950 --> 00:39:26,820 It's not ready for deployment at large scale, at this point. 904 00:39:26,820 --> 00:39:28,740 It's still experimental. 905 00:39:28,740 --> 00:39:31,980 So it wasn't a great fit. 906 00:39:31,980 --> 00:39:33,773 So obviously the industries that were 907 00:39:33,773 --> 00:39:35,190 going to be affected by this, they 908 00:39:35,190 --> 00:39:37,470 didn't know what their pathways were going to be, 909 00:39:37,470 --> 00:39:38,940 in many cases. 910 00:39:38,940 --> 00:39:39,630 Right? 911 00:39:39,630 --> 00:39:41,753 And, look, in many sectors, look at transport. 912 00:39:41,753 --> 00:39:43,545 We don't know if it's going to be biofuels. 913 00:39:43,545 --> 00:39:45,100 We don't know if it's going to be electrics. 914 00:39:45,100 --> 00:39:46,980 We don't know if it's going to be hybrids. 915 00:39:46,980 --> 00:39:48,420 We don't know what it's going to-- or maybe just 916 00:39:48,420 --> 00:39:50,760 significant improvements to internal combustion engines. 917 00:39:50,760 --> 00:39:53,382 All those pieces are still very much on the table, 918 00:39:53,382 --> 00:39:54,840 in the transport sector-- obviously 919 00:39:54,840 --> 00:39:56,530 a huge economic sector. 920 00:39:56,530 --> 00:40:01,862 So one of the problems with cap-and-trade and neoclassical 921 00:40:01,862 --> 00:40:04,320 model was that it didn't have a sophisticated understanding 922 00:40:04,320 --> 00:40:06,180 of the technology policy side. 923 00:40:06,180 --> 00:40:09,080 And I wish I had understood that then, but-- 924 00:40:09,080 --> 00:40:09,663 WOMAN: [LAUGH] 925 00:40:09,663 --> 00:40:11,205 WILLIAM BONVILLIAN: --and obviously I 926 00:40:11,205 --> 00:40:12,480 wasn't the only actor. 927 00:40:12,480 --> 00:40:16,923 And, overall, I think a price solution 928 00:40:16,923 --> 00:40:18,090 is going to be needed, here. 929 00:40:18,090 --> 00:40:20,170 But meanwhile, can we make progress? 930 00:40:20,170 --> 00:40:22,830 So part of the way in which we can make progress 931 00:40:22,830 --> 00:40:25,830 is by a considerably more sophisticated and effective 932 00:40:25,830 --> 00:40:28,500 technology strategy. 933 00:40:28,500 --> 00:40:30,210 After this book was-- 934 00:40:30,210 --> 00:40:34,197 after the book that this chapter appeared in was written, 935 00:40:34,197 --> 00:40:36,030 obviously there was a major political change 936 00:40:36,030 --> 00:40:37,073 in the United States. 937 00:40:37,073 --> 00:40:38,490 So the changes we're going to have 938 00:40:38,490 --> 00:40:40,680 to think about, if we're going to do a Plan B 939 00:40:40,680 --> 00:40:44,010 and I just sit on our hands for the next decade, 940 00:40:44,010 --> 00:40:45,720 I think that's a really important task. 941 00:40:45,720 --> 00:40:49,290 And we're going to have to think about who the actors are 942 00:40:49,290 --> 00:40:52,050 going to be that are prepared to take on climate change. 943 00:40:52,050 --> 00:40:54,900 Because we can't just afford to wipe off 944 00:40:54,900 --> 00:40:57,990 4, 8, 10 years of progress. 945 00:40:57,990 --> 00:40:59,970 We've got to figure out what to do so. 946 00:40:59,970 --> 00:41:01,770 There's a new menu of actors, here, that's 947 00:41:01,770 --> 00:41:06,510 potential-- at state level, and in regions, and in companies. 948 00:41:06,510 --> 00:41:10,050 Because I do think this innovation wave is under way. 949 00:41:10,050 --> 00:41:12,810 And Martín's point about niche players, 950 00:41:12,810 --> 00:41:14,463 that's an important economic point. 951 00:41:14,463 --> 00:41:16,380 You can move ahead with that kind of approach, 952 00:41:16,380 --> 00:41:18,570 in a number of technology spots. 953 00:41:18,570 --> 00:41:21,205 So, arguably, we're going to need a Plan B, 954 00:41:21,205 --> 00:41:23,830 and we're going to have to think about who the actors are going 955 00:41:23,830 --> 00:41:28,740 to be in Plan B. One thing which we did 956 00:41:28,740 --> 00:41:32,040 do in the Department of Energy, over the last 10 years, 957 00:41:32,040 --> 00:41:35,580 is make it a much more sophisticated 958 00:41:35,580 --> 00:41:38,460 technology-implementation organization, 959 00:41:38,460 --> 00:41:40,390 through work of Sam Bodman and Steve Chu 960 00:41:40,390 --> 00:41:43,600 and Ernie Moniz over the past decade. 961 00:41:43,600 --> 00:41:47,490 So all these new pieces, including ARPA-E, 962 00:41:47,490 --> 00:41:49,200 Energy Frontier Research Centers, 963 00:41:49,200 --> 00:41:52,590 to kind of turn the focus of the Office of Science 964 00:41:52,590 --> 00:41:56,370 onto new energy technology advances. 965 00:41:56,370 --> 00:41:58,800 There's 45 of these centers, now, at universities 966 00:41:58,800 --> 00:42:00,500 across the country. 967 00:42:00,500 --> 00:42:02,490 Office of Science is now really focused 968 00:42:02,490 --> 00:42:06,000 on new technology advances. 969 00:42:06,000 --> 00:42:08,820 EERE, Energy Efficiency and Renewable Energy, 970 00:42:08,820 --> 00:42:12,030 has developed a major focus on advanced manufacturing 971 00:42:12,030 --> 00:42:15,420 as a way of driving down entry costs for new energy 972 00:42:15,420 --> 00:42:16,110 technologies. 973 00:42:16,110 --> 00:42:17,568 That's really important, if they're 974 00:42:17,568 --> 00:42:20,205 going to get in range of price. 975 00:42:20,205 --> 00:42:22,830 They've created something we'll talk about in the last reading. 976 00:42:22,830 --> 00:42:26,700 They have created a whole new way of getting, in effect, 977 00:42:26,700 --> 00:42:31,200 substituting space for capital, at the site of three 978 00:42:31,200 --> 00:42:33,858 historic energy laboratories. 979 00:42:33,858 --> 00:42:35,400 We'll talk about in the last reading. 980 00:42:35,400 --> 00:42:39,150 They have a much stronger technology-transition office. 981 00:42:39,150 --> 00:42:41,730 They have innovation hubs that, when your technology is 982 00:42:41,730 --> 00:42:43,890 ready to kind of scale up, you can actually 983 00:42:43,890 --> 00:42:46,260 get a substantial amount of implementation 984 00:42:46,260 --> 00:42:49,380 and late-stage applied research money focused 985 00:42:49,380 --> 00:42:52,110 on areas like batteries, fourth-generation nuclear 986 00:42:52,110 --> 00:42:55,470 power, and a series of other technology areas. 987 00:42:55,470 --> 00:42:58,380 So all these new innovation pieces 988 00:42:58,380 --> 00:43:00,780 have been added to the Department of Energy. 989 00:43:00,780 --> 00:43:03,510 So it's much more technology-ready 990 00:43:03,510 --> 00:43:04,960 than it was a decade ago. 991 00:43:04,960 --> 00:43:08,520 It's much more in position to be able to work on the energy 992 00:43:08,520 --> 00:43:10,830 tasks that it was assigned. 993 00:43:10,830 --> 00:43:11,820 So that's-- 994 00:43:11,820 --> 00:43:13,380 Obviously, these could be curtailed 995 00:43:13,380 --> 00:43:14,640 by the current administration. 996 00:43:14,640 --> 00:43:16,128 That's a genuine challenge, here. 997 00:43:16,128 --> 00:43:17,670 But at least we've got experience now 998 00:43:17,670 --> 00:43:19,980 with what some of these issues are. 999 00:43:19,980 --> 00:43:22,235 There's still big gaps in the system. 1000 00:43:22,235 --> 00:43:23,610 The front end is much better now, 1001 00:43:23,610 --> 00:43:25,527 at the Department of Energy, but there's still 1002 00:43:25,527 --> 00:43:28,440 big gaps-- areas like, how do you do test beds? 1003 00:43:28,440 --> 00:43:31,980 How are we going to do a technology strategy that 1004 00:43:31,980 --> 00:43:34,380 cuts across public and private sectors, 1005 00:43:34,380 --> 00:43:36,390 for a common strategy across players? 1006 00:43:36,390 --> 00:43:38,550 We haven't done that yet. 1007 00:43:38,550 --> 00:43:42,870 We need new financing mechanisms for technology implementation. 1008 00:43:42,870 --> 00:43:44,610 So there's a lot of pieces that-- 1009 00:43:44,610 --> 00:43:48,480 there still remain gaps on the back end of the system. 1010 00:43:48,480 --> 00:43:49,725 But we have made progress. 1011 00:43:52,087 --> 00:43:54,170 And, look, let me put the other piece on the table 1012 00:43:54,170 --> 00:43:55,665 and we'll do them both. 1013 00:43:55,665 --> 00:43:57,075 Are both of these yours, Chris? 1014 00:43:57,075 --> 00:43:57,575 CHRIS: Yep. 1015 00:43:57,575 --> 00:43:58,533 WILLIAM BONVILLIAN: OK. 1016 00:44:03,230 --> 00:44:14,360 So this is a chapter in a piece that just came out last month. 1017 00:44:14,360 --> 00:44:21,790 The US is very reliant on entrepreneurial startups 1018 00:44:21,790 --> 00:44:23,490 to bring innovation into its system. 1019 00:44:26,550 --> 00:44:29,940 That's been a key innovation organizational accomplishment 1020 00:44:29,940 --> 00:44:33,660 of the last 30 or 40 years, actually. 1021 00:44:33,660 --> 00:44:37,170 So we developed a $60-billion venture-capital support system 1022 00:44:37,170 --> 00:44:38,670 to support startups. 1023 00:44:38,670 --> 00:44:39,420 It's how we do it. 1024 00:44:39,420 --> 00:44:42,540 It's a very interesting part of our system. 1025 00:44:42,540 --> 00:44:45,570 No other country really has a system as strong as ours. 1026 00:44:45,570 --> 00:44:47,835 The legacy sectors are like protected castles. 1027 00:44:52,050 --> 00:44:56,040 VCs don't like to take the castles on. 1028 00:44:56,040 --> 00:44:57,780 You can understand why. 1029 00:44:57,780 --> 00:45:00,270 They like to innovate in new frontier areas, where 1030 00:45:00,270 --> 00:45:02,062 there are not incumbents, where they're not 1031 00:45:02,062 --> 00:45:03,390 going to get opposition. 1032 00:45:03,390 --> 00:45:08,070 So, back in 2008, when it looked like energy prices were going 1033 00:45:08,070 --> 00:45:12,090 to be high and cap-and-trade was coming along, 1034 00:45:12,090 --> 00:45:15,240 VCs began to ramp up their investments 1035 00:45:15,240 --> 00:45:18,062 in new energy technologies. 1036 00:45:18,062 --> 00:45:19,020 And they've now walked. 1037 00:45:21,760 --> 00:45:26,110 So let's look at venture-capital investment, nationwide. 1038 00:45:26,110 --> 00:45:29,680 This is what venture capital spent in 2015 1039 00:45:29,680 --> 00:45:31,531 its money on-- its $60 billion. 1040 00:45:31,531 --> 00:45:34,180 Right? 1041 00:45:34,180 --> 00:45:35,450 Software. 1042 00:45:35,450 --> 00:45:36,240 Right? 1043 00:45:36,240 --> 00:45:37,710 That's the long and short of it. 1044 00:45:37,710 --> 00:45:39,780 They did a fair amount of biotech. 1045 00:45:39,780 --> 00:45:41,040 Software was about 40%. 1046 00:45:41,040 --> 00:45:43,530 That's about 13%. 1047 00:45:43,530 --> 00:45:47,730 A bunch of services, media entertainment, 1048 00:45:47,730 --> 00:45:50,760 IT services-- that was the bulk of the rest. 1049 00:45:50,760 --> 00:45:52,860 Now, you look at this little piece down here, 1050 00:45:52,860 --> 00:45:53,970 right, this piece. 1051 00:45:53,970 --> 00:45:55,890 That's 5%. 1052 00:45:55,890 --> 00:45:58,440 That's hard technologies. 1053 00:45:58,440 --> 00:46:01,290 That's energy and industrial. 1054 00:46:01,290 --> 00:46:03,000 Right? 1055 00:46:03,000 --> 00:46:05,623 This has profound implications, absolutely 1056 00:46:05,623 --> 00:46:06,540 profound implications. 1057 00:46:06,540 --> 00:46:08,457 So the way in which we stand up new innovation 1058 00:46:08,457 --> 00:46:12,430 is going to be through this venture-capital finance system. 1059 00:46:12,430 --> 00:46:16,030 And all they're going to do is software and biotech 1060 00:46:16,030 --> 00:46:18,342 and a few services. 1061 00:46:18,342 --> 00:46:20,050 We've got a serious problem on our hands. 1062 00:46:20,050 --> 00:46:23,290 We're not going to have an energy-technology revolution. 1063 00:46:23,290 --> 00:46:27,670 But we're also not standing up innovations 1064 00:46:27,670 --> 00:46:30,100 in hard technologies. 1065 00:46:30,100 --> 00:46:32,650 Software and biotech are not particularly 1066 00:46:32,650 --> 00:46:33,760 job-creating areas. 1067 00:46:33,760 --> 00:46:36,060 Software maybe negative job creating. 1068 00:46:36,060 --> 00:46:36,992 Right? 1069 00:46:36,992 --> 00:46:38,950 Are we going to have any jobs, in this economy? 1070 00:46:38,950 --> 00:46:40,492 I mean, what's going to happen, here? 1071 00:46:40,492 --> 00:46:43,205 These are really, really serious problems. 1072 00:46:43,205 --> 00:46:45,580 OK? 1073 00:46:45,580 --> 00:46:47,610 We tried to do the same chart for 2016, 1074 00:46:47,610 --> 00:46:49,960 but [LAUGH] the Venture Capital Association [LAUGH] 1075 00:46:49,960 --> 00:46:52,543 changed the way they collected their numbers, because software 1076 00:46:52,543 --> 00:46:54,903 was so pervasive that they couldn't separate it out 1077 00:46:54,903 --> 00:46:55,570 anymore [LAUGH]. 1078 00:46:55,570 --> 00:46:56,100 Right? 1079 00:46:56,100 --> 00:46:57,670 It was in every sector. 1080 00:46:57,670 --> 00:46:59,710 So [LAUGH] 15 is the last good set 1081 00:46:59,710 --> 00:47:03,670 of numbers we're going to get around software investment. 1082 00:47:03,670 --> 00:47:05,980 So, who comes to the rescue, here? 1083 00:47:05,980 --> 00:47:08,260 So Rafael comes to the rescue. 1084 00:47:08,260 --> 00:47:09,010 I didn't get this. 1085 00:47:09,010 --> 00:47:10,540 I mean, this is his thinking. 1086 00:47:10,540 --> 00:47:15,940 And I had this conversation with him. 1087 00:47:15,940 --> 00:47:17,315 We had been struggling with this, 1088 00:47:17,315 --> 00:47:19,023 in the Advanced Manufacturing Partnership 1089 00:47:19,023 --> 00:47:21,010 program, the President's advanced manufacturing 1090 00:47:21,010 --> 00:47:22,390 innovation effort. 1091 00:47:22,390 --> 00:47:23,920 How are we going to get financing 1092 00:47:23,920 --> 00:47:25,840 for companies that are going to manufacture in the United 1093 00:47:25,840 --> 00:47:26,470 States? 1094 00:47:26,470 --> 00:47:28,810 Because they're not getting venture finance. 1095 00:47:28,810 --> 00:47:30,850 And we looked at the other potential sources-- 1096 00:47:30,850 --> 00:47:36,100 you know, private equity, M&A in existing company financing. 1097 00:47:36,100 --> 00:47:40,330 They're just not significant for innovative new companies. 1098 00:47:40,330 --> 00:47:42,580 Venture capital is pretty much the story. 1099 00:47:42,580 --> 00:47:46,983 And, you know, Rafael-- 1100 00:47:46,983 --> 00:47:48,400 I was thinking about, how could we 1101 00:47:48,400 --> 00:47:50,880 do some kind of new financing, or how could we 1102 00:47:50,880 --> 00:47:54,382 create incentives for venture capital to change all its rules 1103 00:47:54,382 --> 00:47:55,840 and go after these harder problems? 1104 00:47:58,620 --> 00:48:03,300 He basically said, venture capital is doing good stuff. 1105 00:48:03,300 --> 00:48:05,980 Software and biotech are important things. 1106 00:48:05,980 --> 00:48:07,600 They're going to do what they can do. 1107 00:48:10,390 --> 00:48:13,440 Substitute space for capital. 1108 00:48:13,440 --> 00:48:14,940 That wasn't quite the way he put it, 1109 00:48:14,940 --> 00:48:16,898 but that was the essence of what he was saying. 1110 00:48:16,898 --> 00:48:20,640 And I said, Rafael, what are you talking about? 1111 00:48:20,640 --> 00:48:21,930 Never had dawned on me. 1112 00:48:21,930 --> 00:48:22,800 Right? 1113 00:48:22,800 --> 00:48:27,560 Basically what he said was, let's create really 1114 00:48:27,560 --> 00:48:32,450 technology-equipment, know-how-rich spaces and get 1115 00:48:32,450 --> 00:48:36,350 a bunch of very interesting hard-technology startups-- 1116 00:48:36,350 --> 00:48:37,850 in other words, the biotechs are OK, 1117 00:48:37,850 --> 00:48:39,560 and the software companies are OK. 1118 00:48:39,560 --> 00:48:42,080 Let's get some of the rest of the crew in 1119 00:48:42,080 --> 00:48:46,280 and create places where they get really advanced equipment 1120 00:48:46,280 --> 00:48:46,950 and know-how. 1121 00:48:46,950 --> 00:48:47,450 Right? 1122 00:48:47,450 --> 00:48:49,760 So there's a lot of technology incubators out there, 1123 00:48:49,760 --> 00:48:51,260 and we've got probably eight of them 1124 00:48:51,260 --> 00:48:53,603 right in our Boston neighborhood, here, 1125 00:48:53,603 --> 00:48:55,020 and some of which are very strong. 1126 00:48:55,020 --> 00:48:58,160 They tend to be earlier-stage. 1127 00:48:58,160 --> 00:49:02,780 They tend to-- they capture you when you're new 1128 00:49:02,780 --> 00:49:04,580 and you're really at the business-plan, 1129 00:49:04,580 --> 00:49:07,370 business-development kind of stage. 1130 00:49:07,370 --> 00:49:09,590 There isn't really a model to help you, 1131 00:49:09,590 --> 00:49:12,140 when you've got to start to scale up-- 1132 00:49:12,140 --> 00:49:14,600 and with that scale-up proposition. 1133 00:49:14,600 --> 00:49:19,360 So that's what his concept is. 1134 00:49:19,360 --> 00:49:21,850 And it happens to speak, I think profoundly, 1135 00:49:21,850 --> 00:49:25,165 to this energy-technology space, if we 1136 00:49:25,165 --> 00:49:26,290 could create some of these. 1137 00:49:26,290 --> 00:49:29,680 The engine that he's now led the creation of 1138 00:49:29,680 --> 00:49:33,580 is exactly an attempt to solve this problem. 1139 00:49:33,580 --> 00:49:35,950 In other words, his view is, we're 1140 00:49:35,950 --> 00:49:38,970 leading a lot of science-based innovation developed in MIT, 1141 00:49:38,970 --> 00:49:41,080 just sitting on the table. 1142 00:49:41,080 --> 00:49:43,090 Because we don't have a scale-up mechanism. 1143 00:49:43,090 --> 00:49:49,090 Can we work on trying to create a space where that could occur? 1144 00:49:49,090 --> 00:49:52,480 So, in effect, what venture capital would finance-- 1145 00:49:52,480 --> 00:49:55,090 that equipment, that technology, that know-how, 1146 00:49:55,090 --> 00:49:57,560 for the scale-up-- 1147 00:49:57,560 --> 00:50:00,200 can we contribute that, create that, 1148 00:50:00,200 --> 00:50:03,020 and then invite the startups in that are 1149 00:50:03,020 --> 00:50:04,880 doing hard-technology startups? 1150 00:50:04,880 --> 00:50:06,410 So there's a bunch of other models. 1151 00:50:06,410 --> 00:50:08,660 DOE got this, big-time. 1152 00:50:08,660 --> 00:50:11,210 ARPA-E began running into a wall. 1153 00:50:11,210 --> 00:50:12,990 ARPA-E had assumed venture capital 1154 00:50:12,990 --> 00:50:15,302 was the way in which its startups were going to work. 1155 00:50:15,302 --> 00:50:17,510 And then they realized their startups weren't getting 1156 00:50:17,510 --> 00:50:19,730 venture money, when venture-capital funding 1157 00:50:19,730 --> 00:50:21,110 in energy collapsed-- right? 1158 00:50:21,110 --> 00:50:23,810 Went down 80%. 1159 00:50:23,810 --> 00:50:31,810 So this band of characters took some space right 1160 00:50:31,810 --> 00:50:34,480 at the Lawrence Berkeley Laboratory, 1161 00:50:34,480 --> 00:50:38,020 up on top of the hill, up above the Berkeley campus, 1162 00:50:38,020 --> 00:50:39,850 on Cyclotron Road. 1163 00:50:39,850 --> 00:50:43,000 And they created a technology, equipment, 1164 00:50:43,000 --> 00:50:47,990 know-how-rich space and provided salaries-- 1165 00:50:47,990 --> 00:50:49,990 for a couple of years, which could be extended-- 1166 00:50:49,990 --> 00:50:52,730 for a crew of startups. 1167 00:50:52,730 --> 00:50:54,430 They're now in their third tranche. 1168 00:50:54,430 --> 00:50:56,530 Very interesting. 1169 00:50:56,530 --> 00:50:58,750 Very interesting companies. 1170 00:50:58,750 --> 00:51:01,000 And it's a whole new technology transition model 1171 00:51:01,000 --> 00:51:03,400 for the Department of Energy. 1172 00:51:03,400 --> 00:51:06,070 So, for possibly 40 years, the Department of Energy 1173 00:51:06,070 --> 00:51:10,390 has been trying to get these big, famous energy 1174 00:51:10,390 --> 00:51:13,960 laboratories that are on mesas, behind barbed wire, 1175 00:51:13,960 --> 00:51:17,410 to transfer their technology out. 1176 00:51:17,410 --> 00:51:20,170 And the folks that work there are paid, you know, 1177 00:51:20,170 --> 00:51:22,300 guaranteed salaries for life. 1178 00:51:22,300 --> 00:51:25,030 And they get entitlement-funded research. 1179 00:51:25,030 --> 00:51:27,490 They're guaranteed interesting scientific work. 1180 00:51:27,490 --> 00:51:30,130 And we want them to walk out of there 1181 00:51:30,130 --> 00:51:33,250 and, you know, not be paid in a stand-up company? 1182 00:51:33,250 --> 00:51:34,540 I mean, good luck. 1183 00:51:34,540 --> 00:51:35,260 Right? 1184 00:51:35,260 --> 00:51:37,960 It's not an optimal technology transfer model. 1185 00:51:37,960 --> 00:51:42,910 And, look-- technology transfers with people that walk, right? 1186 00:51:42,910 --> 00:51:44,560 Technology transfer doesn't happen 1187 00:51:44,560 --> 00:51:49,060 by developing a list or a plan and handing it to someone. 1188 00:51:49,060 --> 00:51:51,760 Technology transfer works through people. 1189 00:51:51,760 --> 00:51:54,460 You've got to really encourage people to emigrate and move 1190 00:51:54,460 --> 00:51:57,310 with the ideas, because they have the tacit knowledge 1191 00:51:57,310 --> 00:51:58,510 to make these things happen. 1192 00:51:58,510 --> 00:52:01,568 Well, this may be a much better technology-transfer model 1193 00:52:01,568 --> 00:52:03,610 for the Department of Energy than the one they've 1194 00:52:03,610 --> 00:52:04,818 been working on for 40 years. 1195 00:52:04,818 --> 00:52:07,390 So two other labs, Argon and Oak Ridge, 1196 00:52:07,390 --> 00:52:09,990 have now picked up the same model. 1197 00:52:09,990 --> 00:52:10,900 Steph? 1198 00:52:10,900 --> 00:52:12,820 STEPH: One of the elements I didn't 1199 00:52:12,820 --> 00:52:14,340 see in the analysis of the models 1200 00:52:14,340 --> 00:52:16,360 was the importance of competition 1201 00:52:16,360 --> 00:52:22,420 or having that sort of truncated time frame. 1202 00:52:22,420 --> 00:52:24,948 How is it that they sort of put pressure on them to deliver? 1203 00:52:24,948 --> 00:52:26,740 WILLIAM BONVILLIAN: Well all of these teams 1204 00:52:26,740 --> 00:52:28,750 had to compete, to get in there. 1205 00:52:28,750 --> 00:52:30,600 So that was a very tough composition-- 1206 00:52:30,600 --> 00:52:33,430 more than 100 actors, 100 different teams, 1207 00:52:33,430 --> 00:52:36,280 were competing to be part of the first eight. 1208 00:52:36,280 --> 00:52:38,860 So that was a highly competitive process. 1209 00:52:38,860 --> 00:52:41,320 Look, if you've got an interesting startup idea 1210 00:52:41,320 --> 00:52:43,960 and you're just out of grad school or, for that matter, 1211 00:52:43,960 --> 00:52:45,850 just out of undergrad school, and you've 1212 00:52:45,850 --> 00:52:49,300 got a really interesting, small group and idea 1213 00:52:49,300 --> 00:52:51,190 and you want to move it, the fact 1214 00:52:51,190 --> 00:52:53,650 that somebody would give you space, incredible equipment, 1215 00:52:53,650 --> 00:52:56,170 and technology, incredible know-how, 1216 00:52:56,170 --> 00:52:58,360 and pay you a salary for a couple of years, 1217 00:52:58,360 --> 00:52:59,810 what could be better? 1218 00:52:59,810 --> 00:53:00,310 Right? 1219 00:53:00,310 --> 00:53:04,090 This is really good news, for hard-technology startups 1220 00:53:04,090 --> 00:53:05,090 in the energy space. 1221 00:53:05,090 --> 00:53:06,798 So it's been very attractive, and there's 1222 00:53:06,798 --> 00:53:09,250 a lot of competition to get into these places. 1223 00:53:09,250 --> 00:53:12,850 So competition is embedded right at the heart of the model. 1224 00:53:12,850 --> 00:53:13,460 Martha? 1225 00:53:13,460 --> 00:53:15,670 MARTHA: So, Bill, do you have any sense-- 1226 00:53:15,670 --> 00:53:18,190 well, first of all, I can't remember how old they are 1227 00:53:18,190 --> 00:53:20,652 and what kind of track record they have, at this point in-- 1228 00:53:20,652 --> 00:53:22,610 WILLIAM BONVILLIAN: So these are all brand-new. 1229 00:53:22,610 --> 00:53:24,070 This is a brand-new model. 1230 00:53:24,070 --> 00:53:24,610 Right? 1231 00:53:24,610 --> 00:53:24,960 MARTHA: Cyclotron-- 1232 00:53:24,960 --> 00:53:26,668 WILLIAM BONVILLIAN: So they just accepted 1233 00:53:26,668 --> 00:53:28,130 their third round of teams. 1234 00:53:28,130 --> 00:53:29,290 So they're two years old. 1235 00:53:29,290 --> 00:53:29,998 AUDIENCE: Got it. 1236 00:53:29,998 --> 00:53:30,570 OK. 1237 00:53:30,570 --> 00:53:32,000 I wasn't really clear. 1238 00:53:32,000 --> 00:53:34,930 So are they going to be able to expand, 1239 00:53:34,930 --> 00:53:37,240 under this new political climate, to other labs? 1240 00:53:37,240 --> 00:53:38,490 WILLIAM BONVILLIAN: We'll see. 1241 00:53:38,490 --> 00:53:43,532 I think-- from the sense I have in talking to DOE friends-- 1242 00:53:43,532 --> 00:53:44,740 what's wrong with this model? 1243 00:53:44,740 --> 00:53:48,550 I mean, you're in effect repurposing an established 1244 00:53:48,550 --> 00:53:50,097 model at extremely modest costs. 1245 00:53:50,097 --> 00:53:50,680 MARTHA: Right. 1246 00:53:50,680 --> 00:53:51,100 So, in other words-- 1247 00:53:51,100 --> 00:53:52,642 WILLIAM BONVILLIAN: Lawrence Berkeley 1248 00:53:52,642 --> 00:53:54,360 Lab's an $800-million-a-year operation. 1249 00:53:54,360 --> 00:53:55,960 You know, salaries, for these folks? 1250 00:53:55,960 --> 00:53:57,070 That's not much. 1251 00:53:57,070 --> 00:53:57,670 Right? 1252 00:53:57,670 --> 00:53:59,400 And yet the opportunities of standing up 1253 00:53:59,400 --> 00:54:01,608 with new technologies are really pretty significant, 1254 00:54:01,608 --> 00:54:02,650 supporting entrepreneurs. 1255 00:54:02,650 --> 00:54:04,750 So I think this one is a viable model, 1256 00:54:04,750 --> 00:54:06,212 in either political climate. 1257 00:54:06,212 --> 00:54:07,920 PERSON: Right, so who makes the decision? 1258 00:54:07,920 --> 00:54:11,298 And what stage is the technology, when they enter? 1259 00:54:11,298 --> 00:54:13,090 WILLIAM BONVILLIAN: So, you know, this guy, 1260 00:54:13,090 --> 00:54:17,830 Ilan Gur is right out of ARPA-E. So he's very used to-- he 1261 00:54:17,830 --> 00:54:19,450 understands really well-- 1262 00:54:19,450 --> 00:54:21,640 he came through a whole startup experience, himself. 1263 00:54:21,640 --> 00:54:27,820 He's had startup experiences and has his PhD in science, 1264 00:54:27,820 --> 00:54:29,890 from Berkeley-- 1265 00:54:29,890 --> 00:54:31,870 very talented young technologist, 1266 00:54:31,870 --> 00:54:34,270 very sharp, able guy. 1267 00:54:34,270 --> 00:54:36,850 He's got a whole team, there, that's also quite able. 1268 00:54:36,850 --> 00:54:38,890 And strong support from the lab. 1269 00:54:38,890 --> 00:54:39,550 Right? 1270 00:54:39,550 --> 00:54:41,490 So the lab likes this. 1271 00:54:41,490 --> 00:54:44,350 This is a way of getting their stuff out. 1272 00:54:44,350 --> 00:54:46,840 Look-- it's a new model, right? 1273 00:54:46,840 --> 00:54:52,630 The model is, have a competition for, an effect, 1274 00:54:52,630 --> 00:54:55,340 a nerd motorcycle gang. 1275 00:54:55,340 --> 00:54:59,440 Park them outside the barbed wire. 1276 00:54:59,440 --> 00:55:02,680 Give them a home, and give them the keys to go in 1277 00:55:02,680 --> 00:55:03,670 and loot the place. 1278 00:55:03,670 --> 00:55:05,510 I mean, that's essentially the model. 1279 00:55:05,510 --> 00:55:06,205 Right? 1280 00:55:06,205 --> 00:55:07,460 That's what they're doing. 1281 00:55:07,460 --> 00:55:10,295 PERSON: So, when you say "park them outside the fence," 1282 00:55:10,295 --> 00:55:11,160 is that literal? 1283 00:55:11,160 --> 00:55:11,660 Or-- 1284 00:55:11,660 --> 00:55:12,740 STEPH: Yeah, that's literal. 1285 00:55:12,740 --> 00:55:13,450 WILLIAM BONVILLIAN: That's literal. 1286 00:55:13,450 --> 00:55:16,480 They're immediately adjacent to these highly secure facilities. 1287 00:55:16,480 --> 00:55:17,700 PERSON: Why don't they just put them inside? 1288 00:55:17,700 --> 00:55:18,280 WOMAN: But allowed in. 1289 00:55:18,280 --> 00:55:19,840 WILLIAM BONVILLIAN: Well, they are allowed in. 1290 00:55:19,840 --> 00:55:20,440 Yeah. 1291 00:55:20,440 --> 00:55:20,940 Right. 1292 00:55:20,940 --> 00:55:22,650 There are just some security issues, and-- 1293 00:55:22,650 --> 00:55:24,060 STEPH: --side of a mountain, literally? 1294 00:55:24,060 --> 00:55:25,143 WILLIAM BONVILLIAN: Right. 1295 00:55:25,143 --> 00:55:26,510 STEPH: And it's quite steep. 1296 00:55:26,510 --> 00:55:28,340 So, if you're walking and you trip, like, 1297 00:55:28,340 --> 00:55:30,113 you would fall very [LAUGH] heavily. 1298 00:55:30,113 --> 00:55:31,780 WILLIAM BONVILLIAN: It's very beautiful. 1299 00:55:31,780 --> 00:55:32,412 Great views. 1300 00:55:32,412 --> 00:55:34,620 STEPH: They have a great view the bay and the bridge. 1301 00:55:34,620 --> 00:55:36,160 WILLIAM BONVILLIAN: Remember, we talked about Ernest Lawrence? 1302 00:55:36,160 --> 00:55:37,500 This is his lab. 1303 00:55:37,500 --> 00:55:38,500 Right? 1304 00:55:38,500 --> 00:55:41,800 Lawrence Berkeley Laboratory. 1305 00:55:41,800 --> 00:55:43,660 STUDENT: My only concern would be, 1306 00:55:43,660 --> 00:55:47,180 if the technology's too early, they'll be based on, like, 1307 00:55:47,180 --> 00:55:48,850 the people who they know, instead of 1308 00:55:48,850 --> 00:55:50,900 the actual technology. 1309 00:55:50,900 --> 00:55:53,800 So what would be interesting is if it's already technology that 1310 00:55:53,800 --> 00:55:55,330 shows some promise, that way it's 1311 00:55:55,330 --> 00:55:57,190 kind of like a pseudo right-before scale-up, 1312 00:55:57,190 --> 00:56:00,130 where it's, I need to get my technical abilities scaled up? 1313 00:56:00,130 --> 00:56:00,390 WILLIAM BONVILLIAN: Yeah. 1314 00:56:00,390 --> 00:56:01,723 STUDENT: That'll be really good. 1315 00:56:01,723 --> 00:56:04,160 But the issue is, like, this happens kind of like at MIT 1316 00:56:04,160 --> 00:56:06,370 with, like, Delta-V, where it's like, 1317 00:56:06,370 --> 00:56:08,580 it's kind of become a Sloane-y kind of like hub, 1318 00:56:08,580 --> 00:56:11,468 where it's like, there's people who don't have great ideas, 1319 00:56:11,468 --> 00:56:13,885 but they apply because they know the right person who does 1320 00:56:13,885 --> 00:56:15,302 if they go through, versus, like-- 1321 00:56:15,302 --> 00:56:17,677 WILLIAM BONVILLIAN: This is a very tough-minded selection 1322 00:56:17,677 --> 00:56:18,180 process. 1323 00:56:18,180 --> 00:56:19,320 You know? 1324 00:56:19,320 --> 00:56:21,370 Ilan is a real talent. 1325 00:56:21,370 --> 00:56:23,800 He's running a good process, here. 1326 00:56:23,800 --> 00:56:27,010 Look, we're kind of running out of time, here, so let me just 1327 00:56:27,010 --> 00:56:28,270 get the rest of the story out. 1328 00:56:28,270 --> 00:56:30,580 Because part of it, Martín, speaks to the next issue 1329 00:56:30,580 --> 00:56:32,080 we've got, which is-- 1330 00:56:32,080 --> 00:56:35,080 one of the issues here is, these are all early stage. 1331 00:56:35,080 --> 00:56:36,010 Right? 1332 00:56:36,010 --> 00:56:38,470 These are very talented technology teams, right out 1333 00:56:38,470 --> 00:56:40,790 of university laboratories. 1334 00:56:40,790 --> 00:56:42,340 Here's a different model. 1335 00:56:42,340 --> 00:56:44,830 TechBridge, right here in Boston, 1336 00:56:44,830 --> 00:56:47,710 is part of the Boston Fraunhofer system. 1337 00:56:47,710 --> 00:56:50,260 And they have a different model, but they're similarly 1338 00:56:50,260 --> 00:56:54,670 providing this technology, equipment, know-how-rich space 1339 00:56:54,670 --> 00:56:57,130 as a substitute for VC money. 1340 00:56:57,130 --> 00:57:03,010 And the idea here is, Cyclotron Road 1341 00:57:03,010 --> 00:57:05,830 starts with the technology group and then 1342 00:57:05,830 --> 00:57:08,170 tries to nurture the technology. 1343 00:57:08,170 --> 00:57:11,470 TechBridge starts with large regional companies. 1344 00:57:11,470 --> 00:57:14,840 And it goes to them, and it says, what do you want? 1345 00:57:14,840 --> 00:57:15,620 Right? 1346 00:57:15,620 --> 00:57:17,620 And, typically, they don't want disruptive stuff 1347 00:57:17,620 --> 00:57:19,120 that's going to wreck their business 1348 00:57:19,120 --> 00:57:20,470 model-- for obvious reasons. 1349 00:57:20,470 --> 00:57:23,012 And they don't want to bother with stuff that they're already 1350 00:57:23,012 --> 00:57:24,460 doing, that they understand well. 1351 00:57:24,460 --> 00:57:29,080 But there are substantial groups of adjacent energy technologies 1352 00:57:29,080 --> 00:57:32,950 that fit with their model, that would be interesting to them. 1353 00:57:32,950 --> 00:57:35,770 And that's what TechBridge tries to find out. 1354 00:57:35,770 --> 00:57:39,550 So it gets a list of, what do you folks want? 1355 00:57:39,550 --> 00:57:42,490 And then it goes to find talented startups in the Boston 1356 00:57:42,490 --> 00:57:46,780 area, of which there's a lot, and connect the right startup 1357 00:57:46,780 --> 00:57:50,720 to the right industry player, for a collaborative project. 1358 00:57:50,720 --> 00:57:51,430 OK? 1359 00:57:51,430 --> 00:57:52,510 Very different model. 1360 00:57:52,510 --> 00:57:54,250 Very interesting. 1361 00:57:54,250 --> 00:57:57,070 The most interesting part of it is 1362 00:57:57,070 --> 00:58:00,720 that those folks work together for a little while. 1363 00:58:00,720 --> 00:58:02,850 They come up with kind of the prototype together. 1364 00:58:02,850 --> 00:58:04,510 Right? 1365 00:58:04,510 --> 00:58:06,388 But industry doesn't quite trust the startup. 1366 00:58:06,388 --> 00:58:07,930 The startup doesn't know whether it's 1367 00:58:07,930 --> 00:58:10,060 going to get robbed by the big company. 1368 00:58:10,060 --> 00:58:11,440 Who knows, right? 1369 00:58:11,440 --> 00:58:14,350 They bring in the Fraunhofer laboratories, 1370 00:58:14,350 --> 00:58:18,250 this famous laboratory system, and the Fraunhofer labs 1371 00:58:18,250 --> 00:58:21,730 do, for the startup-industry combo, 1372 00:58:21,730 --> 00:58:24,280 what they do for German companies. 1373 00:58:24,280 --> 00:58:28,360 They do a very tough-minded technology assessment. 1374 00:58:28,360 --> 00:58:31,030 They break down the technology, they evaluate it-- 1375 00:58:31,030 --> 00:58:32,710 Can this technology be manufactured? 1376 00:58:32,710 --> 00:58:34,030 How would you manufacture it? 1377 00:58:34,030 --> 00:58:35,613 Can you manufacture it at a price that 1378 00:58:35,613 --> 00:58:37,090 would actually be saleable? 1379 00:58:37,090 --> 00:58:39,580 You know, is this resilient technology? 1380 00:58:39,580 --> 00:58:42,060 All the kind of stuff they do for German companies, 1381 00:58:42,060 --> 00:58:43,930 they're doing for the startup. 1382 00:58:43,930 --> 00:58:48,708 It's a very rich, sophisticated technology evaluation process. 1383 00:58:48,708 --> 00:58:50,500 We don't really have anything in our system 1384 00:58:50,500 --> 00:58:52,690 like it, so it's pretty intriguing. 1385 00:58:52,690 --> 00:58:54,970 And, in effect, they certify to the company-- 1386 00:58:54,970 --> 00:58:57,880 I mean, they may say, this stuff is worthless, throw it away, 1387 00:58:57,880 --> 00:59:00,983 or they could say, this is actually very interesting. 1388 00:59:00,983 --> 00:59:02,650 Here's how you could make it, and here's 1389 00:59:02,650 --> 00:59:04,858 the components you ought to use and the materials you 1390 00:59:04,858 --> 00:59:10,282 ought to think about, and here's a pathway to a marketplace. 1391 00:59:10,282 --> 00:59:11,740 The company, the big company, loves 1392 00:59:11,740 --> 00:59:13,657 this, because they realize the startup may not 1393 00:59:13,657 --> 00:59:14,690 be totally crazy. 1394 00:59:14,690 --> 00:59:17,350 And then the startup likes it because, in effect, it's 1395 00:59:17,350 --> 00:59:21,220 certified their technology. 1396 00:59:21,220 --> 00:59:24,400 So this puts both players into a much more informed space. 1397 00:59:24,400 --> 00:59:26,260 And that's been very-- 1398 00:59:26,260 --> 00:59:28,180 it's been very intriguing, sort of adding 1399 00:59:28,180 --> 00:59:30,220 this technology-validation piece to this. 1400 00:59:30,220 --> 00:59:33,280 Remember, we talked about the role of FDA 1401 00:59:33,280 --> 00:59:37,230 in certifying technology, which guarantees a market? 1402 00:59:37,230 --> 00:59:39,700 This is the first time I've seen this played out 1403 00:59:39,700 --> 00:59:41,050 in a US kind of model. 1404 00:59:41,050 --> 00:59:42,840 And it's kind of intriguing. 1405 00:59:42,840 --> 00:59:44,740 And I'll put one more on the table for you. 1406 00:59:50,300 --> 00:59:55,070 That's Greentown Labs, a respected, quite capable energy 1407 00:59:55,070 --> 00:59:58,050 incubator, full of folks like you-- 1408 00:59:58,050 --> 01:00:00,560 you know, off the lab bunch at a school, 1409 01:00:00,560 --> 01:00:02,370 with cool energy technology ideas. 1410 01:00:05,860 --> 01:00:09,570 Greentown began understanding that there 1411 01:00:09,570 --> 01:00:15,690 are 60-odd teams, had a lot of neat research ideas. 1412 01:00:15,690 --> 01:00:17,650 They had no idea to make anything. 1413 01:00:17,650 --> 01:00:18,150 Right? 1414 01:00:18,150 --> 01:00:20,140 No idea. 1415 01:00:20,140 --> 01:00:23,097 You know, you weren't taught how to make things, here at MIT. 1416 01:00:23,097 --> 01:00:25,097 Although it is changing with the Maker movement. 1417 01:00:25,097 --> 01:00:25,597 But-- 1418 01:00:29,480 --> 01:00:31,850 University-lab-originated technology teams 1419 01:00:31,850 --> 01:00:34,820 don't know anything about manufacturing. 1420 01:00:34,820 --> 01:00:36,860 So they had an interesting idea. 1421 01:00:36,860 --> 01:00:39,040 There's a manufacturing extension program. 1422 01:00:39,040 --> 01:00:41,540 Every state has one, sponsored by the Department of Commerce 1423 01:00:41,540 --> 01:00:43,880 NIST. 1424 01:00:43,880 --> 01:00:46,100 Massachusetts happens to have a good-- 1425 01:00:46,100 --> 01:00:49,225 quite a good manufacturing extension program. 1426 01:00:52,600 --> 01:00:55,970 Greentown and the MEP got together. 1427 01:00:55,970 --> 01:00:57,720 And the MEP said, hmm, that's interesting. 1428 01:00:57,720 --> 01:00:59,387 We've never worked with startups before. 1429 01:00:59,387 --> 01:01:02,710 We work with small manufacturers. 1430 01:01:02,710 --> 01:01:06,970 But maybe we could link small manufacturers and the startups. 1431 01:01:06,970 --> 01:01:10,030 And Massachusetts happens to have still a pretty strong base 1432 01:01:10,030 --> 01:01:12,220 of small manufacturers. 1433 01:01:12,220 --> 01:01:14,530 They work for the defense sector, the growing robotics 1434 01:01:14,530 --> 01:01:16,060 sector, the medical-device sector-- which 1435 01:01:16,060 --> 01:01:17,477 are big sectors, in Massachusetts, 1436 01:01:17,477 --> 01:01:21,010 and there's some talented small companies. 1437 01:01:21,010 --> 01:01:27,400 The MEP ran a survey of its capable small manufacturers. 1438 01:01:27,400 --> 01:01:30,760 And the survey results came back. 1439 01:01:30,760 --> 01:01:35,170 83 were interested in talking to startups. 1440 01:01:35,170 --> 01:01:37,240 Why? 1441 01:01:37,240 --> 01:01:42,737 These small manufacturers are tied to existing supply chains. 1442 01:01:42,737 --> 01:01:43,570 They don't innovate. 1443 01:01:43,570 --> 01:01:46,060 They don't do R&E. They don't have access to innovation. 1444 01:01:46,060 --> 01:01:48,310 How are they going to grow their market significantly? 1445 01:01:48,310 --> 01:01:50,860 They're kind of locked into a pathway. 1446 01:01:50,860 --> 01:01:53,020 This is a route out, for some of them. 1447 01:01:53,020 --> 01:01:56,335 In addition, others like the startup culture. 1448 01:01:56,335 --> 01:01:57,710 They thought, that's pretty cool. 1449 01:01:57,710 --> 01:01:59,620 Let's get my employees feeling like that. 1450 01:01:59,620 --> 01:02:00,120 Right? 1451 01:02:00,120 --> 01:02:02,140 Maybe we'll get some stuff done. 1452 01:02:02,140 --> 01:02:04,580 And some others thought, gee, the startup culture's 1453 01:02:04,580 --> 01:02:06,580 important, now, in Massachusetts, to its feature 1454 01:02:06,580 --> 01:02:06,870 acc-- 1455 01:02:06,870 --> 01:02:08,203 [AUDIO OUT] We're good citizens. 1456 01:02:08,203 --> 01:02:09,700 We're going to help them. 1457 01:02:09,700 --> 01:02:14,170 So they created this complex process 1458 01:02:14,170 --> 01:02:17,740 of how to arrange these exchanges. 1459 01:02:17,740 --> 01:02:25,628 Now, the startups, they communicate by internet things 1460 01:02:25,628 --> 01:02:27,420 that you all understand and I have no idea. 1461 01:02:27,420 --> 01:02:27,830 Of. 1462 01:02:27,830 --> 01:02:28,240 Right? 1463 01:02:28,240 --> 01:02:29,157 I don't what they are. 1464 01:02:29,157 --> 01:02:31,425 But that's how they communicate. 1465 01:02:31,425 --> 01:02:32,800 You know, I'm exaggerating, here, 1466 01:02:32,800 --> 01:02:36,030 but the startups by and large voted for Bernie, 1467 01:02:36,030 --> 01:02:38,490 and the small manufacturers-- 1468 01:02:38,490 --> 01:02:41,580 I'm exaggerating-- probably voted for Donald. 1469 01:02:41,580 --> 01:02:44,670 And they worked by face-to-face meetings-- 1470 01:02:44,670 --> 01:02:46,270 things like telephones. 1471 01:02:46,270 --> 01:02:47,500 You know? 1472 01:02:47,500 --> 01:02:48,600 You remember landlines? 1473 01:02:48,600 --> 01:02:50,323 They still exist. 1474 01:02:50,323 --> 01:02:51,990 These are completely different cultures. 1475 01:02:51,990 --> 01:02:54,750 How are they going to fall in love with each other 1476 01:02:54,750 --> 01:02:56,940 and be able to trust each other to do technology 1477 01:02:56,940 --> 01:02:57,940 development together? 1478 01:02:57,940 --> 01:03:00,600 And there were no incentives, here. 1479 01:03:00,600 --> 01:03:02,770 There were no subsidies. 1480 01:03:02,770 --> 01:03:04,590 The startup had to come up with money, 1481 01:03:04,590 --> 01:03:08,010 to fund the advanced prototype or the pilot production they 1482 01:03:08,010 --> 01:03:09,420 wanted to undertake. 1483 01:03:09,420 --> 01:03:11,760 So there were no giveaways to incentivize people. 1484 01:03:11,760 --> 01:03:14,310 This was real money, and both sides were at stake. 1485 01:03:14,310 --> 01:03:16,950 So they arranged this four-step process, 1486 01:03:16,950 --> 01:03:20,500 to try and bring about communication. 1487 01:03:20,500 --> 01:03:24,090 43 startups were interested. 1488 01:03:24,090 --> 01:03:27,870 After a year of pilot projects, 19 deals. 1489 01:03:27,870 --> 01:03:29,100 Money changed hands. 1490 01:03:29,100 --> 01:03:30,660 Things were being made. 1491 01:03:30,660 --> 01:03:31,800 Pretty interesting. 1492 01:03:31,800 --> 01:03:34,140 So this is another piece. 1493 01:03:34,140 --> 01:03:37,180 We've now collected a bunch of ideas, here. 1494 01:03:37,180 --> 01:03:38,220 Right? 1495 01:03:38,220 --> 01:03:40,500 Bunch of ideas, here, that are potentially relevant-- 1496 01:03:40,500 --> 01:03:46,050 From Cyclotron Road, repurposing an existing source 1497 01:03:46,050 --> 01:03:49,260 of strong technology equipment and know-how, 1498 01:03:49,260 --> 01:03:50,735 repurpose these energy labs. 1499 01:03:50,735 --> 01:03:52,110 That's a really interesting idea, 1500 01:03:52,110 --> 01:03:53,840 because that's fairly cheap. 1501 01:03:53,840 --> 01:03:54,660 Right? 1502 01:03:54,660 --> 01:03:56,850 You don't have to build all this new equipment. 1503 01:03:56,850 --> 01:03:58,600 MIT is doing the same thing with equipment 1504 01:03:58,600 --> 01:04:02,040 it's got, for the engine. 1505 01:04:02,040 --> 01:04:05,543 From TechBridge, the idea of, maybe you 1506 01:04:05,543 --> 01:04:07,710 could do this-- maybe you could connect up companies 1507 01:04:07,710 --> 01:04:09,930 at the outset, with startups. 1508 01:04:09,930 --> 01:04:10,800 That's interesting. 1509 01:04:10,800 --> 01:04:13,200 And maybe you could do a technology validation step. 1510 01:04:13,200 --> 01:04:15,300 And then this third piece, here-- 1511 01:04:15,300 --> 01:04:19,590 and then I'll call it a day and let Chris lead some questions. 1512 01:04:19,590 --> 01:04:21,870 But this third piece, here, is, maybe 1513 01:04:21,870 --> 01:04:24,733 you could tie small manufacturers and startups, 1514 01:04:24,733 --> 01:04:27,150 because they both have a problem that the other side could 1515 01:04:27,150 --> 01:04:27,650 solve. 1516 01:04:27,650 --> 01:04:28,740 Right? 1517 01:04:28,740 --> 01:04:32,580 So you start to see a pretty interesting model 1518 01:04:32,580 --> 01:04:38,520 for Rafael's idea of substituting space 1519 01:04:38,520 --> 01:04:39,570 for venture funding. 1520 01:04:39,570 --> 01:04:40,860 This is an interesting model. 1521 01:04:40,860 --> 01:04:42,650 Universities could do this model. 1522 01:04:42,650 --> 01:04:45,180 MIT is trying to experiment to show other schools that it 1523 01:04:45,180 --> 01:04:46,740 could be done. 1524 01:04:46,740 --> 01:04:50,010 Federal labs are already pursuing this. 1525 01:04:50,010 --> 01:04:53,100 And the DOD has 67 of these, and Lincoln Lab 1526 01:04:53,100 --> 01:04:56,760 is extremely interested in this model, for example. 1527 01:04:56,760 --> 01:04:59,790 So is Draper, just up the street. 1528 01:04:59,790 --> 01:05:02,860 So, in other words, there are ways this thing could scale. 1529 01:05:02,860 --> 01:05:03,660 Right? 1530 01:05:03,660 --> 01:05:06,300 So, between universities and existing laboratory 1531 01:05:06,300 --> 01:05:09,120 capabilities-- and then MIT's got the idea of connecting you 1532 01:05:09,120 --> 01:05:12,480 to companies and nodes that could help you 1533 01:05:12,480 --> 01:05:15,300 as you develop a more sophisticated product line. 1534 01:05:15,300 --> 01:05:16,920 So there could be a new model, here, 1535 01:05:16,920 --> 01:05:19,440 that would really help with what's 1536 01:05:19,440 --> 01:05:22,377 become now a very significant gap in US innovation system, 1537 01:05:22,377 --> 01:05:24,210 over the collapse of venture-capital funding 1538 01:05:24,210 --> 01:05:27,850 for other than software, biotech, and certain service 1539 01:05:27,850 --> 01:05:30,233 sectors. 1540 01:05:30,233 --> 01:05:31,150 Chris, it's all yours. 1541 01:05:31,150 --> 01:05:32,080 CHRIS: Awesome. 1542 01:05:32,080 --> 01:05:35,080 So I thought this is a really interesting article, 1543 01:05:35,080 --> 01:05:39,030 because you often hear about, oh, energy, funding, 1544 01:05:39,030 --> 01:05:40,780 and the whole system's not really working, 1545 01:05:40,780 --> 01:05:43,780 but it was kind of hard for me, at least, to see why, 1546 01:05:43,780 --> 01:05:47,340 and, like, the discussion of the neoclassical economic model 1547 01:05:47,340 --> 01:05:49,480 and why that doesn't really work out, 1548 01:05:49,480 --> 01:05:51,580 especially for this kind of industry, 1549 01:05:51,580 --> 01:05:53,560 was pretty interesting to me. 1550 01:05:53,560 --> 01:05:56,250 So the way I saw it was that-- 1551 01:05:56,250 --> 01:05:58,010 So there's kind of a twofold problem. 1552 01:05:58,010 --> 01:06:03,160 Like, we have problems in energy revolution and the technology 1553 01:06:03,160 --> 01:06:05,560 space and then also, like, implementing 1554 01:06:05,560 --> 01:06:06,880 those technologies. 1555 01:06:06,880 --> 01:06:11,260 And Reif presents this innovation-orchards kind 1556 01:06:11,260 --> 01:06:13,510 of framework, which is really interesting. 1557 01:06:13,510 --> 01:06:17,590 And, as Bill mentioned, we have a somewhat robust kind 1558 01:06:17,590 --> 01:06:23,710 of model for early, maybe like incubator-type startups. 1559 01:06:23,710 --> 01:06:27,480 And then we have to somehow bridge that gap to innovation. 1560 01:06:27,480 --> 01:06:30,220 I was just wondering, what are your thoughts on how 1561 01:06:30,220 --> 01:06:33,340 we can kind of create that smooth transition 1562 01:06:33,340 --> 01:06:37,300 between institutions that might be providing some early seed 1563 01:06:37,300 --> 01:06:39,730 funding and then how to transition those 1564 01:06:39,730 --> 01:06:42,490 into later stage, whether those be connected 1565 01:06:42,490 --> 01:06:46,660 to, like, TechBridge or those other models that have kind 1566 01:06:46,660 --> 01:06:50,980 of demonstrated some pretty good ways to bring 1567 01:06:50,980 --> 01:06:54,994 that implementation process into play. 1568 01:06:59,430 --> 01:07:00,890 RASHID: I think two things. 1569 01:07:00,890 --> 01:07:05,720 One, I was pretty astonished at the first piece, 1570 01:07:05,720 --> 01:07:08,062 particularly taking this neoclassical view of, 1571 01:07:08,062 --> 01:07:10,270 hey, should we do cap-and-trade instead of carbon tax 1572 01:07:10,270 --> 01:07:13,140 [INAUDIBLE] for curbing emissions? 1573 01:07:13,140 --> 01:07:15,980 And I think it did a pretty good job of saying that maybe, like, 1574 01:07:15,980 --> 01:07:19,850 it's more complicated than that, but also like the fact that we 1575 01:07:19,850 --> 01:07:24,350 were still looking to do sort of a cap-and-trade system, 1576 01:07:24,350 --> 01:07:27,500 even in 2010, which is relatively recent, 1577 01:07:27,500 --> 01:07:31,370 and classical economics has existed for a while now-- 1578 01:07:31,370 --> 01:07:34,250 made me think, like, is economics-- 1579 01:07:34,250 --> 01:07:36,820 Are the solutions that we think theoretically, 1580 01:07:36,820 --> 01:07:39,740 like, in economics, are they effectual? 1581 01:07:39,740 --> 01:07:42,230 And are they just kind of limiting us, because we only 1582 01:07:42,230 --> 01:07:43,730 have this school of economic thought 1583 01:07:43,730 --> 01:07:45,860 that says this is sort of our solution subset, 1584 01:07:45,860 --> 01:07:47,750 this is the answer? 1585 01:07:47,750 --> 01:07:49,610 And are there economists out there 1586 01:07:49,610 --> 01:07:51,440 aren't neoclassical economists, that 1587 01:07:51,440 --> 01:07:55,100 may have solutions for us that exist outside of-- 1588 01:07:55,100 --> 01:07:57,410 that probably would be a lot more palatable and useful 1589 01:07:57,410 --> 01:08:00,190 than a carbon tax or a cap-and-trade system. 1590 01:08:00,190 --> 01:08:01,690 WILLIAM BONVILLIAN: So, Rasheed, let 1591 01:08:01,690 --> 01:08:03,870 me build on that for a second and just-- 1592 01:08:03,870 --> 01:08:06,590 and, just to be clear, don't get me wrong, 1593 01:08:06,590 --> 01:08:08,750 I do think a pricing mechan-- there is definitely 1594 01:08:08,750 --> 01:08:10,100 a place for a pricing mechanism. 1595 01:08:10,100 --> 01:08:12,120 It can help a lot. 1596 01:08:12,120 --> 01:08:14,047 I think part of the problem, here, 1597 01:08:14,047 --> 01:08:16,130 is that neoclassical economics, as we talked about 1598 01:08:16,130 --> 01:08:24,410 in the first class, hasn't been able to develop an outlook that 1599 01:08:24,410 --> 01:08:33,915 enables it to treat technology innovation as endogenous 1600 01:08:33,915 --> 01:08:35,390 to economic-growth theory. 1601 01:08:35,390 --> 01:08:35,890 Right? 1602 01:08:35,890 --> 01:08:38,100 So SOLO announces it's exogenous, 1603 01:08:38,100 --> 01:08:42,962 because it's too complex a model for us to track the variables. 1604 01:08:42,962 --> 01:08:44,670 And, as we've talked about in this class, 1605 01:08:44,670 --> 01:08:47,310 it involves history and culture and organization theory 1606 01:08:47,310 --> 01:08:49,020 and all kinds of other things that 1607 01:08:49,020 --> 01:08:51,569 are kind of outside the parameters of what economics 1608 01:08:51,569 --> 01:08:54,060 is normally able to track in its curves. 1609 01:08:54,060 --> 01:08:56,430 So that's a genuine problem. 1610 01:08:56,430 --> 01:09:04,939 So when neoclassical economics comes up with a fix to climate, 1611 01:09:04,939 --> 01:09:08,038 it misses the technology side. 1612 01:09:08,038 --> 01:09:09,580 Because it doesn't have sophisticated 1613 01:09:09,580 --> 01:09:10,580 handles to deal with it. 1614 01:09:10,580 --> 01:09:12,979 Now, obviously economists like Romer and others 1615 01:09:12,979 --> 01:09:16,939 are attempting to make technology theory endogenous, 1616 01:09:16,939 --> 01:09:18,710 part of economic theory, but that's still 1617 01:09:18,710 --> 01:09:20,210 an ongoing project. 1618 01:09:20,210 --> 01:09:22,720 But that's where we ran into trouble, 1619 01:09:22,720 --> 01:09:26,930 was that the technology need over an extended period of time 1620 01:09:26,930 --> 01:09:30,470 didn't match the timetable on cap-and-trade. 1621 01:09:30,470 --> 01:09:32,779 And the solution there was to push off cap-and-trade. 1622 01:09:32,779 --> 01:09:35,602 And that's, in effect, what we've done. 1623 01:09:35,602 --> 01:09:37,310 I still think we need to come back to it, 1624 01:09:37,310 --> 01:09:39,080 but I think the project at hand is 1625 01:09:39,080 --> 01:09:41,390 a technology-development project and really 1626 01:09:41,390 --> 01:09:44,370 a state and local government technology-implementation 1627 01:09:44,370 --> 01:09:47,420 alternatives, where we could come up 1628 01:09:47,420 --> 01:09:50,898 with a Plan B that helped make progress for the next decade 1629 01:09:50,898 --> 01:09:51,398 or so. 1630 01:09:53,920 --> 01:09:56,942 STEPH: I also, to add to Rasheed's point, 1631 01:09:56,942 --> 01:09:58,900 I think that's what I was getting at last week, 1632 01:09:58,900 --> 01:10:04,030 with my point about nonmarket solutions to market-- 1633 01:10:04,030 --> 01:10:05,680 to problems that we're approaching 1634 01:10:05,680 --> 01:10:10,348 through the lens of economics, in the sense that, perhaps 1635 01:10:10,348 --> 01:10:11,140 if we think about-- 1636 01:10:14,740 --> 01:10:20,050 if we start our problem-solving from a lens of promoting 1637 01:10:20,050 --> 01:10:24,163 social good, rather than increasing capital gain, 1638 01:10:24,163 --> 01:10:26,830 then we might be able to come up with alternative and innovative 1639 01:10:26,830 --> 01:10:27,850 solutions. 1640 01:10:27,850 --> 01:10:28,768 Right? 1641 01:10:28,768 --> 01:10:30,310 And so I think that's sort of where-- 1642 01:10:30,310 --> 01:10:31,767 Reif? 1643 01:10:31,767 --> 01:10:32,350 STUDENT: Reif. 1644 01:10:32,350 --> 01:10:35,700 STEPH: Reif was coming from, that this model-- 1645 01:10:35,700 --> 01:10:38,290 and I mentioned this on our very first day of class-- 1646 01:10:38,290 --> 01:10:40,150 very much is similar to the model 1647 01:10:40,150 --> 01:10:42,250 that nongovernmental organizations and nonprofits 1648 01:10:42,250 --> 01:10:44,890 have been using for a very long time, in sort 1649 01:10:44,890 --> 01:10:48,700 of trading or leveraging the kindness of individuals 1650 01:10:48,700 --> 01:10:51,250 and their willingness to let them participate 1651 01:10:51,250 --> 01:10:52,090 in their spaces. 1652 01:10:52,090 --> 01:10:54,610 And you see this happen for political campaigns. 1653 01:10:54,610 --> 01:10:56,170 Volunteer fellows will go, and they 1654 01:10:56,170 --> 01:10:57,880 will live in a supporter's house, 1655 01:10:57,880 --> 01:11:00,088 and then they will go on and knock on people's doors 1656 01:11:00,088 --> 01:11:00,880 for that candidate. 1657 01:11:00,880 --> 01:11:03,088 And they will do so for very little money or no money 1658 01:11:03,088 --> 01:11:03,640 at all. 1659 01:11:03,640 --> 01:11:06,640 And so, as someone who comes from the nonprofit and NGO 1660 01:11:06,640 --> 01:11:10,270 sector, and I've been you know volunteering 1661 01:11:10,270 --> 01:11:12,470 in politics since I was really little, 1662 01:11:12,470 --> 01:11:17,260 the ways in which you can leverage on the sort of good 1663 01:11:17,260 --> 01:11:21,010 and ethics of people seems to me a much more interesting place 1664 01:11:21,010 --> 01:11:23,770 to start for research and development 1665 01:11:23,770 --> 01:11:26,260 and for hardware technologies than people would think. 1666 01:11:26,260 --> 01:11:29,890 Because, if you approach it from a lens of economics, 1667 01:11:29,890 --> 01:11:31,690 it's very difficult to make the case, 1668 01:11:31,690 --> 01:11:33,940 oftentimes, that your technology could be disruptive 1669 01:11:33,940 --> 01:11:34,917 and could pay off. 1670 01:11:34,917 --> 01:11:37,000 But if you approach it from a lens of social good, 1671 01:11:37,000 --> 01:11:38,458 it's possible that you could appeal 1672 01:11:38,458 --> 01:11:40,330 to the ethos of a venture capitalist. 1673 01:11:40,330 --> 01:11:42,400 Because, for example, someone like Bill Gates 1674 01:11:42,400 --> 01:11:44,230 is more likely to say, I want to do this 1675 01:11:44,230 --> 01:11:46,190 because I think it's the right thing to do, 1676 01:11:46,190 --> 01:11:49,450 than to make the argument that it's a good investment for him 1677 01:11:49,450 --> 01:11:51,440 and that the ROI will be greater. 1678 01:11:51,440 --> 01:11:55,690 So I think that there is a benefit to sometimes pivoting 1679 01:11:55,690 --> 01:11:59,320 away from market-oriented problem-solving 1680 01:11:59,320 --> 01:12:02,930 and to view it from a different sort of lens of ethics 1681 01:12:02,930 --> 01:12:04,930 or social-good promotion. 1682 01:12:04,930 --> 01:12:08,210 Obviously that won't always work, but there are instances, 1683 01:12:08,210 --> 01:12:10,000 and I think this is one, in which that 1684 01:12:10,000 --> 01:12:12,620 is where we are leaning toward. 1685 01:12:12,620 --> 01:12:15,700 WILLIAM BONVILLIAN: And I will add, Steph, to your point, 1686 01:12:15,700 --> 01:12:18,610 that part of what has come with the engine 1687 01:12:18,610 --> 01:12:21,670 is a bridge fund available to those startups. 1688 01:12:21,670 --> 01:12:25,870 So Rafael and colleagues have been 1689 01:12:25,870 --> 01:12:29,250 able to raise over, I think, $150 million, 1690 01:12:29,250 --> 01:12:31,905 now, for commitments to a bridge fund. 1691 01:12:31,905 --> 01:12:33,280 Because, you know, these startups 1692 01:12:33,280 --> 01:12:34,572 are going to need some funding. 1693 01:12:34,572 --> 01:12:35,072 Right? 1694 01:12:35,072 --> 01:12:35,930 It's not going to-- 1695 01:12:35,930 --> 01:12:38,545 they save huge expenses by equipment and technology 1696 01:12:38,545 --> 01:12:41,290 and know-how savings, in this new space, 1697 01:12:41,290 --> 01:12:43,970 but they still are going to need to get funding. 1698 01:12:43,970 --> 01:12:46,390 And so this bridge fund could really help them. 1699 01:12:46,390 --> 01:12:50,870 That money was raised from, essentially, 1700 01:12:50,870 --> 01:12:54,750 generous rich people in this region, who 1701 01:12:54,750 --> 01:12:59,270 were prepared to, in effect, make a charitable donation 1702 01:12:59,270 --> 01:13:01,040 towards this thing, thinking that it might 1703 01:13:01,040 --> 01:13:02,660 be helpful to the overall innovation 1704 01:13:02,660 --> 01:13:05,570 economy in the Massachusetts area. 1705 01:13:05,570 --> 01:13:10,010 And they have an opportunity for return. 1706 01:13:10,010 --> 01:13:11,950 So, if these startups take off, there 1707 01:13:11,950 --> 01:13:13,490 is an opportunity for return. 1708 01:13:13,490 --> 01:13:15,520 But, frankly, they're not expecting it. 1709 01:13:15,520 --> 01:13:16,860 So that has actually worked. 1710 01:13:16,860 --> 01:13:18,710 And Rafael has just been able to demonstrate 1711 01:13:18,710 --> 01:13:23,235 that you can raise money on the basis of that kind of approach. 1712 01:13:23,235 --> 01:13:25,610 STEPH: And I think they're one of the interesting models. 1713 01:13:25,610 --> 01:13:26,690 And perhaps you've looked at this. 1714 01:13:26,690 --> 01:13:27,458 Maybe you haven't. 1715 01:13:27,458 --> 01:13:29,000 But it's the way in which art museums 1716 01:13:29,000 --> 01:13:30,833 and, in particular, contemporary art museums 1717 01:13:30,833 --> 01:13:33,620 pursue funding from philanthropists. 1718 01:13:33,620 --> 01:13:36,510 Because it's often that a lot of the contemporary artists that 1719 01:13:36,510 --> 01:13:38,690 are sort of on the leading edge are something 1720 01:13:38,690 --> 01:13:40,635 that people are very reticent to adopt. 1721 01:13:40,635 --> 01:13:42,260 So the museums that purchase their art, 1722 01:13:42,260 --> 01:13:43,843 either for their permanent collections 1723 01:13:43,843 --> 01:13:45,560 or for their temporary exhibits, often 1724 01:13:45,560 --> 01:13:48,620 allow their philanthropists to gain some sort of benefit 1725 01:13:48,620 --> 01:13:51,560 or value from having hosted that and having 1726 01:13:51,560 --> 01:13:52,880 attached their name to it. 1727 01:13:52,880 --> 01:13:54,890 And, later on, it is that, because art 1728 01:13:54,890 --> 01:13:57,110 is seen as a commodity and luxury good, 1729 01:13:57,110 --> 01:14:00,580 they're able to sort of gain capital return on it, as well. 1730 01:14:00,580 --> 01:14:02,330 So I think it could be interesting to look 1731 01:14:02,330 --> 01:14:05,150 at the ways in which museums and art museums specifically 1732 01:14:05,150 --> 01:14:07,536 do their philanthropy for technology. 1733 01:14:10,360 --> 01:14:10,860 CHRIS: Sure. 1734 01:14:10,860 --> 01:14:11,370 Go ahead. 1735 01:14:11,370 --> 01:14:11,690 STUDENT: Well, I think there's-- 1736 01:14:11,690 --> 01:14:12,840 OK. 1737 01:14:12,840 --> 01:14:15,420 There is also, like, purely private-sector 1738 01:14:15,420 --> 01:14:17,370 market-driven models. 1739 01:14:17,370 --> 01:14:22,230 I think a really good example is Autodesk., so right down here 1740 01:14:22,230 --> 01:14:23,230 by the seaport. 1741 01:14:23,230 --> 01:14:23,730 And-- 1742 01:14:23,730 --> 01:14:24,860 WILLIAM BONVILLIAN: Why don't you describe it. 1743 01:14:24,860 --> 01:14:25,443 STUDENT: Yeah. 1744 01:14:25,443 --> 01:14:27,720 So, Autodesk, they basically want 1745 01:14:27,720 --> 01:14:31,110 to become the software company for any CAD, CNC, 1746 01:14:31,110 --> 01:14:33,090 anything that you want to make. 1747 01:14:33,090 --> 01:14:36,490 And so they have a fellowship program here, and then-- 1748 01:14:36,490 --> 01:14:39,240 so Auto-- they're MIT startups who work in their 1749 01:14:39,240 --> 01:14:41,700 build space at the innovation building. 1750 01:14:41,700 --> 01:14:45,798 And they also-- like, Pier 9 is, like, probably the best maker 1751 01:14:45,798 --> 01:14:46,590 space in the world. 1752 01:14:46,590 --> 01:14:48,630 And they have [INAUDIBLE] come in. 1753 01:14:48,630 --> 01:14:50,880 For them, they get a lot of value out of it, 1754 01:14:50,880 --> 01:14:56,460 because these innovators are testing their software 1755 01:14:56,460 --> 01:14:58,380 and pushing it to its limits and giving them 1756 01:14:58,380 --> 01:14:59,930 ideas for new features. 1757 01:14:59,930 --> 01:15:03,960 Also, when those startups hit market, 1758 01:15:03,960 --> 01:15:06,660 Autodesk really helped make that possible. 1759 01:15:06,660 --> 01:15:08,460 So there's a lot of benefit to them. 1760 01:15:08,460 --> 01:15:12,790 And they give these people working on hard technologies 1761 01:15:12,790 --> 01:15:14,998 a really great working space to develop their stuff. 1762 01:15:14,998 --> 01:15:17,040 WILLIAM BONVILLIAN: Chris, do you want to give us 1763 01:15:17,040 --> 01:15:18,570 a few closing thoughts on this? 1764 01:15:18,570 --> 01:15:19,320 CHRIS: Yeah, sure. 1765 01:15:19,320 --> 01:15:21,653 WILLIAM BONVILLIAN: You had some very perceptive opening 1766 01:15:21,653 --> 01:15:22,500 comments. 1767 01:15:22,500 --> 01:15:23,000 CHRIS: Cool. 1768 01:15:23,000 --> 01:15:23,500 Yeah. 1769 01:15:23,500 --> 01:15:28,500 So, I think one thing we didn't really get a chance to touch on 1770 01:15:28,500 --> 01:15:34,050 was that climate change and, like, the whole energy sector 1771 01:15:34,050 --> 01:15:37,110 is kind of a different beast from a lot of different kind 1772 01:15:37,110 --> 01:15:40,860 of sectors, because the way you evaluate 1773 01:15:40,860 --> 01:15:45,645 how "good" a technology is, is kind of a much longer time 1774 01:15:45,645 --> 01:15:49,590 span than, say, I don't know, biotech, where you can 1775 01:15:49,590 --> 01:15:52,230 immediately see the impacts. 1776 01:15:52,230 --> 01:15:53,670 I mean, the drug works or not. 1777 01:15:53,670 --> 01:15:54,170 Right? 1778 01:15:54,170 --> 01:15:55,260 You can immediately tell. 1779 01:15:55,260 --> 01:15:58,110 But, for climate change, sure, you can, I don't know, 1780 01:15:58,110 --> 01:16:01,650 measure carbon emissions year by year or something like that. 1781 01:16:01,650 --> 01:16:05,250 But then you run the risk of, policies, 1782 01:16:05,250 --> 01:16:07,710 social mindset, or whatever, shifting, 1783 01:16:07,710 --> 01:16:11,880 once maybe you get on a trend of seeing some improvement, 1784 01:16:11,880 --> 01:16:15,210 and then you might just shift and completely erase 1785 01:16:15,210 --> 01:16:18,490 what you've done in the past year or so. 1786 01:16:18,490 --> 01:16:21,840 So, definitely, the longer time span makes it more difficult, 1787 01:16:21,840 --> 01:16:24,930 not only for funding but also, like, development, 1788 01:16:24,930 --> 01:16:25,920 implementation. 1789 01:16:25,920 --> 01:16:30,390 And I think a lot of these new models, 1790 01:16:30,390 --> 01:16:32,970 like the innovation orchards, TechBridge, 1791 01:16:32,970 --> 01:16:35,760 these models are really cool and should 1792 01:16:35,760 --> 01:16:38,487 be interesting to see how they play out. 1793 01:16:38,487 --> 01:16:39,570 WILLIAM BONVILLIAN: Great. 1794 01:16:39,570 --> 01:16:42,237 Martha, do you want to give us a thought from MITI's perspective 1795 01:16:42,237 --> 01:16:46,110 about some of these new models? 1796 01:16:46,110 --> 01:16:51,743 MARTHA: So-- well, I guess that-- 1797 01:16:51,743 --> 01:16:53,410 Bill, you kind of caught me by surprise. 1798 01:16:53,410 --> 01:16:54,120 I've been holding back-- 1799 01:16:54,120 --> 01:16:54,395 WILLIAM BONVILLIAN: Sorry. 1800 01:16:54,395 --> 01:16:55,145 MARTHA: That's OK! 1801 01:16:55,145 --> 01:16:57,103 That's all right. 1802 01:16:57,103 --> 01:16:58,770 I think-- well, first of all, Chris just 1803 01:16:58,770 --> 01:17:00,353 touched on something really important, 1804 01:17:00,353 --> 01:17:02,880 which is that one of the big challenges-- 1805 01:17:02,880 --> 01:17:04,560 and I think I've mentioned this before-- 1806 01:17:04,560 --> 01:17:07,140 is that, traditionally, energy technologies take 1807 01:17:07,140 --> 01:17:09,010 decades to get adopted. 1808 01:17:09,010 --> 01:17:12,690 And just the pie chart on the VCs [LAUGH] 1809 01:17:12,690 --> 01:17:17,310 tells you something about what energy technologies are 1810 01:17:17,310 --> 01:17:19,840 competing against for capital. 1811 01:17:19,840 --> 01:17:22,440 I guess that this is a great model, 1812 01:17:22,440 --> 01:17:24,480 if it could get replicated, you know, 1813 01:17:24,480 --> 01:17:27,180 and even break through energy ventures, which 1814 01:17:27,180 --> 01:17:28,530 is a different model. 1815 01:17:28,530 --> 01:17:33,640 I mean, this is an earlier stage, helping people get past. 1816 01:17:33,640 --> 01:17:38,570 It feels like things move slowly. 1817 01:17:38,570 --> 01:17:43,050 And, like everything related to this whole energy challenge, 1818 01:17:43,050 --> 01:17:45,750 we need to kind of pick up the pace. 1819 01:17:45,750 --> 01:17:47,760 And, Bill, you talked about the states 1820 01:17:47,760 --> 01:17:49,780 and that there's different players. 1821 01:17:49,780 --> 01:17:50,530 It's challenging. 1822 01:17:50,530 --> 01:17:51,030 Right? 1823 01:17:51,030 --> 01:17:54,150 I mean, the states just don't have the kind of-- 1824 01:17:54,150 --> 01:17:56,480 first of all, they compete against each other. 1825 01:17:56,480 --> 01:17:58,220 They also just don't have the resources. 1826 01:17:58,220 --> 01:18:00,970 So we'll see where we end up.